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中文摘要：
针对电力信号监测中可能遇到的各种干扰，提出了一种基于进化硬件的自适应电力系统形态滤波器的设计方法。不仅滤波算法可自适应调节，而且结构元素形状和尺寸也可自动调整。以遗传算法作为优化工具，在Xilinx XCV2000-E现场可编程门阵列上对滤波器结构和参数进行在线优化。对典型噪声的在线滤波结果表明，该滤波器能够根据噪声的不同自适应调整结构和参数，因而鲁棒性好，适用范围广，滤波性能比均值滤波器和中值滤波器更好，且该滤波器是采用硬件实时实现的，便于在嵌入式系统中应用。
英文摘要：
Focusing on different types of interference possibly encountered in power signal monitoring, a design method of mathematical morphology filter based on evolvable hardware is proposed. Not only filtering algorithms can be adjusted adaptively, but also shape, amplitude and width of the structure elements can be regulated automatically. Taking genetic algorithm as optimizing engine, the architecture of filter is implemented on Xilinx XCV2000-E Field-Programmable Gate Arrays and optimized online. Results of online filtering show that the filter can adjust its architecture and parameters adaptively according to different types of noises, thus has good robustness, wide applicability and better filtering performance than mean filter and median filter. Moreover, the filter is implemented on hardware and operated on real-time, which makes it a very promising filter for embedded systems.
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