Abstract
In this research paper, a novel Convolutional Associative Memory is proposed. In the proposed model, Synapse of each neuron is modeled as a Linear FIR filter. The dynamics of Convolutional Associative Memory is discussed. A new method called Sub-sampling is given. Proof of convergence theorem is discussed. An example depicting the convergence is shown. Some potential applications of the proposed model are also proposed.
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CITATION STYLE
Garimella, R. M., Munugoti, S. D., & Rayala, A. (2015). Convolutional associative memory: FIR filter model of synapse. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9491, pp. 356–364). Springer Verlag. https://doi.org/10.1007/978-3-319-26555-1_40
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