Genetic algorithms and their applications

Abstract

odeling is a common but important technique for signal characterization. With the advent of computational power, many problems that were considered to be unsolvable in the past can now be tackled with ease. Successful applications in this area include the time-delay estimation modeled as a finite impulse response (FIR) filter [ 11 for sonar and radar systems; speech coding using linear predictive coding [2-41; wavelets for speech and image coding and recognition [5-81; fractals for image compression and recognition systems [9-111; and delayed-X filter [12-141 for active noise control [ 151, to name but a few.An efficient model for signal processing is not easy to come by and is often obtained with the aid of an optimization scheme. The accuracy of the model is generally governed by a set of variables or parameters that is optimized in the 22 IEEE SIGNAL PROCESSING MAGAZINE

Genetic algorithm based correlations for heat transfer calculation on concave surfaces

“…Porto et al [21] used evolutionary programming to train neural networks to distinguish between sonar reflections from different types of objects: man-made metal spheres, seamounts, fish and plant life, and random background noise. Tang et al [22] survey the uses of genetic algorithms in acoustics and signal processing.…”

A Genetic Algorithm for Efficient Video Content Representation

“…Thus, the average objective value of the population is mapped into the average fitness [17]. After fitness values,…”

A Quantum Behaved Gravitational Search Algorithm

“…Similarly to genetic algorithms [2], GSA is an optimization tool based on a population, where each member is seen as a mass, and each mass is a potential solution to the problem under analysis. It has already been shown that GSA is comparable in performance with other evolutionary algorithms such as particle swarm optimization (PSO) [3] and Genetic Algorithm (GA) [2].…”