Digital Filter Design Using Evolutionary Algorithms

Evolutionary approaches have been used in a large variety of design domains, from aircraft engineering to the designs of filters. An alternative approaches to the design of digital filter have been proposed using evolutionary algorithms and the concept of Evolvable Hardware. In this paper, clustering and Pareto optimization are combined into a single evolutionary design algorithm to prevent the system from converging prematurely to a local minimum and to encourage a number of different designs that fulfill the design criteria. This approach is demonstrated in the domain of digital filter design using a polar coordinate based pole-zero representation. The results demonstrate that the evolutionary process is able to create designs that are competitive with those created using a conventional design process. They also demonstrate that each evolutionary run can produce a number of different designs with similar fitness values, but very different characteristics.