individual sinc demo

demo/demo_sinc.m

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+% Demo: learn a sinc. Run one algorithm using its default parameters.
+%
+% This file is part of the Kernel Adaptive Filtering Toolbox for Matlab.
+% http://sourceforge.net/projects/kafbox/
+
+close all
+clear all
+rs = 1; randn('state',rs); rand('state',rs); %#ok<RAND>
+
+%% PARAMETERS
+
+N = 1000; % number of training data
+N_test = 500; % number of test data
+SNR = 20; % SNR in dB
+
+algorithm = 'aldkrls';
+
+%% GENERATE DATA
+x = randn(N,1);
+x_test = linspace(min(x),max(x),N_test)';
+y_ref = sinc([x;x_test]);
+y = y_ref + sqrt(10^(-SNR/10)*var(y_ref))*randn(N+N_test,1);
+y_test = y_ref(N+1:N+N_test);
+
+%% RUN ALGORITHM
+fprintf('%s: ',upper(algorithm));
+Y_est = zeros(N_test,1);
+kaf = feval(algorithm);
+t1 = tic;
+for i=1:N,
+    if ~mod(i,floor(N/10)), fprintf('.'); end
+    kaf = kaf.train(x(i),y(i));
+end
+y_est = kaf.evaluate(x_test);
+MSE = mean((y_test-y_est).^2);
+
+%% OUTPUT
+
+fprintf(' %.2fs. MSE=%3.2fdB\n',toc(t1),10*log10(MSE))
+
+figure; hold all
+plot(x,y(1:N),'.')
+
+plot(x_test,y_est,'LineWidth',2)
+legend({'data',strrep(upper(algorithm),'_','-')})
+axis([min(x)-0.5 max(x)+0.5 min(y)-0.5 max(y)+0.5]);