Abstract
A novel multilayer feedforward neural network model using the adaptive lookup table units as the neuron synapses and its learning algorithm are proposed. An improvement of the network model in performance over the conventional backpropagation (BP) network is the global convergence property. Also, the network shows much faster convergence speed as well as more time-saving iteration during the weight updating than the conventional feedforward network. >
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