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Optimal filtering by neural networks with range extenders and/or reducers

  • US 5,649,065 A
  • Filed: 08/09/1993
  • Issued: 07/15/1997
  • Est. Priority Date: 05/28/1993
  • Status: Expired due to Fees
First Claim
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1. A method for processing an m-dimensional vector-valued measurement process to estimate an n-dimensional vector-valued signal process, said method comprising the steps of:

  • (1) selecting a recurrent neural network paradigm;

    (2) selecting an estimation error criterion;

    (3) generating training data comprising realizations of said signal process and corresponding realizations of said measurement process;

    (4) constructing a training criterion;

    (5) selecting at least one range transformer;

    (6) synthesizing said training data into a primary filter, which comprises a recurrent neural network of said recurrent neural network paradigm and said at least one range transformer;

    (7) implementing said primary filter; and

    (8) receiving one measurement vector of said measurement process at a time at at least one input terminal of the implementation of said primary filter and producing an estimate of one signal vector of said signal process at a time at at least one output terminal of the implementation of said primary filter.

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