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首页> 外文期刊>Circuits, systems, and signal processing >Maximum Likelihood-Based Recursive Least-Squares Algorithm for Multivariable Systems with Colored Noises Using the Decomposition Technique
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Maximum Likelihood-Based Recursive Least-Squares Algorithm for Multivariable Systems with Colored Noises Using the Decomposition Technique

机译：使用分解技术的有色噪声多变量系统基于最大似然的递归最小二乘算法

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摘要

This paper considers the parameter estimation problems for a class of multivariable equation-error systems with colored noises. By using the decomposition technique, a multivariable system is transformed into several subsystems to reduce the computational burden, and a maximum likelihood-based recursive least-squares identification algorithm is developed for estimating the parameters of each subsystem. As a comparison, a multivariable recursive extended least-squares algorithm is presented. The analysis indicates that the proposed algorithm has lower computational complexity than the multivariable recursive extended least-squares algorithm, and the numerical simulation results demonstrate that the proposed method is effective.
机译：本文考虑了一类带有色噪声的多元方程误差系统的参数估计问题。通过使用分解技术，将多变量系统转换为几个子系统以减少计算负担，并开发了基于最大似然性的递归最小二乘识别算法来估计每个子系统的参数。作为比较，提出了一种多变量递归扩展最小二乘算法。分析表明，该算法比多变量递归扩展最小二乘算法具有较低的计算复杂度，数值仿真结果表明该方法是有效的。

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