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New chaos-based communication schemes for transmission of analog and digital information are suggested. The carrier signal is produced by chaotic generator having well-defined oscillation phases at least on short time intervals. For data…

Chaotic Dynamics · Physics 2017-08-10 Olga B. Isaeva , Alexey Yu. Jalnine , Sergey P. Kuznetsov

The invariance of the Lyapunov exponent of a chaotic signal as it propagates along a wireless transmission channel provides a theoretical base for the application of chaos in wireless communication. In additive Gaussian channel, the chaotic…

Signal Processing · Electrical Eng. & Systems 2022-04-21 Hai-Peng Ren , Wu-Yun Zheng , Celso Grebogi

Compressed sensing is designed to measure sparse signals directly in a compressed form. However, most signals of interest are only "approximately sparse", i.e. even though the signal contains only a small fraction of relevant (large)…

Information Theory · Computer Science 2013-04-04 Jean Barbier , Florent Krzakala , Marc Mézard , Lenka Zdeborová

A traditional assumption underlying most data converters is that the signal should be sampled at a rate exceeding twice the highest frequency. This statement is based on a worst-case scenario in which the signal occupies the entire…

Information Theory · Computer Science 2015-05-13 Yonina C. Eldar

We report on an ultra-high-frequency (> 1 GHz), piecewise-linear chaotic system designed from low-cost, commercially available electronic components. The system is composed of two electronic time-delayed feedback loops: A primary analog…

Chaotic Dynamics · Physics 2015-06-11 Seth D. Cohen , Damien Rontani , Daniel J. Gauthier

The synchronization of coupled chaotic systems represents a fundamental example of self organization and collective behavior. This well-studied phenomenon is classically characterized in terms of macroscopic parameters, such as Lyapunov…

Xampling generalizes compressed sensing (CS) to reduced-rate sampling of analog signals. A unified framework is introduced for low rate sampling and processing of signals lying in a union of subspaces. Xampling consists of two main blocks:…

Information Theory · Computer Science 2015-03-19 Moshe Mishali , Yonina C. Eldar

In this paper, synchronization of fractional order Coullet system with precise and also unknown parameters are studied. The proposed method which is based on the adaptive backstepping, has been developed to synchronize two chaotic systems…

Chaotic Dynamics · Physics 2012-06-12 T. M. Shahiri , A. Ranjbar , R. Ghaderi , M. Karami , S. H. Hosseinnia

Adaptive control is a control method that has an adaptation mechanism that reacts to model uncertainties. The control method is used to realized synchronization of a new chaotic system in a unidirectional master-slave topology. The master…

Signal Processing · Electrical Eng. & Systems 2019-12-04 Christian Nwachioma

We show that scaling arguments are very useful to analyze the dynamics of periodically modulated noisy systems. Information about the behavior of the relevant quantities, such as the signal-to-noise ratio, upon variations of the noise…

Statistical Mechanics · Physics 2016-08-15 J. M. G. Vilar , J. M. Rubí

Spatially extended dynamical systems, namely coupled map lattices, driven by additive spatio-temporal noise are shown to exhibit stochastic synchronization. In analogy with low-dymensional systems, synchronization can be achieved only if…

Chaotic Dynamics · Physics 2009-10-31 Lucia Baroni , Roberto Livi , Alessandro Torcini

In this paper is proposed a novel incremental iterative Gauss-Newton-Markov-Kalman filter method for state estimation of dynamic models given noisy measurements. The mathematical formulation of the proposed filter is based on the…

Optimization and Control · Mathematics 2019-09-17 Bojana Rosic

Compressive sensing (CS) is a technique for estimating a sparse signal from the random measurements and the measurement matrix. Traditional sparse signal recovery methods have seriously degeneration with the measurement matrix uncertainty…

Information Theory · Computer Science 2011-06-21 Yipeng Liu , Qun Wan , Fei Wen , Jia Xu , Yingning Peng

We show that two initially weakly coupled chaotic systems can achieve self-organized synchronization by adaptively reducing their speed and/or enhancing the coupling strength. Explicit adaptive algorithms for speed-reduction and…

Statistical Mechanics · Physics 2009-11-07 Xiao Fan Wang

In this paper, we address the problem of stabilization in continuous time linear dynamical systems using state feedback when compressive sampling techniques are used for state measurement and reconstruction. In [5], we had introduced the…

Optimization and Control · Mathematics 2011-10-18 Kang Kang , Sourabh Bhattacharya , Tamer Basar

Noiseless compressive sensing is a protocol that enables undersampling and later recovery of a signal without loss of information. This compression is possible because the signal is usually sufficiently sparse in a given basis. Currently,…

Information Theory · Computer Science 2024-07-22 D. Barbier , C Lucibello , L. Saglietti , F. Krzakala , L. Zdeborova

Phase modulation is a commonly used modulation mode in digital communication, which usually brings phase sparsity to digital signals. It is naturally to connect the sparsity with the newly emerged theory of compressed sensing (CS), which…

Information Theory · Computer Science 2015-01-05 Zhengli Xing , Jie Zhou , Jiangfeng Ye , Jun Yan , Lin Zou , Qun Wan

In this paper, adaptive non-uniform compressive sampling (ANCS) of time-varying signals, which are sparse in a proper basis, is introduced. ANCS employs the measurements of previous time steps to distribute the sensing energy among…

Applications · Statistics 2017-03-10 Alireza Zaeemzadeh , Mohsen Joneidi , Nazanin Rahnavard

Limit possibilities of observer-based synchronization systems under information constraints (limited information capacity of the coupling channel) are evaluated. We give theoretical analysis for multi-dimensional drive-response systems…

Chaotic Dynamics · Physics 2009-11-11 Alexander L. Fradkov , Boris Andrievsky , Robin J. Evans

This article considers recovery of signals that are sparse or approximately sparse in terms of a (possibly) highly overcomplete and coherent tight frame from undersampled data corrupted with additive noise. We show that the properly…

Information Theory · Computer Science 2013-09-10 Junhong Lin , Song Li