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.

Method of estimation of hidden correlation of narrowband noise signals

2019 ◽  
pp. 34-39 ◽  
Author(s):  
E.I. Chernov ◽  
N.E. Sobolev ◽  
A.A. Bondarchuk ◽  
L.E. Aristarhova
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
New Technology ◽  
Digital Signal ◽  
Measuring Instruments ◽  
Central Frequency ◽  
Pearson Criterion ◽  
Useful Signal ◽  
Band Limited ◽  
Narrowband Noise

The concept of hidden correlation of noise signals is introduced. The existence of a hidden correlation between narrowband noise signals isolated simultaneously from broadband band-limited noise is theoretically proved. A method for estimating the latent correlation of narrowband noise signals has been developed and experimentally investigated. As a result of the experiment, where a time frag ent of band-limited noise, the basis of which is shot noise, is used as the studied signal, it is established: when applying the Pearson criterion, there is practically no correlation between the signal at the Central frequency and the sum of signals at mirror frequencies; when applying the proposed method for the analysis of the same signals, a strong hidden correlation is found. The proposed method is useful for researchers, engineers and metrologists engaged in digital signal processing, as well as developers of measuring instruments using a new technology for isolating a useful signal from noise – the method of mirror noise images.

UNMASKING CHAOTIC MASK BY A WAVELET MULTISCALE DECOMPOSITION ALGORITHM

2001 ◽  
Vol 11 (02) ◽  
pp. 561-569 ◽  
Author(s):  
XIANGAO HUANG ◽  
JIANXUE XU ◽  
WEI HUANG ◽  
ZEJUN LU
Keyword(s):  
Numerical Simulations ◽  
Noise Reduction ◽  
Chaotic System ◽  
Chaos Synchronization ◽  
Reduction Method ◽  
Chaotic Signal ◽  
Decomposition Algorithm ◽  
Multiscale Decomposition ◽  
Useful Signal ◽  
Quantitative Analyses

A method is proposed for extracting a useful signal hidden in a deterministic chaotic signal using a wavelet multiscale decomposition algorithm that can separate two signals with different wavelet scales. The mask removal is done without resorting to chaos synchronization. It is a noise reduction method without knowing the dynamical model of chaotic system, and restricting the modulation ratio of the chaos signal and useful signal. So this method is effective for unmasking chaotic mask through the quantitative analyses and the numerical simulations of three examples.

scholarly journals Precise digital demodulation for fiber optic interferometer sensors

2016 ◽  
Vol 41 ◽  
pp. 1660139
Author(s):  
Andrei Medvedev ◽  
Andrei Berezhnoi ◽  
Aleksei Kudryashov ◽  
Leonid Liokumovich
Keyword(s):  
Phase Modulation ◽  
Fiber Optic ◽  
Digital Signal ◽  
Signal Extraction ◽  
Programming Environment ◽  
Trigonometric Functions ◽  
Harmonic Phase ◽  
Signal Demodulation ◽  
Digital Demodulation ◽  
Inverse Trigonometric Functions

Different methods are used in the interferometer sensors for target signal extraction. Digital technologies provide new opportunities for precise signal detection. We have developed the principle of signal demodulation using an additional harmonic phase modulation and digital signal processing. The principle allows implementation of processing algorithms using different ratios between modulation and discretization frequencies. The expressions allowing calculation of the phase difference using the inverse trigonometric functions were derived. The method was realized in LabVIEW programming environment and was demonstrated for various signal shapes.

scholarly journals CONTROLLED PARAMETER MODULATIONS IN SECURE DIGITAL SIGNAL TRANSMISSIONS

2007 ◽  
Vol 17 (11) ◽  
pp. 4187-4194 ◽  
Author(s):  
P. PALANIYANDI ◽  
M. LAKSHMANAN
Keyword(s):  
Signal Transmission ◽  
Digital Signal ◽  
Chaotic Signal ◽  
Single Step ◽  
Simple Method ◽  
Parameter Modulation ◽  
Maximum Security ◽  
Modulation Technique ◽  
Modified Method ◽  
The Lorenz System

We propose a simple method for secure digital signal transmission by making some modifications in the single-step parameter modulation technique propo sed earlier to overcome certain inherent deficiencies. In the modified method, the parameter modulation is effectively regulated or controlled by the chaotic signal obtained from the transmitting chaotic system so that it has the maximum security. Then, the same idea is also extended to the multistep parameter modulation technique. It is found that both the methods are secure against ciphertext (return map) and plaintex attacks. We have illustrated these methods by means of the Lorenz system.

AN IMPROVED CHAOTIC MASKING SCHEME VIA SYSTEM-ALTERNATING

2013 ◽  
Vol 27 (31) ◽  
pp. 1350201
Author(s):  
XING-YUAN WANG ◽  
BING XU ◽  
YUTIAN MA
Keyword(s):  
Communication System ◽  
Secure Communication ◽  
System Simulation ◽  
Chaotic Signal ◽  
State Observer ◽  
Simulation Environment ◽  
Alternating Method ◽  
Useful Signal ◽  
Communication Scheme ◽  
Conventional Scheme

Aiming at the drawbacks of the chaotic masking scheme, this paper optimizes this conventional scheme by using improved state observer method and system-alternating method, proposes a new secure communication scheme which can improve these drawbacks of chaotic method: (1) Restriction that the power of useful signal must be smaller than that of chaotic signal. (2) Low security. In addition, the model of this whole communication system is constructed under the system simulation environment of Simulink.

