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# An Artificial Neural Network for Spatio-Temporal Bipolar Patterns: Application to Phoneme Classification

@inproceedings{Atlas1987AnAN, title={An Artificial Neural Network for Spatio-Temporal Bipolar Patterns: Application to Phoneme Classification}, author={Les E. Atlas and Toshiteru Homma and Robert J. Marks}, booktitle={NIPS}, year={1987} }

- Published 1987 in NIPS

An artificial neural network is developed to recognize spatio-temporal bipolar patterns associatively. The function of a formal neuron is generalized by replacing multiplication with convolution, weights with transfer functions, and thresholding with nonlinear transform following adaptation. The Hebbian learning rule and the delta learning rule are generalized accordingly, resulting in the learning of weights and delays. The neural network which was first developed for spatial patterns was thus… CONTINUE READING

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