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傅里叶变换基的固有缺陷导致传统滤波器选型分析方法在实际应用场合中经常不能有效地选择出最优滤波器。小波分析方法可以实现从多种不同滤波器中选择出阻带信号抑制最强,通带内波纹最小的滤波器。针对一型微弱信号检测装置,确定出两型较优的滤波器,利用小波伪频率确定小波分解所需分解层数,根据小波分解重构算法对滤波器输出信号的高频细节进行分析研究。仿真结果与模拟电路实验表明,与快速傅立叶变换的分析方法相比,小波分析可以提供清晰的对比分析结果,得到了在不同频率范围内,不同滤波器作用之后的差异明显的滤波效果,最终选择出滤波效果最佳的模拟滤波器。
The inherent defects of Fourier transform base lead to the traditional filter selection analysis method in practical applications often can not effectively select the optimal filter. Wavelet analysis method can be selected from a variety of different filters to stop the strongest stopband signal, passband minimum ripple filter. Aiming at a type of weak signal detection device, two types of optimal filters are determined. The number of decomposition layers required for wavelet decomposition is determined by the wavelet pseudo-frequency. The high-frequency details of the output signal are analyzed based on the wavelet decomposition and reconstruction algorithm. The simulation results and simulation results show that the wavelet analysis can provide a clear contrast analysis result compared with the fast Fourier transform analysis method, and the obvious filtering effect is obtained in different frequency range and different filters. The final choice The best filter out of the analog filter.