Abstract
The local minima of a quadratic functional depending on binary variables are discussed. An arbitrary connection matrix can be presented in the form of quasi-Hebbian expansion where each pattern is supplied with its own individual weight. For such matrices statistical physics methods allow one to derive an equation describing local minima of the functional. A model where only one weight differs from other ones is discussed in details. In this case the equation can be solved analytically. Obtained results are confirmed by computer simulations.
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Karandashev, Y., Kryzhanovsky, B., Litinskii, L. (2010). Local Minima of a Quadratic Binary Functional with a Quasi-Hebbian Connection Matrix. In: Diamantaras, K., Duch, W., Iliadis, L.S. (eds) Artificial Neural Networks – ICANN 2010. ICANN 2010. Lecture Notes in Computer Science, vol 6354. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15825-4_5
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DOI: https://doi.org/10.1007/978-3-642-15825-4_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15824-7
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