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Books ↑

1,2→ Research monographs; 3→ Edited Book; 4,5→ Edited Conference Proceedings

  1. D. P. Mandic and S. L. Goh, Complex Valued Nonlinear Adaptive Filters: Noncircularity, Widely Linear and Neural Models, Research Monograph in the Wiley Series in Adaptive and Learning Systems for Signal Processing, Communications, and Control, ISBN-10: 0470066350, John Wiley & Sons, 2009.
  2. D. P. Mandic, M. Golz, A. Kuh, D. Obradovic, and T. Tanaka (Editors), Signal Processing Techniques for Knowledge Extraction and Information Fusion, ISBN-10: 0387743669, Springer, 2008.
  3. J. Marques de Sa, L. Alexandre, W. Duch, and D. P. Mandic (Editors), Proceedings of the 17th International Conference on Artificial Neural Networks - ICANN 2007. Part I , Lecture Notes in Computer Science, LNCS4668, ISBN-10: 3-540-74689-7, Springer, 2007.
  4. J. Marques de Sa, L. Alexandre, W. Duch, and D. P. Mandic (Editors), Proceedings of the 17th International Conference on Artificial Neural Networks - ICANN 2007. Part II , Lecture Notes in Computer Science, LNCS4669, ISBN-10: 3-540-74693-5, Springer, 2007.
  5. D. P. Mandic and J. A. Chambers, Recurrent Neural Networks for Prediction: Learning Algorithms, Architectures, and Stability, Wiley Series in Adaptive and Learning Systems for Signal Processing, Communications, and Control, ISBN0471495174 (Print), John Wiley & Sons, 2001.
    1. Also in Electronic Form, ISBN 047084535X, Wiley InterScience, 2002.

Edited volumes ↑

  1. H. Kiya, D. P. Mandic, et al. Guest Editors, Special Issue of IEICE Transactions on Fundamentals of Electronics, communications and Computer Sciences (Japan) entitled "Latest Advances in Fundamental Theories of Signal Processing", vol. E92-A, no. 3, March 2009.
  2. W. Duch and D. P. Mandic, Guest Editors, Special Issue of Elsevier Neural Networks entitled "Computational Biologically Inspired Neural Networks", vol. 21, no. 6, 2008.
  3. D. Ergodmus, D. P. Mandic, and T. Tanaka, Guest Editors, Special Issue of Elsevier Neurocomputing entitled "Advances in Blind Signal Processing", to appear Spring 2008.
  4. D. P. Mandic and D. Obradovic, Guest Editors, Special Issue of Journal of VLSI Signal Processing (Springer) entitled "Data Fusion for Industrial, Biomedical and Environmental Applications", vol. 49, no. 2, 2007.
  5. A. K. Barros, D. P. Mandic and J. Larsen, Guest Editors, Special Issue of Journal of VLSI Signal Processing (Springer), entitled "Machine Learning for Signal Processing", vol. 45, no. 1, October 2006

Refereed journals ↑

  1. N. Rehman and D. P. Mandic,,"Multivariate Empirical Mode Decomposition", accepted for publication in the Proceedings of the Royal Society A, November 2009.
  2. N. Rehman and D. P. Mandic,"Empirical Mode Decomposition for Trivariate Signals", accepted for publication in IEEE Transactions on Signal Processing, October, 2009.
  3. C. Ujang--Bukari, C. Cheong-Took, and D. P. Mandic,"Split--Quaternion Nonlinear Adaptive Filtering", accepted for publication in Neural Networks, October 2009.
  4. C. Boukis, D. P. Mandic, and A. Constantinides,,"A Modified Armijo Rule for Online Learning Rate Adaptation", accepted for publication in Digital Signal Processing, September 2009.
  5. T. Rutkowski, T. Tanaka, A. Cichocki, D. Erickson, and D. P. Mandic,"Interactive Components Extraction from fEEG and fNIRS for Affective Brain Machine Interfaces", (invited paper) in Computers in Human Behavior, accepted for publication, June 2009.
  6. W. Y. Leong and D. P. Mandic,"Noisy Component Extraction (NoiCE)", accepted for publication in IEEE Transactions on Circuits and Systems I, May 2009.
  7. C. Cheong Took and D. P. Mandic,"Adaptive IIR Filtering of Noncircular Signals", IEEE Transactions on Signal Processing, vol. 57, no. 10, pp. 4111--4118, 2009.
  8. T. Rutkowski, D. P. Mandic, A. Cichocki, and A. Przybyszewski,"EMD Approach to Multichannel EEG Data Analysis - The Amplitude and Phase Components Clustering", (invited paper) Journal of Circuits, Systems, and Computers, accepted for publication, July 2009.
  9. Y. Yuan, Y. Li, and D. P. Mandic,"Regular Nonlinear Response of the Driven Duffing Oscillator to Chaotic Time Series", Chinese Physics B, vol. 18, no. 3, pp. 958--968, 2009.
  10. B. Jelfs, S. Javidi, P. Vayanos, and D. P. Mandic,"Characterisation of Signal Modality: Exploiting Signal Nonlinearity in Machine Learning and Signal Processing", (invited paper) Journal of Signal Processing Systems, pp. 1--11, April 2009.
  11. C. Boukis, D. P. Mandic, and A. G. Constantinides, "Introducing Stochastic Gradient Descent Algorithms with Exponential Cost Functions", Digital Signal Processing, vol. 19, no. 2, pp. 201--212, 2009.
  12. C. Cheong Took and D. P. Mandic,"The Quaternion LMS Algorithm for Adaptive Filtering of Hypercomplex Processes", IEEE Transactions on Signal Processing, vol. 57, no. 4, pp. 1316-1327, 2009.
  13. D. Looney and D. P. Mandic,"Multi-Scale Image Fusion using Complex Extensions of EMD", IEEE Transactions on Signal Processing, vol. 57, no. 4, pp. 1626-1630, 2009.
  14. Y. Yuan, Y. Li, and D. P. Mandic,"Comparison Analysis of Embedding Dimension between Normal and Epileptic EEG Time Series", the Journal of Physiological Sciences, vol. 58, no. 4, pp. 239-247, 2008.
  15. D. P. Mandic and W. Duch,"Preface: Computational and Biological Inspired Neural Networks", Neural Networks, vol. 21, no. 6, pp. 1-2, 2008.
  16. D. P. Mandic, S. Javidi, S. L. Goh, A. Kuh and K. Aihara,"Complex Valued Prediction of Wind Profile Using Augmented Complex Statistics", Renewable Energy , vol. 34, no. 1, pp. 196-210, 2009.
  17. D. P. Mandic, P. Vayanos, M. Chen, and S. L. Goh,"Online Detection of the Modality of Complex Valued Real World Signals", International Journal of Neural Systems , vol. 18, no. 2, pp. 67-74, 2008.
  18. W. Y. Leong and D. P. Mandic,"Post-Nonlinear Blind Extraction in the Presence of Ill-Conditioned Mixing", IEEE Transactions on Circuits and Systems I, vol. 55, no. 9, pp. 2631--2638, 2008.
  19. D. P. Mandic, M. Chen, T. Gautama, M. M. Van Hulle, and A. G. Constantinides"On the Characterisation of the Deterministic/Stochastic and Linear/Nonlinear Nature of Time Series", Proceedings of the Royal Society A, vol. 464, no. 2093, pp. 1141--1160, 2008.
