International Business Machines Corporation

Jean-Yves Boulet

Pascal R Tannhof

Guy Paillet

Andre R Steimle

Didier R Louis

Catherine Godefroy

In a neural network of N neuron circuits, having an engaged neuron's calculated p bit wide distance between an input vector and a prototype vector and stored in the weight memory thereof, an aggregate search/sort circuit (517) of N engaged neurons' search/sort circuits. The aggregate search/sort circuit determines the minimum distance among the calculated distances. Each search/sort circuit (502-1) has p elementary search/sort units connected in series to form a column, such that the aggregate circuit is a matrix of elementary search/sort units. The distance bit signals of the same bit rank are applied to search/sort units in each row. A feedback signal is generated by ORing in an OR gate (12.1) all local search/sort output signals from the elementary search/sort units of the same row. The search process is based on identifying zeroes in the distance bit signals, from the MSB's to the LSB's. As a zero is found in a row, all the columns with a one in that row are excluded from the subsequent row search. The search process continues until only one distance, the minimum distance, remains and is available at the output of the OR circuit. The above described search/sort circuit may further include a latch allowing the aggregate circuit to sort remaining distances in increasing order.

Circuit for searching/sorting data in neural networks

In a neural network comprised of a plurality of neuron circuits, an improved neuron circuit that generates local result signals, e.g. of the fire type, and a local output signal of the distance or category type. The neuron circuit which is connected to buses that transport input data (e.g. the input category) and control signals. A multi-norm distance evaluation circuit calculates the distance D between the input vector and a prototype vector stored in a R/W memory circuit. A distance compare circuit compares this distance D with either the stored prototype vector's actual influence field or the lower limit thereof to generate first and second comparison signals. An identification circuit processes the comparison signals, the input category signal, the local category signal and a feedback signal to generate local result signals that represent the neuron circuit's response to the input vector. A minimum distance determination circuit determines the minimum distance Dmin among all the calculated distances from all of the neuron circuits of the neural network and generates a local output signal of the distance type. The circuit may be used to search and sort categories. The feed-back signal is collectively generated by all the neuron circuits by ORing all the local distances/categories. A daisy chain circuit is serially connected to corresponding daisy chain circuits of two adjacent neuron circuits to chain the neurons together. The daisy chain circuit also determines the neuron circuit state as free or engaged. Finally, a context circuitry enables or inhibits neuron participation with other neuron circuits in generation of the feedback signal.

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Ballancourt Sur Essonne, France

Jean-Yves Boulet