1 March 1992 Use of dynamical networks for pattern recognition
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An established way to synthesize associative memory networks is to use dynamical neural networks. For large dimensional problems, the dynamical networks usually are computationally burdensome to design and generally introduce spurious memories. A new architecture that consists of an input linear filter, a hidden layer of dynamical network and an output linear filter is proposed in this paper to alleviate some of the difficulties in designing large dimensional dynamical networks. A learning rule and its simplified version are presented for the design of the network parameters.
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Subramania I. Sudharsanan, Subramania I. Sudharsanan, Malur K. Sundareshan, Malur K. Sundareshan, } "Use of dynamical networks for pattern recognition", Proc. SPIE 1707, Applications of Artificial Intelligence X: Knowledge-Based Systems, (1 March 1992); doi: 10.1117/12.56904; https://doi.org/10.1117/12.56904

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