Unit circuit for constructing a neural network and a semiconduct

Electrical transmission or interconnection systems – Nonlinear reactor systems – Parametrons

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307464, 364807, G06G 712

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active

050049321

ABSTRACT:
A semiconductor integrated circuit for constructing a neural network model, comprising a differential amplifier which includes one output terminal and two input terminals, an excitatory synapse circuit which is connected to the noninverting input terminal of said differential amplifier, and an inhibitory synapse circuit which is connected to the inverting input terminal of said differential amplifier, wherein each of said excitatory and inhibitory synapse circuits includes a plurality of current switches, regulated current source ciruits which are equal in number to said current switches and which determine currents to flow through said current switches, and one load resistor which is connected to all of said current switches, input terminals of said each synapse circuit being constructed of terminals which turn "on" and "off" the respective current switches and to which external inputs or outputs of another neural circuit are connected, said each regulated current source circuit being constructed of a circuit whose current value can be increased or decreased by a voltage externally applied separately and as to which a value of the voltage for increasing or decreasing the current value corresponds to a synaptic weight.

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Hollis et al., "Artificial Neurons Using Analog Multipliers".

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