Artificial Neural Nets and Genetic Algorithms

From the contents:Neural networks theory and applications: NNs (= neural networks) classifier on continuous data domains quantum associative memory a new class of neuron-like discrete filters to image processing modular NNs for improving generalisation properties presynaptic inhibition modelling for image processing application NN recognition system for a curvature primal sketch NN based nonlinear temporal-spatial noise rejection system relaxation rate for improving Hopfield network Oja's NN and influence of the learning gain on its dynamics Genetic algorithms theory and applications: transposition: a biological-inspired mechanism to use with GAs (= genetic algorithms) GA for decision tree induction optimising decision classifications using GAs scheduling tasks with intertask communication onto multiprocessors by GAs design of robust networks with GA effect of degenerate coding on GAs multiple traffic signal control using a GA evolving musical harmonisation niched-penalty approach for constraint handling in GAs GA with dynamic population size GA with dynamic niche clustering for multimodal function optimisationSoft computing and uncertainty: self-adaptation of evolutionary constructed decision trees by information spreading evolutionary programming of near optimal NNs