Blind system identification using fourth order spectral analysis of complex signals

C. Huet, J. Le Roux
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引用次数: 4

Abstract

In this paper we give an analytic optimal solution to the identification problem of non minimum phase systems using the fourth order spectra. We show that this solution is in first approximation equivalent to the solution given by the well-known kurtosis maximization method. The proposed solution gives the phase of the system transfer function, the modulus can be obtained from the second order statistics. However this solution requires trispectrum phase unwrapping as the trispectrum phase is known in the interval [-/spl pi/,/spl pi/] but needs to be unwrapped in the interval [-4/spl pi/,4/spl pi/] in order to obtain the optimal solution. Therefore, we present different phase unwrapping solutions. Next, we propose a method to improve the trispectrum phase estimation using a factorizability condition. Simulation results are given and the algorithm shows good behavior even with few data.
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基于四阶谱分析的复杂信号盲系统辨识
本文利用四阶谱给出了非最小相位系统辨识问题的解析最优解。我们证明了这个解在一阶近似上等价于著名的峰度最大化方法给出的解。提出的解给出了系统传递函数的相位,模量可由二阶统计量得到。然而,该解决方案需要三谱相位展开,因为三谱相位在区间[-/spl pi/,/spl pi/]中已知,但需要在区间[-4/spl pi/,4/spl pi/]中展开,以获得最优解。因此,我们提出了不同的相位展开解决方案。其次,我们提出了一种利用可分解性条件改进三谱相位估计的方法。仿真结果表明,在数据较少的情况下,该算法仍具有良好的性能。
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