Chaotic Signal Induced Delay Decay in Hodgkin-Huxley Neuron

2021 ◽  
Vol 411 ◽  
pp. 126540
Author(s):  
Veli Baysal ◽  
Ergin Yılmaz
Keyword(s):  
Chaotic Signal

Range Finding and Fault Locating with Chaotic Signal

2014 ◽  
Vol 1 ◽  
pp. 458-461
Author(s):  
An-Bang Wang ◽  
Tong Zhao ◽  
Hang Xu ◽  
Na Wang ◽  
Yun-Cai Wang
Keyword(s):  
Chaotic Signal ◽  
Range Finding ◽  
Fault Locating

scholarly journals The chaotic masking message model using orthogonal functions

2020 ◽  
pp. 67-76
Author(s):  
Svetlana Belim ◽  
◽  
Sergei Belim ◽  
Keyword(s):  
White Noise ◽  
Computer Experiment ◽  
Digital Signal ◽  
Chaotic Signal ◽  
Noise Amplitude ◽  
Trigonometric Functions ◽  
Orthogonal Functions ◽  
Lagrange Polynomials ◽  
Useful Signal ◽  
Orthogonal Property

The model for chaotic signal masking is proposed in the article. The digital signal in the bit representation is encoded using a family of orthogonal functions. Random white noise is superimposed on the resulting analog signal. The white noise amplitude is significantly greater than the amplitude of the signal. The functions orthogonal property is used to retrieve a useful signal. The advantage proposed this model is that it is not necessary to match the noise generators in the source and in the receiver of the message. The integration operation is required to retrieve the message. The using a simple rectangle scheme is discussed. The comparative computer experiment is based on two families of orthogonal functions: simple trigonometric functions and orthogonal Lagrange polynomials. It has been shown that using the trigonometric function family results in fewer errors when retrieving a message.

A Signal Detection Method for Harmonic Signal Submerged in Complex Noise Background

2013 ◽  
Vol 397-400 ◽  
pp. 2262-2265 ◽  
Author(s):  
Ai Juan Quan ◽  
Xiao Dong Sun ◽  
Lan Xiang Zhu
Keyword(s):  
Background Noise ◽  
Detection Method ◽  
Wavelet Packet ◽  
Harmonic Signal ◽  
Chaotic Signal ◽  
Music Algorithm ◽  
Harmonic Frequency ◽  
Multiple Signal Classification ◽  
Chaotic Signals ◽  
Correlation Characteristic

This paper presents a method to detect weak harmonic signal embedded in chaotic noise. Using different correlation characteristic of harmonic and chaotic signal ,we can transform the sample signal to a new data sequence which has new harmonic . The new harmonic frequency is m times of the original harmonic and beyond the center bandwidth of noise. Then use wavelet packet decomposition to analysis the energy distribution of harmonic and chaotic signals and extract the component which the harmonic energy concentrated on, In the end, a multiple signal classification (MUSIC) algorithm is employed to estimate harmonic frequencies . The method suit for the complex background noise (strong chaotic noise and gaussian noise).

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