Analytical and Simulation Results for the Stochastic Spatial Fitzhugh-Nagumo Model Neuron

2008 ◽  
Vol 20 (12) ◽  
pp. 3003-3033 ◽  
Author(s):  
Henry C. Tuckwell
Keyword(s):  
White Noise ◽  
Model Neuron ◽  
Space Time ◽  
Noise Amplitude ◽  
Amplitude Noise ◽  
Analytical Results ◽  
Uniform Noise ◽  
Simulation Results ◽  
The Difference ◽  
Parameter Ranges

For the Fitzhugh-Nagumo system with space-time white noise, we use numerical methods to consider the generation of action potentials and the reliability of transmission in the presence of noise. The accuracy of simulated solutions is verified by comparison with known exact analytical results. Noise of small amplitude may prevent transmission directly, whereas larger-amplitude noise may also interfere by producing secondary nonlocal responses. The probability of transmission as a function of noise amplitude is found for both uniform noise and noise restricted to a patch. For certain parameter ranges, the recovery variable may be neglected to give a single-component nonlinear diffusion with space-time white noise. In this case, analytical results are obtained for small perturbations and noise, which agree well with simulation results. For the voltage variable, expressions are given for the mean, covariance, and variance and their steady-state forms. The spectral density of the voltage is also obtained. Numerical examples are given of the difference between the properties of nonlinear and linear cables, and the validity of the expressions obtained for the statistical properties is investigated as a function of noise amplitude. For given parameters, analytical results are in good agreement with simulation until a certain critical noise amplitude is reached, which can be estimated. The role of trigger zones in increasing the reliability of transmission is discussed.

PARAMETER IDENTIFICATION OF CHAOTIC SYSTEMS USING WAVELETS AND NEURAL NETWORKS

2004 ◽  
Vol 14 (04) ◽  
pp. 1467-1476 ◽  
Author(s):  
YOUSEF AL-ASSAF ◽  
WAJDI M. AHMAD
Keyword(s):  
Wavelet Transforms ◽  
Secure Communication ◽  
Control Parameter ◽  
Chaotic Systems ◽  
Chaotic Signal ◽  
Potential Utility ◽  
Feed Forward Neural Network ◽  
Useful Signal ◽  
Parametric Modulation ◽  
Electronic Oscillator

This paper addresses the problem of reconstructing a slowly-varying information-bearing signal from a parametrically modulated, nonstationary dynamical signal. A chaotic electronic oscillator model characterized by one control parameter and a double-scroll-like attractor is used throughout the study. Wavelet transforms are used to extract features of the chaotic signal resulting from parametric modulation of the control parameter by the useful signal. The vector of feature coefficients is fed into a feed-forward neural network that recovers the embedded information-bearing signal. The performance of the developed method is cross-validated through reconstruction of randomly-generated control parameter patterns. This method is applied to the reconstruction of speech signals, thus demonstrating its potential utility for secure communication applications. Our results are validated via numerical simulations.

Power Spectrum Analysis Based on VB Language

2014 ◽  
Vol 607 ◽  
pp. 727-730
Author(s):  
Jing Ling Zhou ◽  
Shu Qian Wu ◽  
Guo Qing Wu ◽  
Chun Shu Zhai ◽  
Mei Mei ◽  
...  
Keyword(s):  
Power Spectrum ◽  
Frequency Domain ◽  
Spectrum Analysis ◽  
Digital Signal ◽  
Rotating Machinery ◽  
Power Spectrum Analysis ◽  
Limited Data ◽  
Monitoring And Diagnosis ◽  
Useful Signal ◽  
Meaning Analysis

Power spectrum analysis is one of the important part of digital signal processing, various characteristics of the main signal in the frequency domain, is designed based on the limited data and extract the useful signal is submerged in the noise in the frequency domain. In this paper, the VB language to realize the power spectrum analysis can extract the useful signal was drowned in noise in frequency domain based on power spectrum, frequency structure and physical meaning analysis reflected the more obvious, monitoring and diagnosis in rotating machinery fault, power spectrum analysis is very wide.

CHAOS SYNCHRONIZATION IN THE PRESENCE OF NOISE

2011 ◽  
Vol 22 (12) ◽  
pp. 1409-1418 ◽  
Author(s):  
KUAN-YU CHEN ◽  
PI-CHENG TUNG ◽  
SHIH-LIN LIN ◽  
MONG-TAO TSAI
Keyword(s):  
Feedback Control ◽  
White Noise ◽  
Chaos Synchronization ◽  
State Feedback ◽  
Control Method ◽  
Type System ◽  
Chaotic Signal ◽  
State Feedback Control ◽  
Duffing System ◽  
Feedback Control Method

In this paper, we first develop a systematic procedure of state feedback control, based on a Lur'e-type system, to analyze the synchronization of two chaotic systems in the presence of random white noise. With the aid of the modified independent component analysis (ICA), the real chaotic signal can be extracted from a noisy source where the chaotic signal has been contaminated by random white noise. Hence, a new scheme has been proposed in this paper to combine the modified ICA design and the state feedback control method for achieving chaos synchronization. The synchronization time can be arbitrarily designed to guarantee stability, even if the system's output is corrupted by measuring noise. A Duffing system example is provided to show the effectiveness of the proposed scheme. The new scheme is first used for control systems with measurement noise which can replace the conventional Kalman filter.

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