Quantitative Analysis of Noise Impact on Duffing Chaotic Detection System Using Lyapunov Characteristic Exponents

2011 ◽  
Vol 130-134 ◽  
pp. 1331-1337
Author(s):  
Wen Jing Hu ◽  
Zhi Zhen Liu ◽  
Zhi Hui Li
Keyword(s):  
Detection System ◽  
Signal To Noise Ratio ◽  
Duffing Oscillator ◽  
Threshold Value ◽  
System State ◽  
Signal To Noise ◽  
Phase Trajectories ◽  
Lyapunov Characteristic Exponents ◽  
Noise Ratio ◽  
System States

Performance of the Duffing oscillator to detect weak signals buried in heavy noise is analyzed quantitatively by LCEs. First in the case of noise, differential equations to compute LCE s are derived using RHR algorithm, so the quantitative criteria to identify system states are obtained. Then using LCEs, the threshold value of the forced periodic term is found accurately. Finally the system state and state change are analyzed using LCEs by keeping the threshold value and varying the noise intensity, and the minimum signal to noise ratio is determined. By contrast of phase trajectories and LCEs, it shows that phase trajectories disturbed by strong noise sometimes are ambiguous to our eyes, but through LCEs, the system state can be identified clearly and quantitatively especially in strong noise background. So the minimum signal to noise ratio can be obtained accurately.

NMR spectroscopy threshold signal-to-noise ratio

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Petar Kolar ◽  
Lovro Blažok ◽  
Dario Bojanjac
Keyword(s):  
Nmr Spectroscopy ◽  
Communication Channel ◽  
Detection System ◽  
Signal To Noise Ratio ◽  
Standard Procedure ◽  
Threshold Value ◽  
Signal To Noise ◽  
Online Questionnaire ◽  
Spectroscopy System ◽  
Noise Ratio

Abstract Ever since noise was spotted and proven to cause problems for the transmission and detection of information through a communication channel, a standard procedure in the process of characterizing a detection system of the communication channel is to determine the level of the lowest detectable signal. In signal processing, this is usually done by determining the so-called threshold signal-to-noise ratio (SNR). This determination is especially important for the communication channels and systems that constantly operate with low-level signals. A good example of such a system is definitely the NMR spectroscopy system. However, to the authors’ knowledge, the threshold SNR value of NMR spectroscopy systems has not been determined yet. That is why the experts in the field of NMR spectroscopy were asked to assess, using an online questionnaire, which SNR level they considered to be the NMR threshold SNR level. Afterwards, the threshold value was calculated from the obtained data. Finally, it was compared to the existing rule of thumb and thus, a conclusion about its legitimacy was made. The described questionnaire is still available online (https://forms.gle/Y9hyDZ1v1iJoEbk27). This enables everyone to form their own opinion about the threshold SNR level, which the authors encourage the readers to do.

scholarly journals Cooperative GPS and Neighbors Awareness Based Device Discovery for D2D Communication in in-Band Cellular Networks

2018 ◽  
Vol 7 (2.29) ◽  
pp. 700 ◽  
Author(s):  
O Hayat ◽  
R Ngah ◽  
Yasser Zahedi
Keyword(s):  
Cellular Networks ◽  
Channel Capacity ◽  
Signal To Noise Ratio ◽  
Threshold Value ◽  
D2d Communication ◽  
Core Network ◽  
New Paradigm ◽  
Signal To Noise ◽  
Device Discovery ◽  
Noise Ratio

Device to Device (D2D) communication is a new paradigm for next-generation wireless systems to offload data traffic. A device needs to discover neighbor devices on the certain channel to initiate the D2D communication within the minimum period. A device discovery technique based on Global Positioning System (GPS) and neighbor awareness base are proposed for in-band cellular networks. This method is called network-centric approach, and it improves the device discovery efficiency, accuracy, and channel capacity. The differential code is applied to measure the signal to noise ratio of each discovered device. In the case that the signal to noise ratio (SNR) of two devices is above a specified threshold value, then these two devices are qualified for D2D communication. Two procedures are explored for device discovery; discovery by CN (core network) and eNB (evolved node B) cooperation with the help of GPS and neighbor awareness. Using ‘Haversine’ formula, SNR base distance is calculated. Results show an increment in the channel capacity relative to SNR obtained for each device.  

A constrained minimum power adaptive beamformer with time‐varying adaptation rate

Geophysics ◽  
1979 ◽  
Vol 44 (6) ◽  
pp. 1088-1096 ◽  
Author(s):  
Wen‐Wu Shen
Keyword(s):  
Adaptive Algorithm ◽  
Detection System ◽  
Signal To Noise Ratio ◽  
High Amplitude ◽  
Research Station ◽  
Power Performance ◽  
Signal To Noise ◽  
Filter Output ◽  
Short Period ◽  
Noise Ratio

A linear adaptive algorithm was developed for array beamforming purposes. The design goal for the algorithm is to minimize the squared filter output subject to filter constraints which allow energy propagating from the array steering direction to pass without being distorted. The adaptive filter coefficients were initialized to satisfy the constraints which were preserved during the iterations. The adaptation rate is inversely varied with filter output and total input channel power. Performance of the algorithm was studied using the recorded short‐period array data from the Korean Seismic Research Station. Processed were a high‐amplitude signal from Kamchatka, a medium‐amplitude signal from eastern Kazakh, and a number of low‐amplitude signals from central Eurasia. Results of signal‐to‐noise ratio gain relative to a conventional beamformer among the events tested were consistent and were in the range of 4.5 to 6.5 dB in the wide passband. Much better signal‐to‐noise ratio improvement was obtained in the low‐frequency passband. The adaptive algorithm was programmed in the real‐time mode and can be implemented in a front‐end detection system.