  20. D. Erdogmus, D. P. Mandic, and T. Tanaka, "Guest Editorial: Advances in Blind Signal Processing", Neurocomputing, Special Issue on Advances in Blind Source Separation, vol. 71, no. 10-12, pp. 2069-2070, 2008.
  21. W. Leong, W. Liu, and D. P. Mandic, "Blind Source Extraction: Standard Approaches and Extensions to Noisy and Post-Nonlinear Mixing", Neurocomputing, Special Issue on Advances in Blind Source Separation, vol. 71, no. 10-12, pp. 2344-2355, 2008.
  22. M. Pedzisz and D. P. Mandic, "A Homomorphic Neural Network for Modelling and Prediction", Neural Computation, vol. 20, no. 4, pp. 1042-1064, 2008.
  23. M. Chen, T. Gautama, and D. P. Mandic, "An Assessment of Qualitative Performance of Machine Learning Architectures: Modular Feedback Networks", IEEE Transactions on Neural Networks, vol. vol. 19, no. 1, pp. 183-189, 2008.
  24. Y. Hirata, D. P. Mandic, H. Suzuki, and K. Aihara, "A Collaborative Approach to the Modelling of Real World Vector Fields: Predicting the Wind Direction", Philosophical Transactions of the Royal Society, vol. 366, pp. 591-607, 2008.
  25. S. L. Goh and D. P. Mandic, "An Augmented ACRTRL for Complex Valued Recurrent Neural Networks", Elsevier Neural Networks, vol. 20, no. 10, pp. 1061-1066, 2007.
  26. C. Boukis, D. P. Mandic, and A. Constantinides, "Towards Bias Minimisation in Acoustic Feedback Cancellation Systems", Journal of the Acoustic Society of America, vol. 121, no. 3, pp. 1529-1537, 2007.
  27. T. Tanaka and D. P. Mandic, "Complex Empirical Mode Decomposition", IEEE Signal Processing Letters, vol. 14, no. 2, pp. 101-104, 2007.
  28. W. Liu, D. P. Mandic, and A. Cichocki, "Analysis and Online Realization of the CCA Approach for Blind Source Separation", IEEE Transactions on Neural Networks, vol. 18, no. 5, pp. 1505-1510, 2007.
  29. S. L. Goh and D. P. Mandic, "Stochastic Gradient Adaptive Complex-Valued Nonlinear Neural Adaptive Filters with a Gradient Adaptive Step Size", IEEE Transactions on Neural Networks, vol. 18, no. 5, pp. 1511-1516, 2007.
  30. D. P. Mandic, S. L. Goh, and K. Aihara, "Sequential Data Fusion via Vector Spaces: Fusion of Heterogeneous Data in the Complex Domain", invited paper for the International Journal of VLSI Signal Processing Systems, vol. 48, no. 1-2, pp. 98-108, 2007.
  31. S. L. Goh and D. P. Mandic "An Augmented Extended Kalman Filter Algorithm for Complex-Valued Recurrent Neural Networks", Neural Computation, vol. 19, no. 4, pp. 1-17, 2007.
  32. R. Palaniappan and D. P. Mandic, "Energy of Brain Potentials Evoked During Visual Stimulus: A New Biometric?", International Journal of VLSI Signal Processing Systems, Special Issue on Data Fusion, vol. 49, no. 2, pp. 243-250, 2007.
  33. T. M. Rutkowski and D. P. Mandic, "Communicative Interactivity -A Multimodal Communicative Situation Classification Approach", International Journal of VLSI Signal Processing Systems, Special Issue on Data Fusion, vol. 49, no. 4, pp. 738-742, 2007.
  34. D. Sommer, M. Chen, M. Golz, U. Trutschell and D. P. Mandic, "Fusion of State Space and Frequency-Domain Features for Improved Microsleep Detection", International Journal of VLSI Signal Processing Systems, Special Issue on Data Fusion, vol. 49, no. 2, pp. 243-250, 2007.
  35. T. Tanaka and D. P. Mandic, "Complex Empirical Mode Decomposition", IEEE Signal Processing Letters, vol. 14, no. 2, pp. 101-104, 2007.
  36. R. Palaniappan and D. P. Mandic, "Biometric from the Brain Electrical Activity: A Machine Learning Approach", IEEE Transactions in Pattern Analysis and Machine Intelligence (Special Issue on Biometrics), vol. 29, no. 4, pp. 738-742, 2007.
  37. C. Boukis, D. P. Mandic, A. G. Constantinides, and L. C. Polymenakos, "A Novel Algorithm for the Adaptation of the Pole of Laguerre Fitlers", IEEE Signal Processing Letters, Vol. 13, No. 7, pp. 429 - 432, 2006.
  38. W. Liu and D. P. Mandic, "A Normalised Kurtosis Based Algorithm for Blind Source Extraction from Noisy Measurements", Signal Processing, Vol. 86, pp. 1580 - 1585, 2006.
  39. C. Boukis, D. P. Mandic, and A. Constantinides, "Bias Reduction in Acoustic Feedback Cancellation Systems with Varying All-Pass Filters", IEE Electronics Letters, Vol. 42, No. 9, pp. 556 - 558, 2006.
  40. W. Liu, D. P. Mandic, and A. Cichocki, "Blind Second-order Source Extraction of Instantaneous Noisy Mixtures", IEEE Transactions on Circuits and Systems II, vol. 53, no. 9, pp. 931-935, 2006.
  41. A. K. Barros, D. P. Mandic, and J. Larsen, "Introductory Note - Special Issue on Machine Learning", International Journal of VLSI Signal Processing Systems, vol. 45, pp. 5-6, 2006.
  42. W. Leong, D. P. Mandic, and J. Homer, "Implementing Nonlinear Multiuser Detection in Rayleigh Fading Channel", EURASIP Journal on Wireless Communications and Networking, Vol. 2006, pp. 1 - 9, 2006.
  43. S. L. Goh, M. Chen, D. H. Popovic, K. Aihara, D. Obradovic and D. P. Mandic, "Complex Valued Forecasting of Wind Profile", Renewable Energy, vol. 31, pp. 1733-1750, 2006.
  44. S. L. Goh and D. P. Mandic, "Nonlinear Adaptive Prediction of Complex Valued Nonstationary Signals", IEEE Transactions on Signal
    Processing    , Vol. 53, No. 5, pp. 1827 - 1836, 2005.
  45. S. L. Goh and D. P. Mandic, "A General Complex RTRL Algorithm for Nonlinear Adaptive Filters", Neural Computation, Vo. 16, No. 12, pp. 2699-2713, 2004.
  46. T. Gautama, D. P. Mandic, and M. M. Van Hulle, "A Novel Method for Determining the Nature of Time Series", IEEE Transactions on Biomedical Engineering, Vol. 51, No. 5, pp. 728-736, 2004.
  47. T. Gautama, D. P. Mandic and M. M. Van Hulle, "A Non-parametric Test for Detecting the Complex-valued Nature of Time Series", Invited for a special issue of the International Journal of Knowledge-Based Intelligent Engineering Systems, Vol. 8, No. 2, pp. 99-106, 2004.
  48. G. C. Cawley, N. L. Talbot, R. J. Foxall, S. R. Dorling, and D. P. Mandic, "Heteroscedastic Kernel Ridge Regression", (invited paper), Neurocomputing, Vol. 57, pp. 477-484, 2004.
  49. D. P. Mandic, "A Generalised Normalised Gradient Descent Algorithm", IEEE Signal Processing Letters, Vol. 11, No. 2, pp. 115-118, 2004.
