Reservoir Optimization in Recurrent Neural Networks using Kronecker Kernels
In this paper, using the mathematical properties of self-kronecker-production of small size random matrices, a simple but effective method is presented to optimize the reservoir of an echo state network given a certain task. The experimental results investigating the NARMA system show that few steps of the proposed optimization process can lead to a near optimum solution.
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Record created on 2008-06-16, modified on 2016-08-08