Télémètre à détection coherente avec un laser CO2 à ondes entretenues : étude et conception

1983 ◽  
Vol 61 (2) ◽  
pp. 318-331 ◽  
Author(s):  
Denis Vincent ◽  
Gabriel Otis
Keyword(s):  
Detection System ◽  
Signal To Noise Ratio ◽  
Optical Power ◽  
Experimental System ◽  
Intermediate Frequency ◽  
Local Oscillator ◽  
Heterodyne Detection ◽  
Signal To Noise ◽  
Noise Ratio ◽  
Rotating Target

We performed a theoretical and experimental study of a 10.6 μm heterodyne detection system with nonlinear postdetection. A single laser serves as both transmitter and local oscillator; the intermediate frequency is given by the Doppler effect due to a rotating target. An electrooptic crystal modulates the amplitude of the laser beam at a frequency of 15 kHz; a synchronous voltmeter measures the return signal after the nonlinear element. Values of the signal-to-noise ratio with respect to incident optical power agree with the results of the theoretical model. In particular, experimentally measured target-induced frequency spreading effects on the signal-to-noise ratio correspond to the predictions of the model. We also describe an experimental system.

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.

scholarly journals An Improved Chaotic Detection System for Metal Detectors

2021 ◽  
Vol 2087 (1) ◽  
pp. 012065
Author(s):  
Wenjing Hu
Keyword(s):  
Detection System ◽  
Duffing Oscillator ◽  
Threshold Value ◽  
Matlab Simulation ◽  
Metal Detector ◽  
Duffing System ◽  
Characteristic Exponents ◽  
Lyapunov Characteristic Exponents ◽  
Simulation Results ◽  
Metal Detectors

Abstract This paper first applies a chaotic system-Duffing oscillator to a metal detector, and uses RHR algorithm to compute two Lyapunov characteristics exponents of the Duffing system. In this way, the two Lyapunov characteristic exponents can help to judge the Duffing system being chaotic or not quantitatively. And also help to get the threshold value more accurately. Then a simulation model of Duffing system fit for detectors is established by Matlab. Simulation results indicate that an suitable Duffing system can improve the sensitivity of a detector effectively.

scholarly journals An Image Filter Based on Multiobjective Genetic Algorithm and Shearlet Transformation

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Zhi-yong Fan ◽  
Quan-sen Sun ◽  
Ze-xuan Ji ◽  
Kai Hu
Keyword(s):  
Genetic Algorithm ◽  
Wavelet Decomposition ◽  
Signal To Noise Ratio ◽  
Target Function ◽  
Threshold Value ◽  
Rician Noise ◽  
Signal To Noise ◽  
Multiobjective Genetic Algorithm ◽  
Noise Ratio ◽  
Magnetic Resonance Imaging Mri

Rician noise pollutes magnetic resonance imaging (MRI) data, making data’s postprocessing difficult. In order to remove this noise and avoid loss of details as much as possible, we proposed a filter algorithm using both multiobjective genetic algorithm (MOGA) and Shearlet transformation. Firstly, the multiscale wavelet decomposition is applied to the target image. Secondly, the MOGA target function is constructed by evaluation methods, such as signal-to-noise ratio (SNR) and mean square error (MSE). Thirdly, MOGA is used with optimal coefficients of Shearlet wavelet threshold value in a different scale and a different orientation. Finally, the noise-free image could be obtained through inverse wavelet transform. At the end of the paper, experimental results show that this proposed algorithm eliminates Rician noise more effectively and yields better peak signal-to-noise ratio (PSNR) gains compared with other traditional filters.

scholarly journals Detection Spectrum Optimization of Stealth Aircraft Targets From a Space-based Infrared Platform

2021 ◽  
Author(s):  
Xinyue Ni ◽  
Shutian Yu ◽  
Xiaofeng Su ◽  
Fansheng Chen
Keyword(s):  
Detection System ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Central Wavelength ◽  
Detection Techniques ◽  
Detection Systems ◽  
Spectrum Detection ◽  
Detection Technology ◽  
Spectrum Optimization ◽  
Noise Ratio

Abstract Advances in infrared detection techniques require novel spectrum dynamic-modification strategies capable of sensing unprecedentedly low target radiant intensities. A conventional fixed-spectrum detection system cannot satisfy the effective detection of stealth aircraft targets due to complex Earth background clutter and atmospheric attenuation. Therefore, a detection method that can highlight aircraft targets is urgently needed to enhance stealth aircraft detectability. In this research, a spectrum set consisting of different bandwidths associated with a central wavelength is established. Furthermore, a signal-to-noise ratio of the stealth aircraft is computed using the established spectrum set. Finally, the optimal spectrum is selected according to the maximal signal-to-noise ratio from the spectrum set. Our numerical experiments and simulations further demonstrate that the proposed methodology can substantially strengthen the detection performance of stealth aircraft compared with traditional fixed-spectrum detection systems. This work on detection spectrum optimization paves the way to stealth aircraft detection and opens new vistas in the field of target detection technology.

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