  50. M. G. Jafari, J. A. Chambers, and D. P. Mandic, "A Novel Adaptive Learning Rate Sequential Blind Source Separation Algorithm", Elsevier Signal Processing, Vol. 84, pp. 801-804, 2004
  51. A. I. Hanna and D. P. Mandic, "On An Improved Approach to Nonlinear System Identification Using Neural Networks", Journal of the Franklin Institute, Vol. 340, pp. 363 - 370, 2003.
  52. T. Gautama, D. P. Mandic, and M. M. Van Hulle, "The Delay Vector Variance Method for Detecting Determinism and Nonlinearity in Time Series", Physica D, Vol. 190, pp. 167-176, 2004.
  53. S. L. Goh and D. P. Mandic, "Recurrent Neural Networks with Trainable Amplitude of Activation Functions", Neural Networks, Vol. 16, pp. 1095 - 1100, 2003.
  54. A. Palmer, M. Razaz, and D. P. Mandic, "A Spatially - Adaptive Neural Network Approach to Regularized Image Restoration" (invited paper), "Journal of Intelligent & Fuzzy Systems, vol. 13, pp. 177 - 185, 2003.
  55. A. I. Hanna and D. P. Mandic, "A General Fully Adaptive Normalised Gradient Descent Learning Algorithm For Complex-Valued Nonlinear Adaptive Filters", IEEE Transactions on Signal Processing, Vol. 51, No. 10, pp. 2540 - 2549,2003.
  56. S. R. Dorling, R. J. Foxall, D. P. Mandic, and G. C. Cawley, "Penalised Maximum Likelihood Cost Functions for Neural Network Models of Air Quality Data", Elsevier Atmospheric Environment, Vol. 37, No. 24, pp. 3435 - 3443, 2003.
  57. T. Gautama, D. P. Mandic, and M. M. Van Hulle, "On the Analysis of Nonlinearity in fMRI Signals: Comparing BOLD to MION", IEEE Transactions on Medical Imaging, Vol. 22, No. 5, pp. 636 - 644, 2003.
  58. T. Gautama, D. P. Mandic, and M. M. Van Hulle, "On the Indications of Nonlinear Structures in Brain Electrical Activity", Virtual Journal of Biological Physics Research (Selected Papers from Physical Review E), Volume 5, Issue 8, 2003.
  59. T. Gautama, D. P. Mandic, and M. M. Van Hulle, "On the Indications of Nonlinear Structures in Brain Electrical Activity", Physical Review E, Vol. 67, No. 4, pp. 046204 - 1 - 046204 - 5, 2003.
  60. A. S. Palmer, M. Razaz, and D. P. Mandic, "Spatially - Adaptive Image Restoration Using a Nonlinear Feedback Network" (invited paper), Journal of Applied Soft Computing, in print, 2003.
  61. S. L. Goh, D. P. Mandic and M. M. Bozic, "A Nonlinear Neural Adaptive Filter with a Trainable Amplitude of Nonlinearity", invited paper to Journal of Automatic Control, Special Issue on Neural Networks, Vol. 13, No. 1, pp. 1-5, 2003.
  62. A. I. Hanna and D. P. Mandic, "Complex - Valued Nonlinear Neural Adaptive Filters with Trainable Amplitude ofActivation Functions", Neural Networks, Vol. 16, No. 2, pp. 155 - 159, 2003.
  63. A. I. Hanna and D. P. Mandic, "A Data - Reusing Nonlinear Gradient Descent Algorithm for a Class of Complex - Valued Nonlinear Adaptive Filters", Neural Processing Letters, Vol. 17, pp. 85 - 91, 2003.
  64. A. I. Hanna and D. P. Mandic, "A Nonlinear Adaptive Filter with a Gradient Adaptive Amplitude of the Nonlinearity", IEEE Signal Processing Letters, Vol. 9, No. 8, pp. 253 - 255, 2002.
  65. M. G. Jafari, J. A. Chambers, and D. P. Mandic, "A Natural Gradient Algorithm for Cyclostationary Sources", IEE Electronics Letters, Vol. 38, No. 14, pp. 758 - 759, 2002.
  66. D. P. Mandic, "Data - Reusing Recurrent Neural Adaptive Filters", Neural Computation, Vol. 14, No. 11, 2693 - 2708,2002.
  67. Z. V. Babic and D. P. Mandic, "A Fast Algorithm for Linear Convolution of Discrete Time Signals", (Invited Paper), Facta Universitatis: Series Electronics and Energetics, Vol. 14, No. 3, pp. 399 - 409, 2001.
  68. D. P. Mandic, A. I. Hanna, and M. Razaz, "A Normalised Nonlinear Gradient Descent Algorithm with a Gradient Adaptive Step Size", IEEE Signal Processing Letters, Vol. 8, No. 11, pp. 295 - 297, 2001.
  69. D. P. Mandic and I. R. Krcmar, "Stability of the NNGD Algorithm for Nonlinear System Identification", Electronics Letters, Vol. 37, No. 3, pp. 200 - 202, 2001.
  70. D. P. Mandic and J. A. Chambers, "A Normalised Real Time Recurrent Learning Algorithm", Signal Processing, Vol.80, No. 9, pp. 1909 - 1916, 2000.
  71. D. P. Mandic and J. A. Chambers, "Advanced RNN Based NARMA Predictors", (Invited paper), Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology, Vol. 26, No. 1/2, pp. 105 - 117, 2000.
  72. D. P. Mandic and J. A. Chambers, "Relationships Between the A Priori and A Posteriori Errors in Nonlinear Adaptive Filters", Neural Computation, Vol. 12, No. 6, pp. 1285 - 1292, 2000.
  73. D. P. Mandic, "The NNGD Algorithm for Neural Adaptive Filters", Electronics Letters, Vol. 36, No. 9, pp. 845 - 846,2000.
  74. D. P. Mandic and J. A. Chambers, "On the Choice of Parameters of the Cost Function in Nested Modular RNNs", IEEE Transactions on Neural Networks, Vol. 11, No. 2, pp. 315 - 322, 2000.
  75. D. P. Mandic and J. A. Chambers, "On Robust Stability of Time-Variant Discrete-Time Nonlinear Systems with Bounded Parameter Perturbations", IEEE Transactions on Circuits and Systems - I: Fundamental Theory and Applications, Vol.47, No. 2, pp. 185 - 188, 2000.
  76. D. P. Mandic and J. A. Chambers, "Towards an Optimal Learning Rate for Back propagation", Neural Processing Letters,Vol. 11, No. 1, pp. 1-5, 2000.
  77. D. P. Mandic and J. A. Chambers, "On Stability of Relaxive Systems Described by Polynomials with Time-Variant Coefficients", IEEE Transactions on Circuits and Systems - I: Fundamental Theory and Applications, Vol. 47, No. 10, pp. 1534 - 1537, 2000.
  78. D. P. Mandic, "Nonlinear Activation Function and PDF for Nonlinear Prediction via Recurrent Neural Networks", Electronics, Vol. 3, No. 1, pp. 66 - 68, 1999.
  79. D. P. Mandic and J. A. Chambers, "Relationship Between the Slope of the Activation Function and the Learning Rate for the RNN", Neural Computation, Vol. 11, No. 5, pp. 1069-1077, 1999.
  80. D. P. Mandic and J. A. Chambers, "Toward an Optimal PRNN Based NARMA Predictor", IEEE Transactions on Neural Networks, Vol. 10, No. 6, pp. 1435 - 1442, 1999.
