getSpectralMaskStatus

Add a spectral mask to an existing dsp.SpectrumAnalyzer System object scope and get its status using the getSpectralMaskStatus function.

sine = dsp.SineWave('Frequency',[98 100],'SampleRate',1000);
sine.SamplesPerFrame = 1024;
scope = dsp.SpectrumAnalyzer('SampleRate',sine.SampleRate, ...
       'PlotAsTwoSidedSpectrum',false,'ShowLegend',true,...
       'YLimits',[-60 40]);
hide(scope);

scope.SpectralMask.EnabledMasks = 'Upper and lower';
upperMask = [0 -10; 90 -10; 90 30; 110 30; 110 -10; 500 -10];
set(scope.SpectralMask,'UpperMask',upperMask,'LowerMask',-55);

for i=1:100
    scope(sine() + 0.05*randn(1024,2));
end

res = getSpectralMaskStatus(scope)

res = 

  struct with fields:

    IsCurrentlyPassing: 0
        NumPassedTests: 1
         NumTotalTests: 33
           SuccessRate: 3.0303
          FailingMasks: 'Upper and lower'
       FailingChannels: [1 2]
        SimulationTime: 101.3760

You can see the same information in the Spectral Mask panel of the Spectrum Analyzer.

show(scope);
release(scope);

Add a spectral mask to an existing spectrumAnalyzer object scope and get its status using the getSpectralMaskStatus function.

The spectrumAnalyzer object uses the filter bank method as the default spectral estimation method. Compared to the Welch method, the filter bank method has a lower noise floor, better frequency resolution, and also requires fewer samples per update.

To retain the same default behavior as the dsp.SpectrumAnalyzer System object, change the Method property to "welch" and the AveragingMethod property to "exponential". If needed, adjust the value of the forgetting factor.

sine = dsp.SineWave(Frequency=[98 100],SampleRate=1000);
sine.SamplesPerFrame = 1024;   
scope = spectrumAnalyzer(SampleRate=sine.SampleRate,...
       PlotAsTwoSidedSpectrum=false,ShowLegend=true,...
       Method="welch",AveragingMethod="exponential",...
       ForgettingFactor=0.4,YLimits=[-60 40]);
hide(scope);
scope.SpectralMask.EnabledMasks = "upper-and-lower";
upperMask = [0 -10; 90 -10; 90 30; 110 30; 110 -10; 500 -10];
set(scope.SpectralMask,UpperMask=upperMask,LowerMask=-55);
for i=1:100       
    scope(sine() + 0.05*randn(1024,2));
end
res = getSpectralMaskStatus(scope)

res = struct with fields:
    IsCurrentlyPassing: 1
        NumPassedTests: 32
         NumTotalTests: 33
           SuccessRate: 96.9697
          FailingMasks: ''
       FailingChannels: [1×0 double]
        SimulationTime: 102.3990

You can see the same information in the Spectral Mask tab on the Spectrum Analyzer toolstrip.

show(scope);
release(scope);