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function [features, targets] = Stochastic_SA(train_features, train_targets, params, region, plot_on) %Reduce the number of data points using the stochastic simulated annealing algorithm %Inputs:

function [bits_alloc,energy_alloc,SNR] = BitLoad(subchan_gains,total_bits,num_subc,gap,noise,M) % Bit Loading Algorithm % --------------------- % % Inputs : % subchan_gains : SubCarrier

function [bits_alloc,energy_alloc,SNR] = BitLoad(subchan_gains,total_bits,num_subc,gap,noise,M) % Bit Loading Algorithm % --------------------- % % Inputs : % subchan_gains : SubCarrier

function [features, targets] = Stochastic_SA(train_features, train_targets, params, region, plot_on) %Reduce the number of data points using the stochastic simulated annealing algorithm %Inputs:

function plottopdir(ra, n, sorp) % Plot the top n projections of FRAT if exist('n', 'var') == 0 K = [1:5]; elseif length(n) == 1 K = [1:n]; else K = n; end n = length(K); % Energy f

function f0 = find_f0(x) % FIND_F0 Find fundamental frequency % % F0 = FIND_F0(X) % % Find the fundamental frequency of signal X. % By default, FIND_F0 uses the YIN method for F0 estimation

function [features, targets] = Stochastic_SA(train_features, train_targets, params, region, plot_on) %Reduce the number of data points using the stochastic simulated annealing algorithm %Inputs:

function [features, targets] = Stochastic_SA(train_features, train_targets, params, region, plot_on) %Reduce the number of data points using the stochastic simulated annealing algorithm %Inputs:

/* ITU-T G.729 Annex C+ - Reference C code for floating point implementation of G.729 Annex C+ (integration of Annexes B, D and E)

/* Copyright (C) 2006 Massachusetts Institute of Technology % % This program is free software; you can redistribute it and/or modify % it under the terms of the GNU General Public License as publi