首页> 外文会议>European signal processing conference;EUSIPCO 2009 >NON-ITERATIVE SOLUTION FOR PARAFAC WITH A TOEPLITZ MATRIX FACTOR
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NON-ITERATIVE SOLUTION FOR PARAFAC WITH A TOEPLITZ MATRIX FACTOR

机译:具有TOEPLITZ矩阵因子的PARAFAC的非迭代解

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Recently, tensor signal processing has received an increased attention, particularly in the context of wireless communication applications. The so-called PARAllel FACtor (PARAFAC) decomposition is certainly the most used tensor tool. In general, the parameter estimation of a PARAFAC decomposition is carried out by means of the iterative ALS algorithm, which exhibits the following main drawbacks: convergence towards local minima, a high number of iterations for convergence, and difficulty to take, optimally, special matrix structures into account. In this paper, we propose a non-iterative parameter estimation method for a PARAFAC decomposition when one matrix factor has a Toeplitz structure, a situation that is commonly encountered in signal processing applications. We illustrate the proposed method by means of simulation results.
机译:近来,张量信号处理已受到越来越多的关注,特别是在无线通信应用的情况下。所谓的PARAllel FACtor(PARAFAC)分解无疑是最常用的张量工具。通常,PARAFAC分解的参数估计是通过迭代ALS算法进行的,它表现出以下主要缺点:向局部极小值收敛,收敛的迭代次数高以及难以采用最优矩阵结构考虑在内。在本文中,我们提出了一种当矩阵因子具有Toeplitz结构时PARAFAC分解的非迭代参数估计方法,这种情况在信号处理应用中经常遇到。我们通过仿真结果说明了所提出的方法。

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