load_signal.m

This document is intended to serve as an introduction to Wavelet processing through a set of Matlab

function y = load_signal(name, n, options)

% load_signal - load a 1D signal
%
%   y = load_signal(name, n, options);
%
% name is a string that can be :
%   'regular' (options.alpha gives regularity)
%   'step', 'rand',
%   'gaussiannoise' (options.sigma gives width of filtering in pixels),
%   [natural signals]
%   'tiger', 'bell', 'bird'
%   [WAVELAB signals]
%   'HeaviSine', 'Bumps', 'Blocks',
%   'Doppler', 'Ramp', 'Cusp', 'Sing', 'HiSine',
%   'LoSine', 'LinChirp', 'TwoChirp', 'QuadChirp',
%   'MishMash', 'WernerSorrows' (Heisenberg),
%   'Leopold' (Kronecker), 'Piece-Regular' (Piece-Wise Smooth),
%	'Riemann','HypChirps','LinChirps', 'Chirps', 'Gabor'
%	'sineoneoverx','Cusp2','SmoothCusp','Gaussian'
%	'Piece-Polynomial' (Piece-Wise 3rd degree polynomial)

if nargin<2
    n = 1024;
end
options.null = 0;
if isfield(options, 'alpha')
    alpha = options.alpha;
else
    alpha = 2;
end

options.rep = '';
switch lower(name)
    case 'regular'
        y = gen_signal(n,alpha);
    case 'step'
        y = linspace(0,1,n)>0.5;
    case 'gaussiannoise'
        % filtered gaussian noise
        y = randn(n,1);
        if isfield(options, 'sigma')
            sigma = options.sigma; % variance in number of pixels
        else
            sigma = 20;
        end
        h = build_gaussian_filter(101,sigma/(4*n),n);
        y = perform_convolution(y,h);
    case 'rand'
        if isfield(options, 'p1')
            p1 = options.p1;
        else
            c = 10;
            p1 = 1:c; p1 = p1/sum(p1);
        end
        p1 = p1(:); c = length(p1);
        if isfield(options, 'p2')
            p2 = options.p2;
        else
            if isfield(options, 'evol')
                evol = options.evol;
            else
                evol = 0;
            end
            p2 = p1(:) + evol*(rand(c,1)-0.5);
            p2 = max(p2,0); p2 = p2/sum(p2);
        end
        y = zeros(n,1);
        for i=1:n
            a = (i-1)/(n-1);
            p = a*p1+(1-a)*p2; p = p/sum(p);
            y(i) = rand_discr(p, 1);
        end
    case 'bird'
        [y,fs] = load_sound([name '.wav'], n, options);
    case 'tiger'
        [y,fs] = load_sound([name '.au'], n, options);
    case 'bell'
        [y,fs] = load_sound([name '.wav'], n, options);
    otherwise
        y = MakeSignal(name,n);
end

y = y(:);

function y = gen_signal(n,alpha)

%   gen_signal -  generate a 1D C^\alpha signal of length n.
%
%   y = gen_signal(n,alpha);
%
%   The signal is scaled in [0,1].
%   
%   Copyright (c) 2003 Gabriel Peyr