Review on echo state networks
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摘要: 回聲狀態網絡是近年來新興的一種遞歸神經網絡,獨特而簡單的訓練方式以及高精度的訓練結果已使其成為當前研究的熱點之一.在該網絡中,引入了儲備池計算模式這一新的神經網絡的建設方案,克服了之前網絡模型基于梯度下降的學習算法所難以避免的收斂慢和容易陷入局部極小等問題.圍繞這種新型網絡結構,國內外許多學者開展了多樣的研究.本文全面深入介紹了回聲狀態網絡這一新興技術,討論了回聲狀態網絡的優缺點,并綜合近年的研究現狀,總結了回聲狀態網絡的主要研究工作進展和未來的研究方向.Abstract: The echo state network(ESN) is a novel kind of recurrent neural network and has recently become a hot topic for its easy and distinctive training method along with high performance.In ESN,the reservoir computing method is introduced,which is a completely new approach used to design a recurrent neural network.By comparing this novel model with existing recurrent neural network models,it can overcome the difficulty encountered in slow convergence and local minimum in the gradient descent based training algorithm.Currently,there is considerable enthusiasm for the research and application of ESN.A review on ESN is presented in this paper.The advantages and drawbacks of ESN and various improvements are analyzed.Finally,some future research directions are also discussed.
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Key words:
- echo state networks /
- reservoir computing /
- recurrent neural networks
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