Designing optimal time and spatial difference step size is the key technology for quantum-random filtering (QSF) to realize time-varying frequency periodic signal filtering. In this paper, it was proposed to use the short-time Fourier transform (STFT) to dynamically estimate the signal to noise ratio (SNR) and relative frequency of the input time-varying frequency periodic signal. Then the model of time and space difference step size and signal to noise ratio (SNR) and relative frequency of quantum random filter is established by least square method. Finally, the parameters of the quantum filter can be determined step by step by analyzing the characteristics of the actual signal. The simulation results of single-frequency signal and frequency time-varying signal show that the proposed method can quickly and accurately design the optimal filter parameters based on the characteristics of the input signal, and achieve significant filtering effects.
设计最优时间和空间差分步长是量子随机滤波(QSF)实现时变频率周期信号滤波的关键技术。 本文提出用短时傅立叶变换(STFT)动态地估计输入时变频率周期信号的信噪比(SNR)和相对频率,用 最小二乘法建立量子随机滤波器时间和空间差分步长与信噪比(SNR)和相对频率的模型,通过分析实 际信号的特征可以逐步确定量子滤波器的参数。针对单频信号情况和频率时变信号的仿真实验结果表 明,该方法能够根据输入信号的特征,快速、准确设计出滤波器最优参数,取得显著的滤波效果。
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The authors would like to thank Prof. L BEHERA for guiding this paper. Besides, the authors would also like to thank the editors and anonymous reviewers for their time and effort spent handling this paper, as well as for providing constructive comments to further improve the presentation and quality of this paper.
Foundation item: Projects(2017H0022, 2016H6015) supported by Fujian Science and Technology Key Project, China
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Zhou, L., Jin, F., Wu, H. et al. Parameters estimate of recurrent quantum stochastic filter for time variant frequency periodic signals. J. Cent. South Univ. 26, 3328–3337 (2019). https://doi.org/10.1007/s11771-019-4256-7
- quantum stochastic filter (QSF)
- parameters estimation
- least square (LS)
- short-time Fourier transform (STFT)