Results 301 to 310 of about 860,460 (345)

Weak Signal Detection Based on WT-LSTM

2020 IEEE 3rd International Conference on Electronic Information and Communication Technology (ICEICT), 2020
In wireless communication, when the power of received signal is much weaker than the power of noise, signal detection will be very difficult. For the problem of weak signal detection, a new method is proposed in this paper, which combines the two nonlinear methods of Wavelet Transform (WT) and Long Short-Term Memory (LSTM) neural networks together ...
Chunyan Wei, Lin Qi
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A difference resonator for detecting weak signals

Measurement, 1999
Abstract In order to catch the symptoms of machine failures as early and accurately as possible, this paper recommends and first applies a linear difference resonator in the form of x k+1 =ax k +by k , y k+1 =cx k +dy k to detect the characteristic frequency component contained in weak signals.
Liangsheng Qu, Jing Lin
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Comparative Study on Weak Signal Detection Algorithms

2010 International Conference on E-Business and E-Government, 2010
To make the high performance weak signal detection algorithms further applying in the fields of synchronization, channel estimation, equalization for high-data-rate broadband mobile communication systems, algorithms of single-layer autocorrelation, multi-layer autocorrelation, discrete wavelet transform are comparatively studied for the application in ...
Zi-Wei Zheng, Fan Zhang
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Detecting weak sinusoidal signal by LMP test

Sensor Array and Multichannel Signal Processing Workshop Proceedings, 2002, 2003
A simple CFAR detector is proposed in this paper for detecting complex sinusoidal signals with unknown parameters in complex Gaussian noise with unknown variance. The detector is based on the locally most powerful test (LMP), which performance approaches the uniformly most powerful test (UMP) when the signal-to-noise ratio (SNR) approaches zero. It can
null Qing Wang, null Guowei Shi, null Chunru Wan   +2 more
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Weak fault signal detection of rolling bearing

Proceedings 2011 International Conference on Transportation, Mechanical, and Electrical Engineering (TMEE), 2011
The characteristics of local singularity of vibration signal under the wavelet transform are studied, and quantitative analysis of the noise reduction features of wavelet transform methods is carried out. Based on that the modulus maxima of the local singularity of fault vibration signal and noise of rolling bearing under wavelet transform has ...
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Weak Signal Detection Based on Deep Learning

Proceedings of the 2019 4th International Conference on Multimedia Systems and Signal Processing, 2019
Weak signal detection of radio communication signals in complex background noise is an essential part of modern signal processing science. Despite wide application of classical process in various signal detection tasks, the exclusive filter in terms of background noise of radio channel impedes the deployment on modern complex electromagnetism ...
Tao Cheng, Chunhui Liu, Wenrui Ding
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Study on Weak Signal Detection Methods

2013
Weak signal detection technology refers to a technology which analyzes the noise’s production laws and researches the characteristics and correlation of signals with relevant electronics, physics, information, and computer knowledge and techniques, to detect the weak signals that are submerged by noises.
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Detection of weak signals by generalized detector

IEEE 1999 International Geoscience and Remote Sensing Symposium. IGARSS'99 (Cat. No.99CH36293), 2003
This paper is devoted to an experimental study of the generalized detector and comparison with the optimal detector of classical signal detection theory for solving problems of the detection of buried or camouflaged objects. Experimental investigations were carried out under the power signal-to-noise ratio 0.96 dB at the detector input. New features of
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Weak Signal Detection Based on Chaotic Prediction

2009 Second International Workshop on Knowledge Discovery and Data Mining, 2009
In this paper, a weak signal detection method based on radial basis function (RBF) neural networks is discussed. The principle of weak signal detection with a background noise predictor is that the predictor trained by chaotic time series has a small prediction error, and the prediction error becomes relative large when the input contains a source or ...
Junyang Pan, Jinyan Du, Shie Yang
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Data-Adaptive Detection of a Weak Signal

IEEE Transactions on Aerospace and Electronic Systems, 1983
Motivated by a form of the likelihood-ratio-tesf statistic for detection of a rank-one Gaussian signal in colored Gaussian noise, we apply our earlier technique for estimation of a low-rank signal to the problem of estimating and subtracting the waveform of a strong sinusoidal interference prior to detection of a weak sinusoidal signal. We consider the
Tufts, Donald W., Kirsteins, Ivars, Kumaresan, Ramdas   +2 more
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