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BP network training algorithm is based on the error gradient descent to modify weights, which leads to the inevitable problem of a local minimum point. Some researchers have presented some amending ways and made some remarkable achievements. But combining others algorithm for adjusting the weights of BP network is few. At present, a new evolution algorithm called as differential evolution is used...
The paper introduces an approach for linking and activation potential optimization in the Pulse Coupled Neural Network (PCNN) to reduce the number of PCNN parameters. Linking potential has high influence on control of internal activity of PCNN neuron. The neuron internal activity, represented by activation potential, determines the pulse response mode of neuron in the PCNN. Because standard PCNN has...
The paper introduces an approach for threshold potential optimization in the Pulse Coupled Neural Network (PCNN) to solve the quality of generated features for image recognition tasks. Threshold potential plays very important role because it provides and controls pulse effect of PCNN. The suitable control of pulse effect can improve dimension reduction of image classification space by PCNN that is...
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