Genetic Algorithms Evolve Optimized Transforms for Signal Processing Applications

摘要

This report describes a genetic algorithm that evolves optimized sets of coefficients for signal reconstruction under lossy conditions due to quantization. The primary goal of the research described in this final report was to establish a methodology for using genetic algorithms to evolve coefficient sets describing inverse transforms and matched forward/inverse transform pairs that consistently outperform wavelets for image compression and reconstruction applications under conditions subject to quantization error.