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 Wireless neural network and a wireless neural processing element

Details
Inventors: Murphy, John H.;
Assignee: Westinghouse Electric Corp. (Pittsburgh, PA)
Primary Examiner: MacDonald; Allen R.
Assistant Examiner:
Attorney, Agent or Firm: Lynch; M. P.

A neural network is disclosed in which communication between processing elements occurs by radio waves in a waveguide. Radio wave communication using common carrier signals by transceivers in a waveguide allows processing elements to communicate wirelessly and simultaneously. Each processing element includes a radio frequency transceiver and an accompanying antenna which performs the neuron summing operation because input signals simultaneously received from plural processing elements by the antenna add. The weights on each input are provided by different spatial relationships between the transmitting processing elements and the receiving processing element which causes signal strength loses through the waveguide to be different. Each receiving processing element performs a neural threshold or sigmoid operation on the summed signal received from the transceiver and then a strength (amplitude scaling) can be applied to the output before the processing element transmits that output to the other processing elements in the system. Processing elements are grouped, allowing one group to transmit while the other group is receiving. Wafer scale electronics including transceivers and analog processing elements are combined with a comparably sized waveguide to produce a compact device.

DETAILED DESCRIPTION It is an object of the present invention to provide a communication apparatus that allows a large number of neural processing elements to communicate simultaneously with each other.
It is another object of the present invention to provide a network in which a higher density of processing elements is achievable because physical linkages, which occupy integrated circuit space, are eliminated and because a substantial portion of the neural computation is performed electromagnetically again reducing the space required.
It is an additional object to reduce the production cost and increase the reliability of a neural network by eliminating a substantial number of hardwired connections.
It is also an object of the present invention to provide a connection method in which conventional teaching algorithms can be used.
It is a further object of the present invention to provide a network which communicates between processing elements via radio waves in a waveguide.
It is an additional object of the present invention to allow fully connected networks of large numbers of neurons to be practically and economically implemented.
The above objects can be attained by a system in which communication between neural processing elements occurs by radio waves in a waveguide.
Each processing element includes a radio frequency transceiver and antenna where a receiving processing element performs the conventional neural processing element summing operation because input signals simultaneously received from plural processing elements by an antenna add and the weights on each input are provided by the geometry and properties of the waveguide between the transmitting processing elements and the receiving processing element.
Each receiving processing element performs a threshold operation or non-linear transformation and then a weight or amplitude scaling can be applied to the output before the processing element transmits that output to the other processing elements in the system.
These together with other objects and advantages which will be subsequently apparent, reside in the details of construction and operation as more fully hereinafter described and claimed, reference being had to the accompanying drawings forming a part hereof, wherein like numerals refer to like parts throughout



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