Short Term Memory and Pattern Matching with Simple Echo State Networks
暂无分享,去创建一个
Two recently proposed approaches to recognize temporal patterns have been proposed by Jager with the so called Echo State Network (ESN) and by Maass with the so called Liquid State Machine (LSM). The ESN approach assumes a sort of “black-box” operability of the networks and claims a broad applicability to several different problems using the same principle. Here we propose a simplified version of ESNs which we call Simple Echo State Network (SESN) which exhibits good results in memory capacity and pattern matching tasks and which allows a better understanding of the capabilities and restrictions of ESNs.
[1] Herbert Jaeger,et al. The''echo state''approach to analysing and training recurrent neural networks , 2001 .
[2] Henry Markram,et al. Real-Time Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations , 2002, Neural Computation.