Least Pth-Norm Optimal FIR Filter Design
This example shows how to design least Pth-norm FIR filters with the
firlpnorm function. This function uses a least-Pth unconstrained optimization algorithm to design FIR filters with arbitrary magnitude response.
The function designs optimal FIR filters in the least-Pth sense. However the filter is not constrained to have linear-phase, that is, the impulse response has no special symmetry properties.
However, the linear-phase constraint also results in filters with larger order than the more general nonlinear-phase designs. Note that in some hardware implementations, one can reduce the number of multipliers in half when implementing linear-phase filters because of the symmetry in the coefficients. For example, consider the following
N = 30; F = [0 0.3 0.45 1]; E = F; A = [1 1 0 0]; W = [1 1 10 10]; b = firlpnorm(N,F,E,A,W); fvtool(b,1);
If we zoom in, we can see that the filter has a passband peak ripple of about 0.008 and a stopband peak ripple of about 0.000832. A
firgr design with comparable specs will require a 37th order filter. This is especially significant considering that
firgr will provide the lowest order linear-phase FIR filter that meets the specifications.
dev = [0.008 0.000832]; bgr = firgr('minorder',F,A,dev); orderfirgr = length(b)-1; fprintf('Order: %d\n',orderfirgr);
h = fvtool(b,1,bgr,1); legend(h,'FIRLPNORM design','FIRGR design');
Another way to look at this is by using the
firceqrip function which also designs linear-phase equiripple filters, but whose specifications are given in a different way to
firgr (see the constrained equiripple FIR filter design example for details). If we want a linear-phase filter of 30th order that meets the passband and stopband ripple that the design from
firlpnorm achieves we need to live with a larger transition width.
bceq = firceqrip(30,(F(2)+F(3))/2,dev); h = fvtool(b,1,bceq,1); legend(h,'FIRLPNORM design','FIRCEQRIP design');
Of course it is also possible to design nonlinear-phase filters with
firgr by specifying the
minphase option. Doing so allows us to obtain an FIR filter of lower order than in the linear-phase case and still meet the required specs. However, even in this case, the result is a non-optimal nonlinear-phase filter because the filter order is larger than the minimum required for a nonlinear-phase equiripple filter to meet the specs as is evident from the following example.
bm = firgr('minorder',F,A,dev,'minphase'); orderfirgrmin = length(bm)-1; fprintf('Order: %d\n',orderfirgrmin);
h = fvtool(b,1,bm,1); legend(h,'FIRLPNORM design','FIRGR minimum-phase design');
Minimum-Phase Designs with FIRLPNORM
firlpnorm does allow for the option to constrain the zeros to lie on or inside the unit circle, resulting in a minimum-phase design. The constraint, however, results in larger passband ripple and less stopband attenuation than the unconstrained design.
bmlp = firlpnorm(30,F,E,A,W,'minphase'); h = fvtool(b,1,bmlp,1); legend(h,'FIRLPNORM design','FIRLPNORM minimum-phase design');
If we increase the order to that of the minimum-phase filter designed with
firgr we can see that we meet the specs met by both the 30th order
firlpnorm (nonminimum-phase) design and the 32nd order
firgr minimum-phase design.
bmlp = firlpnorm(orderfirgrmin,F,E,A,W,'minphase'); h = fvtool(b,1,bm,1,bmlp,1); legend(h,'FIRLPNORM design',... 'FIRGR minimum-phase design',... 'FIRLPNORM minimum-phase design');
Changing the Pth-Norm
firlpnorm allows for the specification of the Pth-norm used to optimize the filter. The Pth-norm is specified in the exact same way as in
iirlpnorm, i.e. a two element vector with Pinit and Pfinal as its elements. Pinit specifies the initial Pth-norm used by the algorithm (this aids in the convergence) and Pfinal specifies the final Pth-norm with which the filter is optimized.
For example, a least-squares design for the above specs can be obtained as follows:
N = 40; F = [0 0.4 0.45 1]; E = F; A = [0 0 1 1]; W = [1 1 10 10]; P = [2 2]; bl2 = firlpnorm(N,F,E,A,W,P); h = fvtool(bl2,1); legend(h,'FIRLPNORM design')
Comparing to FIRLS
In comparison, we design a linear-phase least-squares filter using
firls. Once again, for the same filter order, the linear-phase constraint results in less stopband attenuation and a larger passband ripple.
W = [1 20]; bls = firls(N,F,A,W); h = fvtool(bl2,1,bls,1); legend(h,'FIRLPNORM design','FIRLS design');
Equiripple designs are useful when one requires the smallest possible order to meet a set of design specifications. To meet the same specs with a least-squares design requires a higher order filter. However, the higher order does provide extra attenuation (less ripple) for a large portion of the stopband (passband). In fact least-squares design minimize the energy of the stopband. Compromises between equiripple design and least-squares design can be reached by using intermediate norms. For example we show the design of a filter with the same specs, but optimized for the following norms: 2, 4, 12, 256 (approx. infinity norm).
W = [1 1 10 10]; P4 = [2 4]; bl4 = firlpnorm(N,F,E,A,W,P4); P12 = [2 12]; bl12 = firlpnorm(N,F,E,A,W,P12); Pinf = [2 256]; blinf = firlpnorm(N,F,E,A,W,Pinf); h = fvtool(bl2,1,bl4,1,bl12,1,blinf,1); legend(h,'P = 2','P = 4','P = 12','P = 256');
In order to meet the minimum stopband attenuation of the equiripple (256-norm) case, it is necessary to increase the order of the other designs.