Neural network and method of using same
First Claim
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1. A method of operating a neural network having a plurality of hidden layer neurons, said method comprising the following steps:
- (a) distributing network inputs to said hidden layer neurons without performing a non-linear transformation on said network inputs;
(b) said hidden layer neurons applying a plurality of gating functions to said neural network inputs to produce a plurality of gated inputs;
(c) said hidden layer neurons multiplying said gated inputs together to generate a plurality of products;
(d) said hidden layer neurons multiplying said plurality of products by a weight value to generate a plurality of non-binary neuron outputs without using a non-linear sigmoid function; and
(e) summing ones of said non-binary neuron outputs of a first group of said plurality of hidden layer neurons to generate a first network output; and
(f) summing ones of said non-binary neuron outputs of a second group of said plurality of hidden layer neurons to generate a second network output.
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Abstract
A method of operating a neural network and a neural network, which is implemented either in hardware or software, is constructed of neurons or neuron circuits each having only one significant processing element in the form of a multiplier. The neural network utilizes a training algorithm which does not require repetitive training and which yields a global minimum to each given set of input vectors.
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Citations
14 Claims
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1. A method of operating a neural network having a plurality of hidden layer neurons, said method comprising the following steps:
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(a) distributing network inputs to said hidden layer neurons without performing a non-linear transformation on said network inputs; (b) said hidden layer neurons applying a plurality of gating functions to said neural network inputs to produce a plurality of gated inputs; (c) said hidden layer neurons multiplying said gated inputs together to generate a plurality of products; (d) said hidden layer neurons multiplying said plurality of products by a weight value to generate a plurality of non-binary neuron outputs without using a non-linear sigmoid function; and (e) summing ones of said non-binary neuron outputs of a first group of said plurality of hidden layer neurons to generate a first network output; and (f) summing ones of said non-binary neuron outputs of a second group of said plurality of hidden layer neurons to generate a second network output. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. An apparatus, comprising:
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a plurality of circuits for applying a plurality of gating functions to an input signal to produce a plurality of gated inputs, wherein at least one of the gated inputs represents the input signal raised to a power other than zero or one, the circuits multiplying the gated inputs together to generate a plurality of products and multiplying the products by a plurality of weight values to generate a plurality of non-binary output signals, wherein the circuits generate the non-binary output signals without using a non-linear sigmoid function; and a first summing circuit for summing ones of the non-binary neuron outputs from a first group of the circuits to generate a first output signal; and a second summing circuit for summing ones of the non-binary neuron outputs from a second group of the circuits to generate a second output signal.
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Specification