fvtool

Visualize frequency response of DSP filters

Syntax

fvtool(sysobj)

fvtool(sysobj,options)

fvtool(____,Name,Value)

Description

fvtool(sysobj) displays the magnitude response of the filter System object™.

fvtool(sysobj,options) displays the response that is specified by the options.

For example, to visualize the impulse response of an FIR filter System object, set options to 'impulse'.

Fs = 96e3; filtSpecs = fdesign.lowpass(20e3,22.05e3,1,80,Fs);
    firlp2 = design(filtSpecs,'equiripple','SystemObject',true);
fvtool(firlp2,'impulse');

fvtool(____,Name,Value) visualizes the response of the filter with each specified property set to the specified value.

For more input options, see FVTool in Signal Processing Toolbox™.

Examples

Impulse and Frequency Response of Halfband Decimation Filter

Create two lowpass halfband decimation filters for data sampled at 44.1 kHz. The design method in the first filter is set to "Equiripple" and in the second filter is set to "Kaiser".

The output data rate is 1/2 the input sample rate, or 22.05 kHz. Specify the filter order to be 52 with a transition width of 4.1 kHz.

Fs = 44.1e3; 
filterspec = "Filter order and transition width";
Order = 52;
TW = 4.1e3; 
firhalfbanddecimEqui = dsp.FIRHalfbandDecimator(...
    Specification=filterspec,...
    FilterOrder=Order,...
    TransitionWidth=TW,...
    DesignMethod="Equiripple",...
    SampleRate=Fs);
firhalfbanddecimKaiser = dsp.FIRHalfbandDecimator(...
    Specification=filterspec,...
    FilterOrder=Order,...
    TransitionWidth=TW,...
    DesignMethod="Kaiser",...
    SampleRate=Fs);

Plot the impulse response of both the filters. The zeroth-order coefficient is delayed 26 samples, which is equal to the group delay of the filter. This yields a causal halfband filter.

hfvt = fvtool(firhalfbanddecimEqui,firhalfbanddecimKaiser,...
    Analysis="impulse");
legend(hfvt,{'Equiripple','Kaiser'})

Plot the magnitude and phase response.

If the filter specifications are tight, say a very high filter order with a very narrow transition width, the filter designed using the "Kaiser" method converges more effectively.

hvftMag = fvtool(firhalfbanddecimEqui,firhalfbanddecimKaiser,...
    Analysis="Magnitude");
legend(hvftMag,{'Equiripple','Kaiser'})

hvftPhase = fvtool(firhalfbanddecimEqui,firhalfbanddecimKaiser,...
    Analysis="Phase");
legend(hvftPhase,{'Equiripple','Kaiser'})

Impulse and Frequency Response of FIR and IIR Lowpass Filters

Create a minimum-order FIR lowpass filter for data sampled at 44.1 kHz. Specify a passband frequency of 8 kHz, a stopband frequency of 12 kHz, a passband ripple of 0.1 dB, and a stopband attenuation of 80 dB.

Fs = 44.1e3; 
filtertype = 'FIR';
Fpass = 8e3;
Fstop = 12e3; 
Rp = 0.1;
Astop = 80;
FIRLPF = dsp.LowpassFilter(SampleRate=Fs,...
                             FilterType=filtertype,...
                             PassbandFrequency=Fpass,...
                             StopbandFrequency=Fstop,...
                             PassbandRipple=Rp,...
                             StopbandAttenuation=Astop);

Design a minimum-order IIR lowpass filter with the same properties as the FIR lowpass filter. Change the FilterType property of the cloned filter to IIR.

IIRLPF = clone(FIRLPF);
IIRLPF.FilterType = 'IIR';

Plot the impulse response of the FIR lowpass filter. The zeroth-order coefficient is delayed by 19 samples, which is equal to the group delay of the filter. The FIR lowpass filter is a causal FIR filter.

fvtool(FIRLPF,Analysis='impulse')

Plot the impulse response of the IIR lowpass filter.

fvtool(IIRLPF,Analysis='impulse')

Plot the magnitude and phase response of the FIR lowpass filter.

fvtool(FIRLPF,Analysis='freq')

Plot the magnitude and phase response of the IIR lowpass filter.

fvtool(IIRLPF,Analysis='freq')

Calculate the cost of implementing the FIR lowpass filter.

