ngd

 FUNCTION ngd() implements the operation of NGD algorithm 

 INPUT:
 x: input signal which should be scaled according to the dynamic range of nonlinearity 
 N: filter length
 mu: step-size

 OUTPUT:
 y: filter output



 Complex Valued Nonlinear Adaptive Filtering toolbox for MATLAB
 Supplementary to the book:
 
 "Complex Valued Nonlinear Adaptive Filters: Noncircularity, Widely Linear and Neural Models"
 by Danilo P. Mandic and Vanessa Su Lee Goh
 
 (c) Copyright Danilo P. Mandic 2009
 http://www.commsp.ee.ic.ac.uk/~mandic
 
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    This program is free software; you can redistribute it and/or modify
    it under the terms of the GNU General Public License as published by
    the Free Software Foundation; either version 2 of the License, or
    (at your option) any later version.
 
    This program is distributed in the hope that it will be useful,
    but WITHOUT ANY WARRANTY; without even the implied warranty of
    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
    GNU General Public License for more details.
 
    You can obtain a copy of the GNU General Public License from
    http://www.gnu.org/copyleft/gpl.html or by writing to
    Free Software Foundation, Inc.,675 Mass Ave, Cambridge, MA 02139, USA.
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 ...........................................

0001 % FUNCTION ngd() implements the operation of NGD algorithm
0002 %
0003 % INPUT:
0004 % x: input signal which should be scaled according to the dynamic range of nonlinearity
0005 % N: filter length
0006 % mu: step-size
0007 %
0008 % OUTPUT:
0009 % y: filter output
0010 %
0011 %
0012 %
0013 % Complex Valued Nonlinear Adaptive Filtering toolbox for MATLAB
0014 % Supplementary to the book:
0015 %
0016 % "Complex Valued Nonlinear Adaptive Filters: Noncircularity, Widely Linear and Neural Models"
0017 % by Danilo P. Mandic and Vanessa Su Lee Goh
0018 %
0019 % (c) Copyright Danilo P. Mandic 2009
0020 % http://www.commsp.ee.ic.ac.uk/~mandic
0021 %
0022 % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0023 %    This program is free software; you can redistribute it and/or modify
0024 %    it under the terms of the GNU General Public License as published by
0025 %    the Free Software Foundation; either version 2 of the License, or
0026 %    (at your option) any later version.
0027 %
0028 %    This program is distributed in the hope that it will be useful,
0029 %    but WITHOUT ANY WARRANTY; without even the implied warranty of
0030 %    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
0031 %    GNU General Public License for more details.
0032 %
0033 %    You can obtain a copy of the GNU General Public License from
0034 %    http://www.gnu.org/copyleft/gpl.html or by writing to
0035 %    Free Software Foundation, Inc.,675 Mass Ave, Cambridge, MA 02139, USA.
0036 % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0037 % ...........................................
0038 function y = ngd(x,N,mu)
0039 
0040 M = 1;% prediction horizon
0041 L = length(x)-M; % run length
0042 filterinput = zeros(N,L); 
0043 WNGD = zeros(N,1); % weight vector
0044 eNGD = zeros(1,L); % error
0045 filteroutput = zeros(1,L); 
0046 output = zeros(1,L);
0047 
0048 for i = 1:L
0049     for m = 1:N
0050         if (i-m+1)>0
0051             filterinput(m,i) = x(1,i-m+1);
0052         else
0053             filterinput(m,i) = 0;
0054         end
0055     end % inputing FIR
0056     filteroutput(i) = transpose(filterinput(:,i)) * WNGD;% output of FIR filter
0057     output(i) = f(filteroutput(i));
0058     eNGD(i) = x(i+M) - output(i);% error(k) of nonlinear FIR filter
0059     WNGD = WNGD + mu * eNGD(i) * conj(fderive(filteroutput(i))) * conj(filterinput(:,i));% weight update
0060 end
0061 y = output; 
0062 
0063