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Cuckoo Search Optimization based design of linear phase FIR filters: A comparison approach

机译:基于线性相位FIR滤波器的Cuckoo搜索优化设计:比较方法

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Optimization algorithms has been used to solve many design problems in science and engineering; notable in image processing, construction design, path planning and many other application. In this paper the method of designing a linear phase symmetric FIR (Finite Impulse Response) filter with the help of Cuckoo Search Optimization (CSO) Algorithm has been highlighted. Since evolutionary optimization algorithms are more powerful than its linear counterpart, CSO has been deployed in order to find out the coefficients of the required filter for a given problem requirement. Even order linear phase symmetric FIR filter are best suitable for this kind of design procedure. The best nests selected by the CSO denotes the particular coefficient set for a given particular even order filter. A low pass filter is shown as a design example. Comparisonal analysis with respect to other strong evolutionary algorithm is also presented in this paper.
机译:优化算法已被用于解决科学与工程中的许多设计问题;在图像处理,施工设计,路径规划和许多其他应用中显着。在本文中,突出了涉及杜鹃搜索优化(CSO)算法的线性相位对称FIR(有限脉冲响应)滤波器的方法。由于进化优化算法比其线性对应物更强大,因此已经部署了CSO,以便找出所需滤波器的系数以获得给定的问题要求。甚至订单线性相位对称FIR滤波器最适合这种设计过程。由CSO选择的最佳嵌套表示针对给定特定偶数序列滤波器的特定系数。低通滤波器显示为设计示例。本文还提出了关于其他强进化算法的比较分析。

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