  81. D. P. Mandic and J. A. Chambers, "Exploiting Inherent Relationships in RNN Architectures", Neural Networks, Vol. 12,No. 10, pp. 1341 - 1345, 1999.
  82. D. P. Mandic and J. A. Chambers, "A Posteriori Error Learning in Nonlinear Adaptive Filters", IEE Proceedings-Vision, Image and Signal Processing, Vol. 146, No. 6, pp. 293 - 296, 1999.
  83. D. P. Mandic and J. A. Chambers, "A Posteriori Real Time Recurrent Learning Schemes for a Recurrent Neural Network Based Nonlinear Predictor", IEE Proceedings - Vision, Image and Signal Processing, Vol. 145, No. 6, pp. 365-370, 1998.

Refereed conferences and workshops ↑

  1. D. P. Mandic, P. Vayanos, C. Boukis, B. Jelfs, S. L. Goh, T. Gautama, and T.Rutkowski, "Collaborative Adaptive Learning Using Hybrid Filters", in Proceedings of ICASSP 2007, vol. III, pp. 921-924, 2007.
  2. W. Y. Leong, D. P. Mandic, and W. Liu, "Blind Extraction of Noisy Events Using Nonlinear Predictor", in Proceedings of ICASSP 2007, vol. II, pp. 657-660, 2007.
  3. M. U. B. Altaf, T. Gautama, T. Tanaka, and D. P. Mandic, "Rotation Invariant Empirical Mode Decomposition", in Proceedings of ICASSP 2007, vol. III, pp. 1009-1012,2007.
  4. M. Chen, T. M. Rutkowski, B. Jelfs, G. Souretis, J. Cao, and D. P. Mandic, "Assessment of Nonlinearity in Brain Electrical Activity: A DVV Approach", in Proceedings of the 2007 RISP International Workshop in Nonlinear Circuits and Signal Processing, pp.461-464, 2007.
  5. B. Jelfs and D. P. Mandic, "Toward Online Monitoring of the Changes in Signal Modality: The Degree of Sparsity", in Proceeedings of the 7th IMA International Conference on Mathematics for Signal Processing, pp. 29-32, 2006.
  6. M. Chen, D. P. Mandic, T. Gautama, and M. Griselli, "Nonlinear Schemes for Heart Valve Failure Detection", in Proceeedings of the 7th IMA International Conference on Mathematics for Signal Processing, pp. 81-84, 2006.
  7. W. Leong and D. P. Mandic, "Towards Blind Separation of Nonlinearly Mixed Sources", in Proceeedings of the 7th IMA International Conference on Mathematics for Signal Processing, pp. 178-181, 2006.
  8. A. Wautier, L. Husson, and D. P. Mandic, "Algorithms for BER-Constrained Variable Length Equalizers driven by Channel Response Knowledge over Frequency-Selective Radio Channels", accepted for VTC2007-Spring, December 2007.
  9. Y. Washizawa, T. Tanaka, D. P. Mandic, and A. Cichocki, "Bandwidth Control in Empirical Mode Decomposition" (in Japanese), in Proceedings of the 21st Japanese Signal Processing Conference (SIP-06), Kyoto 15-17 November, proceedings on CD, 2006.
  10. T. Tanaka, T. Gautama, and D. P. Mandic, "Extentions of Empirial Mode Decomposition to Complex-Valued Signals", in Proceedings of the 21st Japanese Signal Processing Conference (SIP-06), Kyoto 15-17 November, proceedings on CD, 2006.
  11. D. P. Mandic and V. S. L. Goh, "Adaptive Filtering in the Complex Domain:- Nonlinear Filters and Augmented Statistics", in Proceedings of the 21st Japanese Signal Processing Conference (SIP-06), Kyoto 15-17 November, proceedings on CD, 2006.
  12. A. Kuh, C. Zhu, and D. P. Mandic, "Sensor Network Localization Using Least Squares Kernel Regression", in Proceedings of the 10th International Conference on Knowledge Based & Intelligent Information & Engineering Systems, KES-06, pp. 1280-1287, 2006.
  13. M. Chen, T. Gautama, D. Obradovic, J. Chambers, and D. P. Mandic, "Exploiting Signal Non - Gaussianity and Nonlinearity for Performance Assessment of Adaptive Filtering Algorithms: Qualitative Performance of Kalman Filter", accepted for the NSSPW Workshop, Cambridge, June 2006.
  14. W. Y. Leong, J. Homer, D. P. Mandic, and Z. Babic, "A Two-Stage Algorithm for Post-Nonlinear Blind Source Separation", accepted for NEUREL 2006, August 2006.
  15. W. Y. Leong and D. P. Mandic, "Towards Adaptive Blind Extraction of Post--Nonlinearly Mixed Signals", accepted for the IEEE MLSP Workshop, June 2006.
  16. M. Chen, D. Sommer, S. L. Goh, T. Gautama, D. Obradovic, M. Golz, M. Morrell, D. P. Mandic, "A Novel Tool for Sequential Fusion of Nonlinear Features: A Sleep Psychology Application", accepted for MFI2006, June 2006.
  17. W. Leong, D. P. Mandic, and J. Chambers, "Blind Sequential Extraction of Ill - Conditioned Post - Nonlinearly Mixed Sources", accepted for the NSSPW Workshop, Cambridge, June 2006.
  18. P. Vayanos, S. L. Goh, and D. P. Mandic, "Online Detection of the Nature of Complex-Valued Signals", accepted for the IEEE MLSP Workshop, June 2006.
  19. M. Chen, T. Gautama, M. Van Hulle, and D. P. Mandic, "Towards Qualitative Assessment of Machine Learning Algorithms: Utilising Signal Modality Characterisation", accepted for the IEEE MLSP Workshop, June 2006.
  20. M. Golz, D. Sommer, and D. P. Mandic, "Establishing a Gold Standard for Drivers Microsleep Detection", (Best Poster Award), in Proceedings of the International Conference "Monitoring Sleep and Sleepiness - from Physiology to New Sensors", 29-30 May 2006 Basel, Switzerland, Proceedings on CD, 2006.
  21. B. Jelfs, P. Vayanos, M. Chen, S. L. Goh, C. Boukis, T. Gautama, T. Rutkowski, A. Kuh, and D. P. Mandic, "An Online Method For Detecting Nonlinearity Within a Signal", accepted for KES - 2006, 2006.
  22. T. M. Rutkowski, F. Vialatte, A. Cichocki, D. P. Mandic, and A. K. Barros, "Auditory Feedback for Brain Computer Interface Management - An EEG Data Sonification Approach", accepted for KES - 2006, 2006.
  23. Y. Washizawa, T. Tanaka, D. P. Mandic, and A. Cichocki, "A Flexible Method for Envelope Estimation in Empirical Mode Decomposition", accepted for KES - 2006, 2006.
  24. Y. Hirata, H. Suzuki, K. Aihara and D. P. Mandic, "Predicting the wind direction using observations taken from two separate points", in Proceedings of the Experimenal Chaos Conference, 2006.
  25. W. Liu, D. P. Mandic and A. Cichocki, "An Analysis of the CCA Approach for Blind Source Separation and its adaptive realization", accepted for ISCAS 2006, January 2006.
  26. W. Liu, D. P. Mandic and A. Cichocki, "Blind Source Extraction of Instantaneous Noisy Mixtures Using a Linear Predictor", accepted for ISCAS 2006, January 2006.
