The Adaptive Stochastic Resonance Signal Detection System Based on the Multi-Point Random Search Algorithm

2013 ◽  
Vol 339 ◽  
pp. 409-415
Author(s):  
Shui Lin Tu ◽  
Zheng Yang Wu ◽  
Zhen Yi Wu
Keyword(s):  
Signal Detection ◽  
Stochastic Resonance ◽  
Search Algorithm ◽  
Detection System ◽  
Signal To Noise Ratio ◽  
Random Search ◽  
System Structure ◽  
Bistable System ◽  
Weak Signal ◽  
Random Search Algorithm

A model of adaptive stochastic resonance system based on the multi-point random search algorithm is proposed, and a weak signal detection system of adaptive stochastic resonance is established on the LabVIEW development platform. In this detection system, the typical nonlinear bistable system is used as the core of signal processing, and the system output signal-to-noise ratio is chosen as the optimizing objective function. The system structure parameters can be adjusted adaptively by using the multi-point random search algorithm, on which the optimal state of stochastic resonance of the system can be remained and the frequency of the weak signal can be obtained. Influences of the system parameters and the Gaussian noise on the stochastic resonance can be detected by this system. Experimental results show that this detection system is efficient, and has potential applications.

Weak Signal Detection System Based on Lock-in Amplifier Technology

2013 ◽  
Vol 389 ◽  
pp. 489-493
Author(s):  
Yong Lv ◽  
Chun Hui Niu ◽  
Yue Qiang Li ◽  
Qing Shan Chen ◽  
Xiao Ying Li ◽  
...  
Keyword(s):  
Signal Detection ◽  
Detection System ◽  
Signal To Noise Ratio ◽  
Weak Signal ◽  
Weak Signal Detection ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Pass ◽  
Phase Sensitive ◽  
Lock In

In order to detect the weak signal deeply buried in the noise, a weak signal detection system based on lock-in amplifier is proposed. The system includes the preamplifier circuit, active low pass filter circuit, AC amplifying circuit and phase sensitive demodulation circuit. Test results show that it can greatly increase the signal-to-noise ratio (SNR) up to 12.7db.

Weak photoacoustic signal detection based on the differential duffing oscillator

2018 ◽  
Vol 32 (09) ◽  
pp. 1850103 ◽  
Author(s):  
Chenjing Li ◽  
Xuemei Xu ◽  
Yipeng Ding ◽  
Linzi Yin ◽  
Beibei Dou
Keyword(s):  
Signal Detection ◽  
Photoacoustic Spectroscopy ◽  
Detection System ◽  
Signal To Noise Ratio ◽  
Duffing Oscillator ◽  
Threshold Value ◽  
Photoacoustic Signal ◽  
Weak Signal ◽  
Weak Signal Detection ◽  
First Time

In view of photoacoustic spectroscopy theory, the relationship between weak photoacoustic signal and gas concentration is described. The studies, on the principle of Duffing oscillator for identifying state transition as well as determining the threshold value, have proven the feasibility of applying the Duffing oscillator in weak signal detection. An improved differential Duffing oscillator is proposed to identify weak signals with any frequency and ameliorate the signal-to-noise ratio. The analytical methods and numerical experiments of the novel model are introduced in detail to confirm its superiority. Then the signal detection system of weak photoacoustic based on differential Duffing oscillator is constructed, it is the first time that the weak signal detection method with differential Duffing oscillator is applied triumphantly in photoacoustic spectroscopy gas monitoring technology.

Research on Weak Signal Detection by Adding Noise to Cascaded Stochastic Resonance Step by Step

2013 ◽  
Vol 433-435 ◽  
pp. 450-455 ◽  
Author(s):  
Shui Lin Tu ◽  
Zheng Yang Wu ◽  
Zhen Yi Wu
Keyword(s):  
Signal Detection ◽  
Stochastic Resonance ◽  
Transfer Functions ◽  
Bistable System ◽  
Moderate Intensity ◽  
Weak Signal ◽  
Weak Signal Detection ◽  
Potential Wells ◽  
Local Oscillation ◽  
Dc Component

In view of the fact that after excitated by weak signal under background of noise the action of transition between potential wells of bistable system cannot occur or occasionally happen, this paper puts forward a method of weak signal detection by adding noise to cascaded stochastic resonance step by step. In this method the output signal of the former bistable system whose transition between potential wells occasionally occurs is converted into a local oscillation within an unilateral potential well step by step, then DC component is removed, a moderate intensity of Gaussian color noise is stacked and then by utilizing energy transfer functions of bistable system, gradually the signal is enabled to overcome the critical value of the latter bistable system and transition of frequency synchronization between potential wells is produced for signals to be tested. The simulation results of weak sinusoidal signal and periodic impact signals detected under the background of noise show the feasibility of this method.

scholarly journals A Memristor Based Chaotic Oscillator for Weak Signal Detection and Its Circuitry Realization

2021 ◽  
Author(s):  
Kaifeng Dong ◽  
Kun Xu ◽  
Youyou Zhou ◽  
Chao Zuo ◽  
Leiming Wang ◽  
...  
Keyword(s):  
Signal Detection ◽  
Detection System ◽  
Signal To Noise Ratio ◽  
Detection Accuracy ◽  
Chaotic Oscillator ◽  
Weak Signal ◽  
Weak Signal Detection ◽  
Noise Performance ◽  
Detection Range ◽  
Implementation Scheme

Abstract A new type of weak signal detection system that combines the memristor and Van der pol-Duffing chaotic system has been proposed in this paper, and the dynamic characteristics of the system are studied. It is observed that the system can change from a chaotic state to a periodic state under different driving force amplitudes. Moreover, as compared with several classical chaotic oscillators, the numerical simulation results show that the system has stronger anti-noise performance with the detectable signal-to-noise ratio reaches -163dB, and has a wider detection range. Its detection accuracy is up to 1 × 10 −9 . More importantly, this paper provides the circuit implementation scheme of the system, and the weak signal can be detected with our designed circuit. This may offer a possible way for weak signal detection system with good performance in anti-noise performance, detection range and accuracy.

scholarly journals Constructing Synthetic Samples

2016 ◽  
Vol 32 (1) ◽  
pp. 113-127
Author(s):  
Hua Dong ◽  
Glen Meeden
Keyword(s):  
Optimization Problem ◽  
Search Algorithm ◽  
Random Search ◽  
The United States ◽  
Simulation Studies ◽  
Synthetic Sample ◽  
Population Means ◽  
Adaptive Random Search ◽  
Random Search Algorithm ◽  
Two Populations

Abstract We consider the problem of constructing a synthetic sample from a population of interest which cannot be sampled from but for which the population means of some of its variables are known. In addition, we assume that we have in hand samples from two similar populations. Using the known population means, we will select subsamples from the samples of the other two populations which we will then combine to construct the synthetic sample. The synthetic sample is obtained by solving an optimization problem, where the known population means, are used as constraints. The optimization is achieved through an adaptive random search algorithm. Simulation studies are presented to demonstrate the effectiveness of our approach. We observe that on average, such synthetic samples behave very much like actual samples from the population of interest. As an application we consider constructing a one-percent synthetic sample for the missing 1890 decennial sample of the United States.

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