Biologically inspired evolutionary computing tools for channel equalization

One of the classical signal processing problems is the distortion of transmitted signal by the channel before reaching the receiver. Channel Equalization is the solution for the so called problem. It has got a variety of solutions in the sense that the equalizer can be trained using different algorithms. In this paper besides the two standard adaptive algorithms LMS-Least Mean Square Algorithm and RLS-Recursive Least Square Algorithm, biologically inspired evolutionary computing tools like Standard Genetic Algorithm and Particle Swarm Optimization are adopted for channel equalization problem and the consequences are thoroughly studied under the headings convergence-rate, computational complexity ,processing time etc..