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On problem solving with Hopfield neural networks

โœ Scribed by Behzad Kamgar-Parsi; Behrooz Kamgar-Parsi

Book ID
104659761
Publisher
Springer-Verlag
Year
1990
Tongue
English
Weight
818 KB
Volume
62
Category
Article
ISSN
0340-1200

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โœฆ Synopsis

Hop field and Tank have shown that neural networks can be used to solve certain computationally hard problems, in particular they studied the Traveling Salesman Problem (TSP). Based on network simulation results they conclude that analog VLSI neural nets can be promising in solving these problems. Recently, Wilson and Pawley presented the results of their simulations which contradict the original results and cast doubts on the usefulness of neural nets. In this paper we give the results of our simulations that clarify some of the discrepancies. We also investigate the scaling of TSP solutions found by neural nets as the size of the problem increases. Further, we consider the neural net solution of the Clustering Problem, also a computationally hard problem, and discuss the types of problems that appear to be well suited for a neural net approach.

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