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368 Chapter 7 FIR FILTER DESIGN
>> N = N+1
N = 43
>> h = firpm(N,f,m,weights); [db,mag,pha,grd,w] = freqz_m(h,[1]);
>> Asd = -max(db(wsi:1:501))
Asd = 48.2131
>> N = N+1
N = 44
>> h = firpm(N,f,m,weights); [db,mag,pha,grd,w] = freqz_m(h,[1]);
>> Asd = -max(db(wsi:1:501))
Asd = 48.8689
>> N = N+1
N = 45
>> h = firpm(N,f,m,weights); [db,mag,pha,grd,w] = freqz_m(h,[1]);
>> Asd = -max(db(wsi:1:501))
Asd = 49.8241
>> N = N+1
N = 46
>> h = firpm(N,f,m,weights); [db,mag,pha,grd,w] = freqz_m(h,[1]);
>> Asd = -max(db(wsi:1:501))
Asd = 51.0857
>> M = N+1
M = 47
Note that we stopped this iterative procedure when the computed stopband
attenuation exceeded the given stopband attenuation A s, and the optimal value
of M was found to be 47. This value is considerably lower than the window
design techniques (M =61for a Kaiser window) or the frequency sampling
technique (M = 60). In Figure 7.35 we show the time- and the frequencydomain
plots of the designed filter along with the error function in both the
passband and the stopband to illustrate the equiripple behavior.
□ EXAMPLE 7.24 Let us design the bandpass filter described in Example 7.10 using the Parks-
McClellan algorithm. The design parameters are:
ω 1s =0.2π
; R p =1dB
ω 1p =0.35π
ω 2p =0.65π
; A s =60db
ω 2s =0.8π
Solution
The following MATLAB script shows how to design this filter.
>> ws1 = 0.2*pi; wp1 = 0.35*pi; wp2 = 0.65*pi; ws2 = 0.8*pi;
>> Rp = 1.0; As = 60;
>> [delta1,delta2] = db2delta(Rp,As);
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