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A Newton-like algorithm for complex variables with applications in blind equalization

机译:一种类似于牛顿算法的复杂变量及其在盲均衡中的应用

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摘要

Although the Newton algorithm has been extended to the complex domain in different forms, none of them seems to be directly applicable to blind equalization. Therefore, the objective of this correspondence is to develop an algorithm for blind equalization in the complex domain. We propose a Newton-like algorithm based on a complex Taylor series. Stochastic Newton-like algorithms (SNLA) for two blind equalization cost functions are developed. Simulations show that the new algorithms perform slightly better than the self-orthogonalizing algorithm.
机译:尽管牛顿算法已以不同形式扩展到复数域,但是它们似乎都不直接适用于盲均衡。因此,这种对应关系的目的是开发一种在复杂域中进行盲均衡的算法。我们提出了一种基于复杂泰勒级数的牛顿式算法。开发了用于两个盲均衡成本函数的随机牛顿式算法(SNLA)。仿真表明,新算法的性能略优于自正交算法。

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