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function [Rx]=Rx_est(X,M) % [Rx]=Rx_est(X,M) % RX_EST estimates the autocorrelation of the sequence of random % variables given in X. Only Rx(0), Rx(1), ... , Rx(M) are computed.

% File: ReadMe.txt % % Basic Introduction to the Numerical Methods with MATLAB (NMM) Toolbox % % The NMM Toolbox is a collection of m-files and data to accompany the text, % "Numerical Methods w

% File: ReadMe.txt % % Basic Introduction to the Numerical Methods with MATLAB (NMM) Toolbox % % The NMM Toolbox is a collection of m-files and data to accompany the text, % "Numerical Methods w

function [M,m,df]=fftseq(m,ts,df) % [M,m,df]=fftseq(m,ts,df) % [M,m,df]=fftseq(m,ts) %FFTSEQ generates M, the FFT of the sequence m. % The sequence is zero padded to meet th

% Simulate a goal programming network % Adaptive learning rate strategy has been used % For details, see % Van Hulle, M.M. (1991). A Goal Programming Network for Linear % Programming, Bio. Cybern.,

% Simulate a goal programming network % Adaptive learning rate strategy has been used % For details, see % Van Hulle, M.M. (1991). A Goal Programming Network for Linear % Programming, Bio. Cybern.,

function [M,m,df]=fftseq(m,ts,df) % [M,m,df]=fftseq(m,ts,df) % [M,m,df]=fftseq(m,ts) %FFTSEQ Generates M, the FFT of the sequence m. % The sequence is zero padded to meet the required frequency r

function [Rx]=Rx_est(X,M) % [Rx]=Rx_est(X,M) % RX_EST Estimates the autocorrelation of the sequence of random % variables given in X. Only Rx(0), Rx(1), ... , Rx(M) are computed. % Note that

function [M,m,df]=fftseq(m,ts,df) % [M,m,df]=fftseq(m,ts,df) % [M,m,df]=fftseq(m,ts) %FFTSEQ Generates M, the FFT of the sequence m. % The sequence is zero padded to meet the required frequency r

function y = rescale(x,a,b) % rescale - rescale data in [a,b] % % y = rescale(x,a,b); % % Copyright (c) 2004 Gabriel Peyr? if nargin