Abstract
Recently, the stochastic resonance effect has been widely used by the method of discovering and extracting weak periodic signals from strong noise through the stochastic resonance effect. The detection of the single-frequency weak signals by using stochastic resonance effect is widely used. However, the detection methods of the multifrequency weak signals need to be researched. According to the different frequency input signals of a given system, this paper puts forward a detection method of multifrequency signal by using adaptive stochastic resonance, which analyzed the frequency characteristics and the parallel number of the input signals, adjusted system parameters automatically to the low frequency signals in the fixed step size, and then measured the stochastic resonance phenomenon based on the frequency of the periodic signals to select the most appropriate indicators in the middle or high frequency. Finally, the optimized system parameters are founded and the frequency of the given signals is extracted in the frequency domain of the stochastic resonance output signals. Compared with the traditional detection methods, the method in this paper not only improves the work efficiency but also makes it more accurate by using the color noise, the frequency is more accurate being extracted from the measured signal. The consistency between the simulation results and analysis shows that this method is effective and feasible.
Highlights
We need to find and extract useful signal through the signal detection in engineering technology and scientific research
Based on the traditional single-frequency weak signal detection, selected the signal-to-noise ratio (SNR) to be a measurement index of the generation of stochastic resonance and reducing the range of parameter values by the threshold analysis, this method can find the optimal system parameters effectively and can detect a multiple weak periodic signals
When the input signal A = 0, the noise intensity D = 0, the potential function corresponding to the nonlinear bistable system is
Summary
We need to find and extract useful signal through the signal detection in engineering technology and scientific research. Based on the traditional single-frequency weak signal detection, selected the SNR to be a measurement index of the generation of stochastic resonance and reducing the range of parameter values by the threshold analysis, this method can find the optimal system parameters effectively and can detect a multiple weak periodic signals. This paper makes processing the output signal of stochastic resonance by using the autocorrelation method which only changes the amplitude and phase, without changing the frequency It can reduce the impact of noise, make the waveform more similar to measured signal, highlight the frequency of the signal cycle component, and enhance the SNR. Significant changes of the output signal spectrogram occurred in the approximation process This characteristic can be taken as the basis for signal detection and extraction. This paper made a large number of numerical simulations by MATLAB, and the simulation results show the effectiveness and feasibility of the method and have a good prospect
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