  27. S. L. Goh and D. P. Mandic, "An Augmented Extended Kalman Filter Algorithm for Complex - Valued Recurrent Neural Networks", in Proceedings of ICASSP '06, Vol. V, pp. 561 - 564, 2006.
  28. W. Liu and D. P. Mandic, "A Normalised Kurtosis Based Blind Source Extraction Algorithm for Noisy Mixtures", in Proceedings of ICASSP '06, Vol. V, pp. 641 - 644, 2006.
  29. A. Kuh and D. P. Mandic, "Sequential Detection Using Least Squares Temporal Difference Methods", in Proceedings of ICASSP '06, Vol. V, pp. 701 - 704, 2006.
  30. A. B. Cavalcante, D. P. Mandic, T. M. Rutkowski, and A. K. Barros, "Speech Enhancement Based on the Response Features of Facilitated EI Neurons", in Proceedings of ICA 2006 (Springer Volume), pp. 585 - 592, 2006.
  31. D. P. Mandic, S. L. Goh and K. Aihara, "Sequential Data Fusion via Vector Spaces: A Modular Neural Network Approach", in Proceedings of the IEEE Workshop on Machine Learning for Signal Processing, pp. 147 - 151, 2005.
  32. D. Obradovic, A. Szabo, and D. P. Mandic, "Novel EM-based method for channel estimation and signal detection in MIMO-OFDM systems", in Proceedings of EUROCON '05, pp. 1795 - 1798, 2005.
  33. R. Palaniappan, D. Obradovic, and D. P. Mandic, "On Decision Making Ability of People Under Intoxicants Using Single Trial Visual Evoked Potential Signals", in Proceedings of EUROCON '05, pp. 413 - 416, 2005.
  34. P. A. Kountouriotis, S. L. Goh, D. Obradovic, and D. P. Mandic, "Multi-Step Forecasting Using Echo State Networks", in Proceedings of EUROCON '05, pp. 1574 - 1577, 2005.
  35. M. Golz, D. Sommer, and D. P. Mandic, "Microsleep Detection in Electrophysiological Signals", in Proceedings of ICINCO '05, pp. tba, 2005.
  36. T. M. Rutkowski and D. P. Mandic, "Communicative Interactivity -A Multimodal Communicative Situation Classification Approach", in Proceedings of ICANN '05, pp. 741 - 746, 2005.
  37. R. Palaniappan and D. P. Mandic, "Energy of Brain Potentials Evoked During Visual Stimulus: A New Biometric?", in Proceedings of ICANN '05, pp. 735 - 740, 2005.
  38. D. P. Mandic, D. Obradovic, A. Kuh, T. Adali, U. Trutschell, M. Golz, P. de Wilde, J. Barria, A. Constantinides, and J. Chambers "Data Fusion in Modern Engineering Applications: An Overview", in Proceedings of ICANN '05, 715 - 721, 2005.
  39. D. Sommer, M. Chen, M. Golz, U. Trutschell and D. P. Mandic, "Fusion of State Space and Frequency - Domain Features for Improved Microsleep Detection", in Proceedings of ICANN '05, pp. 753 - 759, 2005.
  40. D. P. Mandic, D. Obradovic, and A. Kuh, "A Robust General Normalised Gradient Descent Algorithm", in Proceedings of the IEEE Workshop on Statistical Signal Processing, pp. 133-136, 2005.
  41. W. Liu and D. P. Mandic, "A Class of Novel Blind Source Extraction Algorithms Based On a Linear Predictor", In Proceedings of the International Symposium on Circuits and Systems, ISCAS '05, Kobe Japan, pp. 3599 - 3602, 2005.
  42. S. L. Goh and D. P. Mandic, "A Class of Gradient - Adaptive Step Size Algorithms for Complex - Valued Nonlinear Neural Adaptive Filters", in Proceedings of the International Conference on Acoustics, Speech and Signal Processing, ICASSP2005, Vol. V, pp. 253 - 256, 2005.
  43. W. Liu and D. P. Mandic, "Semi-blind Source Separation for Convolutive Mixtures Based on Frequency Invariant Transformation", in Proceedings of the International Conference on Acoustics, Speech and Signal Processing, ICASSP2005, Vol. V, pp. 285 - 288, 2005.
  44. M. Chen, T. Gautama, M. Van Hulle, and D. P. Mandic, "On Nonlinear Modular Neural Filters", in Proceedings of the International Conference on Acoustics, Speech and Signal Processing, ICASSP2005, Vol. V. pp. 317 - 320, 2005.
  45. M. Chen, T. Gautama, M. Van Hulle, and D. P. Mandic, "A Class of Modular Recurrent Neural Networks: Preservation of Signal Modality", in Proceedings of the IMA Conference on Mathematics in Signal Processing, pp. 43 - 46, 2004.
  46. S. L. Goh and D. P. Mandic, "A Data Reusing Sign Error Algorithm for Complex Valued Adaptive Filters", in Proceedings of the IMA Conference on Mathematics in Signal Processing, pp. 87 - 90, 2004
  47. S. L. Goh, Z. Babic, D. Popovic, T. Tanaka, and D. Mandic, "Complex - Valued Neural Network Schemes for Online Processing of Wind Signal", Proceedings of NEUREL 2004, pp. 249 - 253, 2004.
  48. M. Chen, T. Gautama, M. Bozic, M. Van Hulle, and D. Mandic, "Does Iterative Nonlinear Neural Filtering Affect the Nature of the Processed Signal", Proceedings of NEUREL 2004, pp. 21 - 25, 2004.
  49. T. Tanaka and D. P. Mandic, "A Direct Design Framework for a Class of Oversampled Perfect Reconstruction Filter Banks", in Proceedings of the International Symposium on Communications and Information Technologies, ISCIT 2004, Saporro Janap, pp. 1059 - 1064, 2004.
  50. S. L. Goh and D. P. Mandic, "A Class Of Low Complexity and fast Converging Algorithms for Complex-Valued Neural Networks", in Proceedings of the International Workshop on Machine Learning for Signal Processing, MLSP2004, pp. 13 - 22, 2004.
  51. E. James, A. K. Barros, T. Yoshinori, D. P. Mandic, and N. Ohnichi, "Speech Enhancement by Lateral Inhibition and Binaural Masking", in Proceedings of the International Workshop on Machine Learning for Signal Processing, MLSP2004, pp. 365 - 360, 2004.
  52. S. L. Goh, D. Popovic and D. P. Mandic, "Complex Valued Estimation of Wind Profile and Wind Power", in Proceedings of Melecon 2004 (Best student paper award), Vol. 3, pp. 1037-1040, 2004.
  53. M. Chen and D. P. Mandic, "Quality Assessment of Hybrid Nonlinear Filters", Proceedings of ICASSP 2004,Vol. V, pp. 785-788, 2004.
  54. Z. V. Babic and D. P. Mandic, "An Efficient Small-Scale Noise Removal and Edge Preserving Convolution Filter", in Proceedings of the 6th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services, TELSIKS 2003, pp. 538-541, 2003.
  55. S. L. Goh, Z. V. Babic and D. P. Mandic, "An Adaptive Amplitude Learning Algorithm for Nonlinear Adaptive IIRFilters", in Proceedings of the 6th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services, TELSIKS 2003, pp. 313 - 316, 2003.
  56. D. P. Mandic, A. Cichocki and U. Manmontri, "An On - Line Algorithm for Blind Source Extraction Based on Nonlinear Prediction Approach", in Proceedings of the IEEE Workshop on Neural Networks for Signal Processing, NNSP 2003,September 17 - 19, Toulouse, France, pp. 429 - 438, 2003.
