The design of optimal digital filters directly from analog prototypes


Generally analog prototype filters are not candidates for the design of optimum digital filters because the processing requirements to convert from the analog prototype filter to the target digital filter are excessive. However, some optimized bilinear transform algorithms introduced by Simons and Harden to solve differential equation models were found to be adaptable to the problem of designing optimal digital filters without introducing excessive processing requirements. Based on these optimized bilinear transform algorithms, a procedure is derived whereby the coefficients of an analog prototype filter are adjusted in a parameter optimization process. The convergence of this process yields the digital filter that optimizes a cost function specifically formulated to realize desired digital filter goals and specifications. It is important to note that this new class of digital filters can be FIR or HR with the latter form also guaranteed to be stable.

Publication Title

Computers in Education Journal

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