Evolutionary techniques for the synthesis of 2-D FIR filters

This paper presents an objective and comparative study of evolutionary algorithms applied for designing two dimensional (2D) FIR filters. The design of 2-D FIR filters can be formulated as a non-linear optimization problem. We explore several stochastic methodologies capable of handling large spaces. We finally propose a new genetic algorithm where some concepts are introduced to optimize the trade-off between diversity and elitism in the genetic population. All these characteristics make this study a general and effective one for revealing the performance of evolutionary algorithms.

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