  57. S. L. Goh and D. P. Mandic, "Nonlinear Adaptive Prediction Using a Complex - Valued PRNN", in Proceedings ofthe IEEE Workshop on Neural Networks for Signal Processing, NNSP 2003, September 17 - 19, Toulouse, France, pp.779 - 788, 2003.
  58. T. M. Rutkowski, M. Yokoo, K. Yagi, Y. Kameda, M. Minoh, and D. P. Mandic, "Active Speakers' Position, Identificationand Tracking in Noisy Environments", in Proceedings of IWAENC, Kyoto, Japan, pp. 283-286, 2003.
  59. Su Lee Goh and D. P.Mandic, "A Data - Reusing Gradient Descent Algorithm for Complex - Valued Recurrent NeuralNetworks", Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems (KES 2003), Oxford,September 2003, V. Palade, R. J. Howlett and Lakhmi Jain, Eds., Vol. II, pp.340-350, 2003.
  60. M. Jafari, D. P. Mandic, and J. A. Chambers, "A Fast Converging Cyclostationary Natural Gradient Algorithm", Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems (KES 2003), Oxford, September2003, V. Palade, R. J. Howlett and Lakhmi Jain, Eds., Vol. I, pp.1343-1349, Springer - Verlag, 2003.
  61. T. Gautama, D. P. Mandic, and M. M. Van Hulle, "Complex Surrogate Data", Proceedings of the Knowledge-BasedIntelligent Information and Engineering Systems (KES 2003), Oxford, September 2003, V. Palade, R. J. Howlett and Lakhmi Jain, Eds., Springer - Verlag, Vol. I, pp.1364-1371, 2003.3
  62. T. Dahl, D. P. Mandic and A. G. Constantinides, "Blind MIMO Channel Identification Using Geometric Features", accepted for GLOBECOM 2003, June 2003.
  63. G. C. Cawley, N. L. C. Talbot, R. J. Foxall, S. R. Dorling, and D. P. Mandic, "Unbiased estimation of conditionalvariance in heteroscedastic kernel ridge regression", submitted to the European Symposium on Artificial Neural Networks (ESANN - 2003), Bruges, Belgium, 2003.
  64. D. P. Mandic and A. Cichocki, "An Online Algorithm for Blind Extraction of Sources with Different Dynamical Structures", Proceedings of the 4th International Symposium on Independent Component Analysis and Blind Signal Separation (ICA 2003), April 2003, Nara, Japan, pp. 645 - 650, 2003.
  65. T. Gautama, D. P. Mandic and M. M. Van Hulle, "Differential Entropy for Determining the Optimal Embedding Dimension", Proceedings of the International Conference on Acoustics, Speech and Signal Processing, ICASSP 2003,Hong Kong, Vol. VI, pp. 29 - 32, 2003.
  66. C. G. Boukis, D. P. Mandic and A. G. Constantinides, "A Gradient Adaptive Step Size Algorithm for IIR Filters", Proceedings of the International Conference on Acoustics, Speech and Signal Processing, ICASSP 2003, Hong Kong,Vol. VI, pp. 85 - 88, 2003.
  67. A. I. Hanna, I. Yates, and D. P. Mandic, "An Adaptive Error Adaptive Normalised Algorithm for Complex Valued FIRFilters", Proceedings of the International Conference on Acoustics, Speech and Signal Processing, ICASSP 2003, HongKong, Vol. II, pp. 705 - 708, 2003.
  68. D. P. Mandic, E. V. Papoulis, and C. G. Boukis, "A Normalised Mixed Norm Adaptive Filtering Algorithm Robust Under Impulsive Noise Interference", Proceedings of the International Conference on Acoustics, Speech and Signal Processing, ICASSP 2003, Hong Kong, Vol. VI, pp. 333 - 336, 2003.
  69. A. S. Palmer, M. Razaz, and D. P. Mandic, "Adaptive Nonlinear Feedback Methods for the Solution of Image Restoration Problems", in Proceedings of the 4th International Conference on Recent Advances in Soft Computing, RASC2002,Nottingham, UK, 12 - 13 December, pp. 53 - 54, full paper on a CD ROM, 2002.
  70. K. Pauwels, T. Gautama, D. P. Mandic, and M. M. Van Hulle, "Towards Mode Detection", in Proceedings of the 4thInternational Conference on Recent Advances in Soft Computing, RASC2002, Nottingham, UK, 12 - 13 December, pp.77 - 78, full paper on a CD ROM, 2002.
  71. I. R. Radojicic, D. P. Mandic and D. Vulic, "Searching for a simple ventricular arrhythmia detector", in Proceedings ofthe 2nd European Medical & Biological Engineering Conference EMBEC '02, Vienna (Austria) December 04-08, 2002,Vol. 3, pp. 366 - 367, 2002.
  72. A. Palmer, M. Razaz, and D. P. Mandic, "Spatially Adaptive Image Restoration by Neural Network Filtering", inProceedings of the VII Brazilian Symposium on Neural Networks, Porto de Galinhas, Recife, Brazil, pp. 184 - 189,2002.
  73. B. P. Milner, D. P. Mandic and D. Kolonic, "Deriving the Optimal Payload Size for Packet - Based Communication Overa Binary Symmetrical Channel", accepted for the Second Conference on Mathematics in Communications, LancasterUniversity, 16 - 18 December 2002, October 2002.
  74. S. L. Goh, D. P. Mandic, and M. M. Bozic, "A Nonlinear Neural Adaptive Filter with a Trainable Activation Function",in Proceedings of the Sixth IEEE Seminar on Neural Network Applications in Electrical Engineering, NEUREL 2002, pp. 7 - 10, 2002.
  75. A. I. Hanna, I. R. Krcmar, and D. P. Mandic, "Perlustration of Error Surfaces for Linear and Linear Stochastic Gradient Descent Algorithms", in Proceedings of the Sixth IEEE Seminar on Neural Network Applications in Electrical Engineering, NEUREL 2002, pp. 11 - 16, 2002.
  76. C. Boukis, D. P. Mandic, and A. G. Constantinides, "A Hierarchical Feedforward Adaptive Filter for System Identification", in Proceedings of the IEEE Workshop on Neural Networks for Signal Processing, NNSP 2002, September 4 - 6,Martigny, Switzerland, pp. 269 - 278, 2002.
  77. W. C. Siaw, S. L. Goh, A. I. Hanna, and D. P. Mandic, "Fully Adaptive Neural Nonlinear FIR Filters", in Proceedings of the IEEE Workshop on Neural Networks for Signal Processing, NNSP 2002, September 4 - 6, Martigny, Switzerland, pp. 279 -288, 2002.
  78. R. J. Foxall, G. C. Cawley, S. R. Dorling, and D. P. Mandic, "Error Functions for Prediction of Episodes of Poor AirQuality", in Proceedings of the International Conference on Artificial Neural Networks, ICANN 2002, Madrid, Spain, August 27 - 30, 2002, pp. 1031 - 1036, 2002.
  79. C. Boukis and D. P. Mandic, "A Global Gradient Descent Algorithm for Hierarchical FIR Adaptive Filters", in Proceedings of the 14 International Conference on Digital Signal Processing DSP2002, Santorini, Greece, July 1-3, 2002, Vol. II, pp. 1285 - 1288, 2002.