cost(FIRLPF)

ans = struct with fields:
                  NumCoefficients: 39
                        NumStates: 38
    MultiplicationsPerInputSample: 39
          AdditionsPerInputSample: 38

Calculate the cost of implementing the IIR lowpass filter. The IIR filter is more efficient to implement than the FIR filter.

cost(IIRLPF)

ans = struct with fields:
                  NumCoefficients: 18
                        NumStates: 14
    MultiplicationsPerInputSample: 18
          AdditionsPerInputSample: 14

Calculate the group delay of the FIR lowpass filter.

grpdelay(FIRLPF)

Calculate the group delay of the IIR lowpass filter. The FIR filter has a constant group delay (linear phase), while its IIR counterpart does not.

grpdelay(IIRLPF)

Input Arguments

sysobj — Input filter

filter System object

Input filter, specified as one of the following filter System objects:

• dsp.AllpassFilter

• dsp.AllpoleFilter

• dsp.BiquadFilter

• dsp.CICCompensationDecimator

• dsp.CICCompensationInterpolator

• dsp.CICDecimator

• dsp.CICInterpolator

• dsp.Differentiator

• dsp.FarrowRateConverter

• dsp.FilterCascade

• dsp.FIRDecimator

• dsp.FIRFilter

• dsp.FIRHalfbandDecimator

• dsp.FIRHalfbandInterpolator

• dsp.FIRInterpolator

• dsp.FIRRateConverter

• dsp.FourthOrderSectionFilter

• dsp.HighpassFilter

• dsp.IIRFilter

• dsp.IIRHalfbandDecimator

• dsp.IIRHalfbandInterpolator

• dsp.LowpassFilter

• dsp.NotchPeakFilter

• dsp.SOSFilter

• dsp.VariableBandwidthFIRFilter

• dsp.VariableBandwidthIIRFilter

Example: firFilt = dsp.FIRFilter('Numerator', fir1(130, 2000/(8000/2))); fvtool(firFilt)

options — Filter analysis options

'magnitude' (default) | 'phase' | 'freq' | 'grpdelay' | 'phasedelay' | 'impulse' | 'step' | 'polezero' | 'coefficients' | 'info' | 'magestimate' | 'noisepower'

Filter analysis options, specified as one of the following:

• 'magnitude' –– Magnitude response

• 'phase' –– Phase response

• 'freq' –– Frequency response

• 'grpdelay' –– Group delay

• 'phasedelay' –– Phase delay

• 'impulse' –– Impulse response

• 'step' –– Step response

• 'polezero' –– Pole zero plot

• 'coefficients' –– Coefficients vector

• 'info' –– Filter information

• 'magestimate' –– Magnitude response estimate

• 'noisepower' –– Round-off noise power spectrum

Example: fvtool(firFilt,'freq')

Name-Value Arguments

Specify optional pairs of arguments as Name1=Value1,...,NameN=ValueN, where Name is the argument name and Value is the corresponding value. Name-value arguments must appear after other arguments, but the order of the pairs does not matter.

Before R2021a, use commas to separate each name and value, and enclose Name in quotes.

Example: firFilt = dsp.FIRFilter('Numerator', fir1(130, 2000/(8000/2))); fvtool(firFilt,'Arithmetic','single')

Fs — Sampling rate

scalar

Sampling rate, specified as a scalar. This value determines the Nyquist interval [-Fs/2 Fs/2] in which the fvtool shows the frequency response of the filters in the channelizer.

Data Types: single | double

Arithmetic — Arithmetic type

'double' (default) | 'single' | 'Fixed'

Specify the arithmetic used during analysis. The analysis tool assumes a double-precision filter when the arithmetic input is not specified and the filter System object is unlocked. The 'Arithmetic' property set to 'Fixed' applies only to filter System objects with fixed-point properties.

When the 'Arithmetic' property is set to 'Fixed', the tool shows both the double-precision reference filter and the quantized version of the filter. The CoefficientsDataType property in the respective filter System object is used in creating the quantized version of the filter for all the analyses options except for the two below:

• 'magestimate' –– Magnitude response estimate.

• 'noisepower' –– Round-off noise power spectrum

For these two analyses options, all the fixed-point settings are used in analyzing the quantized version of the filter.

Version History

Introduced before R2006a