AIP Conference Proceedings 151 on Neural Networks for Computing
A massively parallel architecture for a self-organizing neural pattern recognition machine
Computer Vision, Graphics, and Image Processing
On the stability, storage capacity, and design of continuous nonlinear neural networks
IEEE Transactions on Systems, Man and Cybernetics
Optimization by simulated annealing: A preliminary computational study for the TSP
WSC '83 Proceedings of the 15th conference on Winter Simulation - Volume 2
What have we learnt from using real parallel machines to solve real problems?
C3P Proceedings of the third conference on Hypercube concurrent computers and applications - Volume 2
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A binary neuromorphic data structure is used to encode the N — city Traveling Salesman Problem (TSP). In this representation the computational complexity, in terms of number of neurons, is reduced from Hopfield and Tank's &Ogr;(N2) to &Ogr;(N log2 N). A continuous synchronous neural network algorithm in conjunction with the LaGrange multiplier, is used to solve the problem. The algorithm has been implemented on the NCUBE hypercube multiprocessor. This algorithm converges faster and has a higher probability to reach a valid tour than previously available results.