Patent · US Expired

Neural-network dedicated processor for solving assignment problems

US5195170A · kind A · utility

42Cited by
5References
10Claims
0Family size

Assignee

Inventor

Key dates

Filing dateAug 12, 1991
Grant dateMar 16, 1993
Priority date
Expiry dateAug 12, 2011

Classification

  • Technology area (CPC G)Physics
  • CPC primaryG06N20/00
  • WIPO fieldComputer technology
  • WIPO sectorElectrical engineering

Abstract

A neural network processor for solving first-order competitive assignment problems consists of a matrix of N.times.M processing units, each of which corresponds to the pairing of a first number of elements of {R.sub.i } with a second number of elements {C.sub.j }, wherein limits of the first number are programmed in row control superneurons, and limits of the second number are programmed in column superneurons as MIN and MAX values. The cost (weight) W.sub.ij of the pairings is programmed separately into each PU. For each row and column of PUs, a dedicated constraint superneuron insures that the number of active neurons within the associated row or column fall within a specified range. Annealing is provided by gradually increasing the PU gain for each row and column or increasing positive feedback to each PU, the latter being effective to increase hysteresis of each PU or by combining both of these techniques.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.