Digitally weighted neuron for artificial neural network

Electrical transmission or interconnection systems – Nonlinear reactor systems – Parametrons

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307201, 395 21, 395 27, 364807, H03K 1923, H03K 1908

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active

053509536

ABSTRACT:
A neuron for an artificial neural network provides digital weighting of input signals at a common portion of the neuron rather than at each synapse. The neuron is adapted for use of differential signals, and the weighting may be provided by field effect transistors of different widths, by subtracting a plurality of differential signal components from an opposite most significant component, or by subtracting one half of a differential signal component from the opposite next most significant component. The neuron may provide binary sign selection and digit selection by switching input and reference signals at each synapse.

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Mark Hollar, Simon Tam, Hernan Castro, and Ronald Benson; "An Electrically Trainable Artificial Neural Network (Etann) With 10240 `Floating Gate` Synapses"; International Joint Conference On Neural Networks; Washington, D.C.; Jun. 18-22 1989; vol. II, pp. 191-196.

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