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- Leonid B. Litinskii, Dmitry E. Romanov
- ICANN
- 2006

We present an algorithm of clustering of many-dimensional objects, where only the distances between objects are used. Centers of classes are found with the aid of neuron-like procedure with lateral… (More)

- Leonid B. Litinskii
- ICANN
- 2005

The problem of finding of the deepest local minimum of a quadratic functional of binary variables is discussed. Our approach is based on the asynchronous neural dynamics and utilizes the eigenvalues… (More)

- Yakov M. Karandashev, Boris Kryzhanovsky, Leonid B. Litinskii
- Physical review. E, Statistical, nonlinear, and…
- 2012

We generalize the standard Hopfield model to the case when a weight is assigned to each input pattern. The weight can be interpreted as the frequency of the pattern occurrence at the input of the… (More)

We study the set of fixed points of a Hopfield-type neural network with a connection matrix constructed from a high-symmetry set of memorized patterns using the Hebb rule. The memorized patterns… (More)

- Leonid B. Litinskii, Bashir M. Magomedov
- ArXiv
- 2004

The problem of finding out the global minimum of a multiextremal functional is discussed. One frequently faces with such a functional in various applications. We propose a procedure, which depends on… (More)

The proposed method of the free energy calculation is based on the approximation of the energy distribution in the microcanonical ensemble by the Gaussian distribution. We hope that our approach will… (More)

The storage capacity of the Hopfield model is about 15% of the network size. It can be increased significantly in the Potts-glass model of the associative memory only. In this model neurons can be in… (More)

- Leonid B. Litinskii, Boris Kryzhanovsky, Anatoly B. Fonarev
- Proceedings of the 9th International Conference…
- 2002

In this paper we develop a formalism allowing us to describe operating of a network based on the parametrical four-wave mixing process that is well-known in nonlinear optics. The recognition power of… (More)

- Boris Kryzhanovsky, Vladimir Kryzhanovsky, Leonid B. Litinskii
- Advances in Machine Learning II
- 2010

We present the review of our works related to the theory of vector neural networks. The interconnection matrix always is constructed according to the generalized Hebb’s rule, which is well-known in… (More)

Neuron models of associative memory provide a new and prospective technology for reliable date storage and patterns recognition. However, even when the patterns are uncorrelated, the efficiency of… (More)