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Storage Capacity of Kernel Associative Memories

B. Caputo5 and H. Niemann5

(5)  Department of Computer Science, Chair for Pattern Recognition, University of Erlangen-Nuremberg, Martenstrasse 3, 91058 Erlangen, Germany
Abstract
This contribution discusses the thermodynamic phases and storage capacity of an extension of the Hopfield-Little model of associative memory via kernel functions. The analysis is presented for the case of polynomial and Gaussian kernels in a replica symmetry ansatz. As a general result we found for both kernels that the storage capacity increases considerably compared to the Hopfield-Little model.

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