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fircls() - Signal Processing

b = fircls(n,f,amp,up,lo) generates
a length n+1 linear phase FIR filter b.
The frequency-magnitude characteristics of this filter match those
given by vectors f and amp:f is a vector of transition frequencies
in the range from 0 to 1, where 1 corresponds to the Nyquist frequency.
The first point of f must be 0 and
the last point 1. The frequency
points must be in increasing order.amp is a vector describing the
piecewise-constant desired amplitude of the frequency response. The
length of amp is equal to the number of bands in
the response and should be equal to length(f)-1.up and lo are
vectors with the same length as amp. They define
the upper and lower bounds for the frequency response in each band.fircls always uses an even filter order for
configurations with a passband at the Nyquist frequency (that is,
highpass and bandstop filters). This is because for odd orders, the
frequency response at the Nyquist frequency is necessarily 0.
If you specify an odd-valued n, fircls increments
it by 1.fircls(n,f,amp,up,lo,'design_flag') enables
you to monitor the filter design, where 'design_flag' can
be'trace', for a textual display
of the design error at each iteration step.'plots', for a collection of plots
showing the filter's full-band magnitude response and a zoomed view
of the magnitude response in each sub-band. All plots are updated
at each iteration step. The O's on the plot are the estimated extremals
of the new iteration and the X's are the estimated extremals of the
previous iteration, where the extremals are the peaks (maximum and
minimum) of the filter ripples. Only ripples that have a corresponding
O and X are made equal.'both', for both the textual display
and plots.Note  


Normally, the lower value in the stopband will be specified
as negative. By setting lo equal to 0 in
the stopbands, a nonnegative frequency response amplitude can be obtained.
Such filters can be spectrally factored to obtain minimum phase filters.


Syntax

b = fircls(n,f,amp,up,lo)fircls(n,f,amp,up,lo,'design_flag')


Example

Constrained Least-Squares Lowpass FilterOpen This Example
Design a 150th-order lowpass filter with a normalized cutoff frequency of 
 rad/sample. Specify a maximum absolute error of 0.02 in the passband and 0.01 in the stopband. Display plots of the bands.
n = 150;
f = [0 0.4 1];
a = [1 0];
up = [1.02 0.01];
lo = [0.98 -0.01];
b = fircls(n,f,a,up,lo,'both');
  Bound Violation = 0.0788344298966  
  Bound Violation = 0.0096137744998  
  Bound Violation = 0.0005681345753  
  Bound Violation = 0.0000051519942  
  Bound Violation = 0.0000000348656  
  Bound Violation = 0.0000000006231  

The Bound Violations denote the iterations of the procedure as the design converges. Display the magnitude response of the filter.fvtool(b)


Output / Return Value


Limitations


Alternatives / See Also


Reference