Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
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Since the first investigations into Genetic Algorithms (GAs), they have been proposed as control-related systems. A characteristic of GAs is their versatility when used in optimising problems. GAs have been used in the design of digital filters. In this work, a GA is used to adjust a discrete-time transfer function to get it working as a digital filter. A transfer function is forced to produce an output sequence from a given input sequence. The results of the process of the GA are the values of the parameters of a second-order transfer function. GA is checked to resolve a high pass and a low pass filter. Five parameters are adjusted from a discrete-time second-order digital filter to get the desired behaviour of the system. Some ideas about a possible translation of this system into hardware are also mentioned.