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Pre-Grant Publication Number: 20090132452

Artificial neuron

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Prior Art Detail

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#557US6581049: Artificial neurons including power series of weights and counts that represent prior and next association

Applies to Claims 1,9

Submitted by: Diane WillisLast updated: over 3 years ago

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Summary / Description

Summary / Description	Artificial neuron for artificial intelligence system, has multiple dendrites with power series of weights having associated counts for associated powers.

Basic Information

Type of Prior Art	Issued Patents - US

Country	United States of America

Patent/Application #	6581049

Kind Code	United States (US) - United STATES Patent - A

Patentee Name	Saffron Technology, Inc.

Relevant Pages, Columns, or Lines

URL

Filing Date	November 8, 1999

Additional Information

Notes / To Do

Notes	Prior art suggested by William Risk, IBM, submitted by Diane Willis.

Excerpt

Excerpt

An artificial neuron includes inputs and dendrites, a respective one of which is associated with a respective one of the inputs. Each dendrite includes a power series of weights, and each weight in a power series includes an associated count for the associated power. The power series of weights preferably is a base-two power series of weights, each weight in the base-two power series including an associated count that represents a bit position. The counts for the associated power preferably are statistical counts. More particularly, the dendrites preferably are sequentially ordered, and the power series of weights preferably includes a pair of first and second power series of weights. Each weight in the first power series includes a first count that is a function of associations of prior dendrites, and each weight of the second power series includes a second count that is a function of associations of next dendrites. More preferably, a first and second power series of weights is provided for each of multiple observation phases. In order to propagate an input signal into the artificial neuron, a trace preferably also is provided that is responsive to an input signal at the associated input. The trace preferably includes a first trace count that is a function of associations of the input signal at prior dendrites, and a second trace count that is a function of associations of the input signal at next dendrites. The first and second power series are responsive to the respective first and second trace counts. The input signal preferably is converted into the first and second trace counts, and a trace wave propagator propagates the respective first and second trace counts into the respective first and second power series of weights.

Relevance

Claims

A processing element for an artificial neuron, comprising:a first plurality of inputs;

a continuous value determining portion configured to generate a continuous value signal based on the first plurality of inputs;

a second plurality of inputs;

a responsiveness determining portion configured to generate a responsiveness signal corresponding to either a responsive state or a non-responsive state based on the second plurality of inputs; and

an output value determining portion configured to receive the continuous value signal and the responsiveness signal and generate an output signal, wherein the output signal is equal to a predetermined value when the responsiveness signal corresponds to the non-responsive state and the output signal is equal to the continuous value signal when the responsiveness signal corresponds to the responsive state.

Relevance

See the Excerpt.

Claim Chart

Some

A processing element for an artificial neuron, comprising:a first portion that receives a first input signal, the first portion having an activating state and a non-activating state;

a second portion that receives a second input signal, the second portion having an activating state and a non-activating state, wherein a first event is defined as the second input entering the activating state from the non-activating state while the first input is in the activating state, and a second event is defined as the first input entering the non-activating state from the activating state while the second input is in the activating state; and

a third portion that produces an output signal, the third portion having a first state where the magnitude of the output signal is equal to zero and a second state where the magnitude of the output signal and a second state where the magnitude of the output is based on an event time equal to the time elapsed between the first event and the second event.

Relevance

See the Excerpt.

Claim Chart

Some

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