Neural Comput - Design strategies for weight matrices of echo state networks.

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Resumo

This article develops approaches to generate dynamical reservoirs of echo state networks with desired properties reducing the amount of randomness. It is possible to create weight matrices with a predefined singular value spectrum. The procedure guarantees stability (echo state property). We prove the minimization of the impact of noise on the training process. The resulting reservoir types are strongly related to reservoirs already known in the literature. Our experiments show that well-chosen input weights can improve performance.

Resumo Limpo

articl develop approach generat dynam reservoir echo state network desir properti reduc amount random possibl creat weight matric predefin singular valu spectrum procedur guarante stabil echo state properti prove minim impact nois train process result reservoir type strong relat reservoir alreadi known literatur experi show wellchosen input weight can improv perform

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