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A comparison study of system identification using Hammerstein model

机译:使用Hammerstein模型进行系统识别的比较研究

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An attempt has been made in this paper to present performance analysis of a Hammerstein model for system identification area. Hammerstein model block structure is formed by cascade of linear and nonlinear parts. This study different from the studies in literature, focuses on the performance of Hammerstein block model that Second Order Volterra (SOV) Model is preferred instead of Memoryless Polynomial Nonlinear (MPN) as nonlinear part. In simulations, different systems are identified by proposed Hammerstein model which is optimized with classical and heuristic algorithms. Also, its performance is compared with different models.
机译:本文已尝试提出针对系统识别区域的Hammerstein模型的性能分析。 Hammerstein模型块结构由线性和非线性零件的级联形成。该研究与文献研究不同,侧重于Hammerstein块模型的性能,该模型首选二阶Volterra(SOV)模型代替无记忆多项式非线性(MPN)作为非线性部分。在仿真中,通过建议的Hammerstein模型识别不同的系统,该模型使用经典算法和启发式算法进行了优化。另外,将其性能与不同型号进行了比较。

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