  80. C. Boukis, D. P. Mandic, and A. G. Constantinides, "Insights into the Hierarchical Gradient Descent Algorithm", Proceedings of the IEE Workshop on Non-Linear and Non-Gaussian Signal Processing - N2SP, Peebles Hotel Hydro,8-9 July 2002, 2002.
  81. K. Pauwels, T. Gautama, D. P. Mandic, M. M. Van Hulle, and A. G. Constantinides, "Towards Characterisation of Nonstationary Time Series", Proceedings of the IEE Workshop on Non-Linear and Non-Gaussian Signal Processing -4N2SP, Peebles Hotel Hydro, 8-9 July 2002, 2002.
  82. I. R. Radojicic, D. P. Mandic, and D. Vulic, "Distinguishing Between Heart Rhythms Using Temporal Autocorrelations", accepted for the XLVI Conference ETRAN, May 2002.
  83. I. Radojicic, T. Gautama, and D. P. Mandic, "A Comparison of Two Novel Methods for Characterization of Heart RateVariability Series", in Proceedings of the 16th Biennial International EURASIP Conference BIOSIGNAL2002, Brno, Czech Republic, June 2002, pp. 84 - 87, 2002.
  84. D. P. Mandic, A. I. Hanna, and D. I. Kim, "A General Adaptive Normalised Nonlinear Gradient Descent Algorithm ForNonlinear Adaptive Filters", in Proceedings of International Conference on Acoustics, Speech and Signal Processing, ICASSP 2002, Vol. II, pp. 1353 - 1356, May 2002.
  85. A. I. Hanna and D. P. Mandic, "A Normalised Complex Backpropagation Algorithm", in Proceedings of International Conference on Acoustics, Speech and Signal Processing, ICASSP 2002, Vol. I, pp. 977 - 980, May 2002.
  86. D. H. Kolonic, D. P. Mandic, B. Milner and R. Harvey, "On the Derivation of the Optimal Payload Size for PacketBased Transmission Over a Binary Symmetrical Communication Channel", in Proceedings of International Conferenceon Acoustics, Speech and Signal Processing, ICASSP 2002, Vol. IV, pp. 4120 - 4123, May 2002.
  87. W. Sherliker, I. R. Krcmar, M. M. Bozic, and D. P. Mandic, "On Sensitivity for a Class of Adaptive Filters", in Proceedingsof International Conference on Acoustics, Speech and Signal Processing, ICASSP 2002, Vol. I, pp. 1061 - 1064, May 2002.
  88. R. J. Foxall, G. C. Cawley, N. L. C. Talbot, S. R. Dorling, and D. P. Mandic, "Heteroscedastic Regularised Kernel Regression for Prediction of Episodes of Poor Air Quality", in Proceedings of the 10th European Symposium on Artificial Neural Networks ESANN - 2002, 24 - 26 April 2002, Bruges, Belgium, pp. 19 - 24, 2002.
  89. I. Radojicic and D. P. Mandic, "On the Presence of Deterministic Chaos in HRV Signals", Proceedings the 28th AnnualComputers in Cardiology Congress, pp. 465 - 468, 2001.
  90. A. I. Hanna, D. P. Mandic, and M. Razaz, "A Normalised Backpropagation Algorithm for Neural Adaptive Filters", Proceedings of the XI IEEE Workshop on Neural Networks for Signal Processing (NNSP - 2001), Falmouth, MA, pp.63 - 72, 2001.
  91. Z. V. Babic and D. P. Mandic, "A Computationally Efficient Algorithm for Fast Convolution/Correlation", Proceedings of the 5th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services CTELSIKS2001, Nis Yugoslavia, Vol. 2, pp. 595 - 598, 19 - 21 September 2001.
  92. M. M. Bozic and D. P. Mandic, "A Fully Adaptive Algorithm for FFNNs", Proceedings of the IX International Conference on Control and Automation - MED '01, 2001, Proceedings on CD.
  93. I. R. Radojicic, D. P. Mandic and D. Vulic, "Searching for an optimal time-delay in the state-space reconstruction of aheart rate variability signal", Proceedings of the IX IFMBE Mediterranean Conference on Biomedical Signal Processing (MEDICON 2001), Vol. II, pp. 893 - 896, 2001.
  94. I. R. Krcmar and D. P. Mandic, "A Fully Adaptive NNGD Algorithm", in Proceedings of the International Conference on Acoustics, Speech and Signal Processing, ICASSP - 2001, Salt Lake City, Utah, May 2001, Vol. V I, pp. 3493 - 3496,2001.
  95. R. Foxall, I. R. Krcmar, S. Dorling, G. Cawley, and D. P. Mandic, "Nonlinear Modelling of Air Pollution Time Series", in Proceedings of the International Conference on Acoustics, Speech and Signal Processing, ICASSP - 2001, Salt LakeCity, Utah, May 2001, Vol. V I, pp. 3505 - 3508, 2001.
  96. D. P. Mandic, I. R. Krcmar, W. Sherliker, and G. D. Smith, "A Data - Reusing Stochastic Approximation Algorithm forNeural Adaptive Filters", in Proceedings of the International Conference on Artificial Neural Nets and Genetic Algorithms ICANNGA - 2001, pp. 422 - 425, 2001.
  97. R. Foxall, I. Krcmar, G. Cawley, S. Dorling, and D. P. Mandic, "On Nonlinear Processing of Air Pollution Data", in Proceedings of the International Conference on Artificial Neural Nets and Genetic Algorithms ICANNGA - 2001, pp.477 - 480, 2001.
  98. I. R. Krcmar, D. P. Mandic, and R. J. Foxall, "On Predictability of Atmospheric Pollution Time Series", in Proceedings of the International Conference on Artificial Neural Nets and Genetic Algorithms ICANNGA - 2001, pp 481 - 484, 2001.
  99. G. C. Cawley, S. Dorling, R. J. Foxall, and D. P. Mandic, "Estimating the Costs Associated with Worthwhile Predictionsof Poor Air Quality", in Procedings of the International Conference on Artificial Neural Nets and Genetic Algorithms ICANNGA - 2001, 485 - 488, 2001.
  100. D. P. Mandic, "The Use of Mobius Transformations in Neural Networks and Signal Processing", Proceedings of the XIEEE Workshop Neural Networks for Signal Processing (NNSP2000), Sidney, AU, pp. 185-194, 2000.
  101. D. P. Mandic, "On Fixed Points of a General Neural Network via Mobius Transformations", in Proceedings of the FifthInternational Conference on Mathematics in Signal Processing, December 2000, Proceedings on CD.
  102. M. Fisher, D. P. Mandic, and R. Harvey, "Visualising Error Performance Surfaces for Adaptive Filters using Morphological Scale Trees", in Proceedings of the Fifth International Conference on Mathematics in Signal Processing, December 2000,Procedings on CD.
  103. Z. Babic, S. Kalaba, and D. P. Mandic, "Polynomial Modelling in Diagnostics and Perceptual Adjustment Systems Design", Proceedings of the 8th International Conference on Software, Telecommunications and Computer Networks5(SoftCOM-2000), Vol. I, pp. 189 - 198, 2000.
  104. D. P. Mandic, R. Harvey, and D. H. Kolonic, "On the Choice of Tactile Code", in Proceedings of IEEE Conference onMultimedia and Expo, ICME2000, New York, USA, Vol. I, pp. 567 - 570, 2000.
  105. D. P. Mandic and I. R. Krcmar, "On Training with Slope Adaptation for Feedforward NNs", Proceedings of the Fifth IEEE Seminar on Neural Network Applications in Electrical Engineering (NEUREL-2000), pp. 42 - 45, 2000.
