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Neural network using stochastic processing

  • US 4,972,363 A
  • Filed: 02/01/1989
  • Issued: 11/20/1990
  • Est. Priority Date: 02/01/1989
  • Status: Expired due to Fees
First Claim
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1. An apparatus for implementing a neural network having N nodes coupled to one another by interconnections having interconnect weights Tij that quantify the influence of node j on node i, the apparatus comprising:

  • a plurality of node circuits, one associated with each node;

    data processing means including means for receiving library data representing one or more library members, means for determining interconnect weights Tij from the library data and for transmitting interconnect weight data representing the interconnect weights to each node circuit, means for storing current state vector data representing a current state vector comprising N state vector elements, means for receiving input data representing a library member to be retrieved, means for performing one or more iterations until the current state vector reaches an equilibrium state, each iteration comprising transmitting the current state vector data to the node circuits, receiving updated state vector data representing an updated state vector from the node circuits, and setting the current state vector data equal to the updated state vector data, and means for initializing the iteration by setting the current state vector data equal to the input data; and

    each node circuit comprising means for receiving the interconnect weight and current state vector data, and one or more stochastic processors operating in parallel, each stochastic processor including means for multiplying data representing one interconnect weight by data representing a corresponding state vector element to produce a product signal, means for summing the product signals to thereby determine the updated state vector data, and means for transmitting the updated state vector data to the data processing means.

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