An ICA-based adaptive filter algorithm for system identification using a state space approach
An ICA-based adaptive filter algorithm for system identification using a state space approach
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DOI：
10.1109/icosp.2008.4697116
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发表时间：
2008-12
期刊：
影响因子：
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通讯作者：
Jun-Mei Yang;H. Sakai
中科院分区：
文献类型：
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作者：
Jun-Mei Yang;H. Sakai
本文提出了一种新的基于ICA的自适应滤波算法，用于系统辨识。考虑加性噪声模型，将信号从噪声观测中分离出来。首先，我们引入了一个增广的状态空间表示的观察信号表示的ICA方面的问题，然后使用自然梯度，我们推导出一个新的算法。给出了算法的局部收敛条件。仿真结果验证了该方法的有效性。
This paper proposes a new ICA-based adaptive filter algorithm for system identification using a state space approach. An additive noise model is considered and the signal is separated from the noisy observation. First, we introduce an augmented state-space expression of the observed signal representing the problem in terms of ICA, and then using the natural gradient, we derive a new algorithm. The local convergence conditions of the proposed algorithm is derived. Some simulations are carried out to illustrate its effectiveness.