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  • 《DSP using MATLAB》示例 Example 10.2

    代码:

    %% ------------------------------------------------------------------------
    %%            Output Info about this m-file
    fprintf('
    ***********************************************************
    ');
    fprintf('        <DSP using MATLAB> Exameple 10.2 
    
    ');
    
    time_stamp = datestr(now, 31);
    [wkd1, wkd2] = weekday(today, 'long');
    fprintf('      Now is %20s, and it is %7s  
    
    ', time_stamp, wkd2);
    %% ------------------------------------------------------------------------
    
    clear; close all;
    
    % Example parameters
    B = 2; N = 500000; 
    xn = (2*rand(1,N)-1); 
    
    % Quantization error analysis
    [H1, H2, Q, estat] = StatModelR(xn, B, N);          % Compute histograms
    H1max = max(H1); H1min = min(H1);                   % Max and Min of H1
    H2max = max(H2); H2min = min(H2);                   % Max and Min of H2
    
    
    Hf1 = figure('units', 'inches', 'position', [1, 1, 8, 6], ...
    	'paperunits', 'inches', 'paperposition', [0, 0, 6, 4], ...
    	'NumberTitle', 'off', 'Name', 'Exameple 10.2a  B=2');
    set(gcf,'Color','white'); 
    TF = 10;
    
    subplot(2, 1, 1); 
    bar(Q, H1); axis([-0.5, 0.5, -0.001, 4/128]); grid on;
    title('Normalized error e1 and e2 Histograms, B = 2'); 
    xlabel('Normalized error e1'); ylabel('Distribution of e1 ', 'vertical', 'baseline'); 
    set(gca, 'YTickMode', 'manual', 'YTick', [0, [1:1:4]/128] );
    text(-0.45, 0.030, sprintf('SAMPLE SIZE N = %d', N));
    text(-0.45, 0.025, sprintf(' ROUNDED TO B = %d BITS', B));
    text(-0.45, 0.020, sprintf('                   MEAN  =  %.4e', estat(1)));
    text(0.10, 0.030, sprintf('MIN PROB BAR HEIGHT =  %f', H1min)) ;
    text(0.10, 0.025, sprintf('MAX PROB BAR HEIGHT = %f', H1max)) ;
    text(0.10, 0.020, sprintf('                                 SIGMA = %f', estat(2))) ;
    
    
    subplot(2, 1, 2);
    bar(Q, H2); axis([-0.5, 0.5, -0.001, 4/128]); grid on;
    %title('Normalized error e2'); 
    xlabel('Normalized error e2'); ylabel('Distribution of e2', 'vertical', 'baseline'); 
    set(gca, 'YTickMode', 'manual', 'YTick', [0, 1:1:4]/128 );
    text(-0.45, 0.030, sprintf('SAMPLE SIZE N = %d', N));
    text(-0.45, 0.025, sprintf(' ROUNDED TO B = %d BITS', B));
    text(-0.45, 0.020, sprintf('                   MEAN  =  %.4e', estat(3)));
    text(0.10, 0.030, sprintf('MIN PROB BAR HEIGHT =  %f', H2min)) ;
    text(0.10, 0.025, sprintf('MAX PROB BAR HEIGHT = %f', H2max)) ;
    text(0.10, 0.020, sprintf('                                 SIGMA = %f', estat(4))) ;
    

      这里只写了B=2 的情况,B=6的类似。

          运行结果:

        上面给出了B=2和B=6两种情况下误差分布图。从第1张图看出,即使B=2的情况,量化误差采样序列也是独立的和均匀分布的。

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  • 原文地址:https://www.cnblogs.com/ky027wh-sx/p/6928310.html
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