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| Study of Recursive Least Square Adaptive Algorithm for Weighted Stochastic Pooling Networks |
| HAN Bo, LIU Jia, GENG Jinhua, DUAN Fabing
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| Institute of Complexity Science, Qingdao University, Qingdao 266071, China |
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Abstract In practice, the probability distribution model of the background noise is often unknown. Under this circumstance, a recursive least square adaptive algorithm is developed to estimate the random signal via the weighted stochastic pooling network. The analytical formula of the recursive least square adaptive algorithm is derived, and the convergence of the algorithm, the mean square error of the network outputs and the learning curve are analyzed. For non-stationary input signals, the proposed algorithm with the forgetting factor can effectively track the change of the signal. These theoretical results are demonstrated by the numerical experiments, and the phenomenon of suprathreshold stochastic resonance is also observed. The obtained results lay the fundamental framework for the application of the weighted stochastic pooling network in signal estimation.
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Received: 15 July 2019
Published: 29 April 2020
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