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Index: Spectral Audio Signal Processing
Spectral Audio Signal Processing
Optimal FIR Digital Filter Design
Matlab Support for Least-Squares FIR Filter Design
More General Real FIR Filters
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Index of terms in JOS Website
Index: Spectral Audio Signal Processing
Spectral Audio Signal Processing
Optimal FIR Digital Filter Design
Matlab Support for Least-Squares FIR Filter Design
We return now to the
-norm minimization problem of §4.10.2:
(5.46)
and discuss its formulation as a linear programming problem,
very similar to the optimal window formulations in §3.13.
We can rewrite (4.46) as
(5.47)
where
denotes the
th row of the matrix
.
This can be expressed as
s.t.
(5.48)
Introducing a new variable
(5.49)
then we can write
(5.50)
and our optimization problem can be written in more standard form:
s.t.
(5.51)
Thus, we are minimizing a linear objective, subject to a set of
linear inequality constraints.
This is known as a linear programming problem, as discussed
previously in §3.13.1, and it may be solved using the matlablinprog function. As in the case of optimal window design,
linprog is not normally as efficient as the Remez multiple
exchange algorithm (firpm), but it is more general, allowing
for linear equality and inequality constraints to be imposed.