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Fast Multichannel Blind System Identification using Laguerre Filters

机译:使用Laguerre过滤器快速多声道盲系统识别

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Multiple channel blind system identification (MBSI) is often used in applications where the input signal cannot be measured and its statistical properties are unknown. Traditionally, the channel dynamics are modeled using finite impulse response filters. The number of model parameters can be significantly reduced if the filters are expanded onto a suitably chosen expansion basis, such as the discrete Laguerre filters, but several tuning parameters must be chosen correctly. This paper describes an efficient implementation of the Laguerre MBSI technique that allows for the rapid evaluation of many possible basis expansions, and hence tuning parameters. Monte-Carlo simulations compare the performances of the traditional and fast implementations.
机译:多通道盲系统识别(MBSI)通常用于输入信号无法测量的应用中,其统计属性未知。传统上,使用有限脉冲响应滤波器建模频道动态。 The number of model parameters can be significantly reduced if the filters are expanded onto a suitably chosen expansion basis, such as the discrete Laguerre filters, but several tuning parameters must be chosen correctly.本文介绍了LAGUERRE MBSI技术的有效实现,其允许对许多可能的基础扩展进行快速评估,并因此进行调整参数。 Monte-Carlo仿真比较传统和快速实现的表现。

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