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Recursive identification of FIR systems with binary-valued observations

机译:具有二进制值观测的FIR系统的递归识别

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This paper investigates the identification of the finite impulse response (FIR) systems with binary-valued observations. Combining with the stochastic gradient algorithm and statistical property of the system noise, a recursive projection algorithm is proposed to estimate the unknown parameters. Under some mild conditions on the a priori knowledge of the unknown parameters and inputs, the algorithm is proved to be convergent in the almost sure and mean square sense. Furthermore, the almost sure and mean square convergence rates of estimation errors are also obtained, and the schemes of selecting the quantization value are provided to ensure such rates. A numerical example is given to demonstrate the effectiveness of the algorithm and the main results obtained.
机译:本文研究了具有二进制值观测的有限脉冲响应(FIR)系统的识别。 组合与随机梯度算法和系统噪声的统计特性,提出了一种递归投影算法来估计未知参数。 在一些温和的条件下,在先知参数和输入的先验知识上,证明该算法在几乎确定和均值的方形感染中被收敛。 此外,还获得了估计误差的几乎肯定和平均的平方收敛速率,并且提供了选择量化值的方案以确保这些速率。 给出了数值例子来证明算法的有效性和所获得的主要结果。

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