  106. I. Krcmar, M. M. Bozic, and D. P. Mandic, "Global Asymptotic Stability of RNNs with Bipolar Activation Functions", Proceedings of the Fifth IEEE Seminar on Neural Network Applications in Electrical Engineering (NEUREL-2000), pp.33 - 36, 2000.
  107. D. H. Kolonic, D. P. Mandic, and M. Lukic, "Applications of the Bayes Decision Criterion in System Optimisation", Proceedings of the Fifth Balkans Conference on Operations Research, 2000.
  108. J. A. Chambers,W. Sherliker, and D. P. Mandic, "A Normalized Gradient Algorithm for an Adaptive Recurrent Perceptron",in Proceedings of the International Conference on Acoustics, Speech and Signal Processing, ICASSP - 2000, Istanbul,Turkey, Vol. I, pp. 396 - 399, 2000.
  109. R. Harvey, D. P. Mandic, and D. H. Kolonic, "Some Potential Pitfalls with s to z - Plane Mappings", in Proceedings ofthe International Conference on Acoustics, Speech and Signal Processing, ICASSP - 2000, Istanbul, Turkey, Vol. VI, pp.3530 - 3533, 2000.
  110. D. P. Mandic, J. A. Chambers, and M. M. Bozic, "On Global Asymptotic Stability of Fully Connected Recurrent NeuralNetworks", in Proceedings of the International Conference on Acoustics, Speech and Signal Processing, ICASSP - 2000,Istanbul, Turkey, Vol. VI, pp. 3406 - 3409, 2000.
  111. M. Fisher, D. P. Mandic, J. A. Bangham, and R. Harvey, "Visualising Error Surfaces for Adaptive Filters and Other Purposes", in Proceedings of the International Conference on Acoustics, Speech and Signal Processing, ICASSP - 2000,Istanbul, Turkey, Vol. VI, pp. 3522 - 3525, 2000.
  112. D. P. Mandic and J. A. Chambers, "Global Asymptotic Stability of Nonlinear Relaxation Equations Realised Through Recurrent Perceptron", in Proceedings of the International Conference on Acoustics, Speech and Signal Processing, (ICASSP - 99), Phoenix, USA, Vol. 2, pp. 1037-1040, 1999.
  113. D. P. Mandic and J. A. Chambers, "A Nonlinear Adaptive Predictor Realised via Recurrent Neural Networks with Annealing", in the Digest of the IEE Colloquium - Statistical Signal Processing, Savoy Place, London, UK, pp. 2/1-2/6,January 1999.
  114. D. P. Mandic and J. A. Chambers, "From An A Priori RNN to An A Posteriori PRNN Nonlinear Predictor", in Proceedings of the VIII IEEE Workshop Neural Networks for Signal Processing (NNSP98), Cambridge, UK, pp. 174-183, 1998.
  115. D. P. Mandic and J. A. Chambers, "Advanced PRNN Based Nonlinear Prediction/System Identification", in the Digest of the IEE Colloquium Non-linear Signal and Image Processing, Savoy Place, London, UK, pp. 11/1-11/6, May 1998.

Book articles ↑

  1. D. Looney and D. P. Mandic, "Empirical Mode Decomposition for Simultaneous Image Enhancement and Fusion", in T. Stathaki, editor Image Fusion: Algorithms and Applications, pp. tba, Elsevier 2008.
  2. B. Jelfs, P. Vayanos, S. L. Goh and D. P. Mandic, "Collaborative Adaptive Filters for Online Knowledge Extraction and Information Fusion", in D. P. Mandic et al., editors Signal Processing Techniques for Knowledge Extraction and Information Fusion, pp. 1-20, Springer 2008.
  3. D. P. Mandic, G. Souretis, W. Y. Leong, D. Looney, M. M. Van Hulle, and T. Tanaka, "Complex Empirical Mode Decomposition for Multichannel Information Fusion", in D. P. Mandic et al., editors Signal Processing Techniques for Knowledge Extraction and Information Fusion, pp. 243-260, Springer 2008.
  4. T. Rutkowski, A. Cichocki, and D. P. Mandic, "EMDsonic - An Empirical Mode Decomposition Based Brain Signal Activity Sonification Approach", in D. P. Mandic et al., editors Signal Processing Techniques for Knowledge Extraction and Information Fusion, pp. 261-275, Springer 2008.
  5. P. Vayanos, M. Chen, B. Jelfs, and D. P. Mandic, "Exploiting Nonlinearity in Signal Processing: Qualitative Assessment of Adaptive Filtering Algorithms and Signal Modality Characterisation", in M. Chetouani et al., editors Nonlinear and Nonconventional Signal Processing, pp. 155-169, Lecture Notes in Computer Science, Springer 2008.
  6. T. Rutkowski and D. P. Mandic, "Modelling the Communication Atmosphere:- A Human Centered Multimedia Approach to Evaluate Communicative Situations", in , in T. Huang, A. Nijholt, M. Pantic, and A. Plentland, editors, Human Computing, Lecture Notes in Artifcial Intelligence, pp. 155-169, Springer 2007.
  7. T. Rutkowski and D. P. Mandic, "Modelling Communication Interactivity", in T.Nishida editor, Engineering Approaches to Conversational Informatics, pp. 353-370, Wiley 2007.
  8. K. Pauwels, T. Gautama, D. P. Mandic, and M. M. Van Hulle, "Towards Model - Independent Mode Detection and Characterisationof Very Long Biomedical Time Series", in A. Lofti, Ed., in "Applications and Science in Soft Computing", Springer Verlag, pp. 213-218, 2004.
  9. D. P. Mandic, S. L. Goh, and A. I. Hanna, "Data Reusing Algorithms for Complex Valued Adaptive Filters", in A.Hirose, Ed., Complex Valued Neural Networks, World Scientific, Singapore, pp. 131-153, 2003.
  10. D. P. Mandic, J. Baltersee, and J. A. Chambers, "Non-linear Adaptive Prediction of Speech with a Pipelined Recurrent Neural Network and Advanced Learning Algorithms", in A. Prochazka, J. Uhlir, P. W. Rayner, and N. G. Kingsbury, Eds., Signal Analysis and Prediction, Birkhauser, Boston, 1998.

Other ↑

  1. T. Gautama, M. M. Van Hulle and D. P. Mandic, "On the Characterisation of the Deterministic/Stochastic and Linear/Nonlinear Nature of Time Series", Technical Report DPM-04-05, Imperial College London, 2004
  2. A. G. Constantinides and D. P. Mandic, "Contours, Corners and Cats", Invited talk inthe 4th Eurasip Conference, Zagreb, Croatia, 2-4 July, 2003.
  3. D. H. Kolonic and D. P. Mandic, "A Note on the Bayes and Maximum Likelihood Decision Criteria", Technical Report SYS-C00-01, University of East Anglia, School of Information Systems, 2000.
  4. D. P. Mandic and D. H. Kolonic, "Some Aspects of Braille Based Tactile Communica-tion", Technical Report SYS-C00-04, University of East Anglia, School of Information Systems, 2000.
  5. D. P. Mandic, "Evolving Recurrent Neural Networks for Time Series Prediction", Technical Report SYS-C00-05, University of East Anglia, School of Information Systems,2000.
  6. D. P. Mandic, "On the Nonlinear Activation Function of a Neuron", Technical ReportSYS-C00-06, University of East Anglia, School of Information Systems, 2000.