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A modified adaptive IIR filter design via wavelet networks based on Lyapunov stability theory

机译:基于Lyapunov稳定性理论的改进的小波网络自适应IIR滤波器设计。

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In this paper, we present a wavelet network IIR filtering system satisfying asymptotic stability in the sense of Lyapunov unlike many other gradient descent algorithms based adaptive filtering systems. The proposed system also carries the advantages of the time-frequency specific properties of wavelet networks embedded into the proposed filter dynamics. Two experiments for system identification problems corresponding to the infinite impulse response filter design are proposed. The results verified that the proposed wavelet network infinite impulse response adaptive filtering system not only performs better than gradient descent based algorithms but also performs as good as other stability theory based optimization algorithms.
机译:在本文中,我们提出了一种基于Lyapunov的渐近稳定性的小波网络IIR滤波系统,这与许多其他基于梯度下降算法的自适应滤波系统不同。所提出的系统还具有嵌入到所提出的滤波器动力学中的小波网络的时频特定特性的优点。提出了两个与无限冲激响应滤波器设计相对应的系统识别问题的实验。结果证明,所提出的小波网络无限冲激响应自适应滤波系统不仅性能优于基于梯度下降的算法,而且性能还优于其他基于稳定性理论的优化算法。

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