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Design of optimal shift-invariant orthonormal wavelet filter banks via genetic algorithm

机译:基于遗传算法的最优平移不变正交小波滤波器组设计

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Although the orthonormal discrete wavelet transform offers the advantage of computation efficiency, it is generally not shift-invariant thereby yielding different transform coefficient values when applied to the same signal with different time shifts. Proposed in this paper is a new design method based on the genetic algorithm for the construction of orthonormal wavelet filter banks with an optimal shift-invariant property. In particular, the paper presents transformation of the multi-objective filter bank design problem to a single-objective constrained optimisation problem, chromosome representation of filter coefficients, the shift-invariant objective function for chromosome fitness evaluation, as well as a special constraint to discard infeasible solutions thereby confining the search for the optimum, based on the natural evolution mechanisms, within the wavelet sub-space. Furthermore, using denoising as an example, the performance of the wavelet filter bank constructed is compared with the classical wavelet filter banks to demonstrate its optimality.
机译:尽管正交离散小波变换具有计算效率高的优点,但通常不偏移不变,从而在应用于具有不同时移的相同信号时会产生不同的变换系数值。本文提出了一种基于遗传算法的构造具有最优平移不变特性的正交小波滤波器组的新设计方法。特别是,本文提出了多目标滤波器组设计问题到单目标约束优化问题的变换,滤波器系数的染色体表示,用于染色体适应性评估的位移不变目标函数以及丢弃的特殊约束。因此,不可行的解决方案因此将基于自然演化机制的最优搜索限制在子波子空间内。此外,以去噪为例,将构造的小波滤波器组的性能与经典的小波滤波器组进行比较,以证明其最优性。

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