Titlebook: Artificial Neural Nets and Genetic Algorithms; Proceedings of the I Andrej Dobnikar,Nigel C. Steele,Rudolf F. Albrecht Conference proceedin

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Improving the Performance of the Hopfield Network By Using A Relaxation Rate of the Hopfield network can be improved by using a . to control the relaxation process. Analysis suggests that the relaxation process has an important impact on the quality of a solution. A . is then introduced to control the relaxation process in order to achieve solutions with better quality. Two

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esoteric

GLOSS

uncertain

anticipate

Rates of Learning in Gradient and Genetic Training of Recurrent Neural Networksradient learning of fixed points introduces the problem of the . formulated as the relative speed of evolution of the network and the adaptation process, and motivates an analogous study when genetic training is used. The existence of bounds for the rate of learning in order to guarantee convergence

minimal

chondromalacia

ATR’s Artificial Brain Project: CAM-Brain Machine (CBM) and Robot Kitten (Robokoneko) Issues based neural networks directly in FPGA electronics at electronic speeds in special hardware called a CAM-Brain Machine (CBM). The CBM updates the CA cells at a rate of 150 Billion a second, and can perform a full run of a genetic algorithm (GA) in about 1 second. 32K of these evolved circuits (modu

overreach

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