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By considering generalized synchronizable chaotic systems, the drive-auxiliary system variables are combined suitably using encryption key functions to obtain a compound chaotic signal. An appropriate feedback loop is constructed in the…

chao-dyn · Physics 2009-10-30 K. Murali , M. Lakshmanan

A new approach is proposed to the integrated analysis of the time structure of synchronization of multidimensional chaotic systems. The method allows one to diagnose and quantitatively evaluate the intermittency characteristics during…

Chaotic Dynamics · Physics 2015-07-02 A. V. Makarenko

In compressed sensing one measures sparse signals directly in a compressed form via a linear transform and then reconstructs the original signal. However, it is often the case that the linear transform itself is known only approximately, a…

Information Theory · Computer Science 2013-11-13 Florent Krzakala , Marc Mézard , Lenka Zdeborová

In many areas of imaging science, it is difficult to measure the phase of linear measurements. As such, one often wishes to reconstruct a signal from intensity measurements, that is, perform phase retrieval. In several applications the…

Information Theory · Computer Science 2015-06-16 Afonso S. Bandeira , Dustin G. Mixon

Sparse recovery can recover sparse signals from a set of underdetermined linear measurements. Motivated by the need to monitor large-scale networks from a limited number of measurements, this paper addresses the problem of recovering sparse…

Information Theory · Computer Science 2015-03-20 Meng Wang , Weiyu Xu , Enrique Mallada , Ao Tang

This article extends the concept of compressed sensing to signals that are not sparse in an orthonormal basis but rather in a redundant dictionary. It is shown that a matrix, which is a composition of a random matrix of certain type and a…

Probability · Mathematics 2010-11-10 Holger Rauhut , Karin Schnass , Pierre Vandergheynst

Sparse representations have emerged as a powerful tool in signal and information processing, culminated by the success of new acquisition and processing techniques such as Compressed Sensing (CS). Fusion frames are very rich new signal…

Information Theory · Computer Science 2011-06-20 Petros T. Boufounos , Gitta Kutyniok , Holger Rauhut

Recurrence analysis is a well settled method allowing to discern chaos from order, and determinism from noise. We apply this tool to study time series representing geodesic and inspiraling motion of a test particle in a deformed Kerr…

General Relativity and Quantum Cosmology · Physics 2017-10-24 Georgios Lukes-Gerakopoulos , Ondřej Kopáček

We consider the recovery of sparse signals subject to sparse interference, as introduced in Studer et al., IEEE Trans. IT, 2012. We present novel probabilistic recovery guarantees for this framework, covering varying degrees of knowledge of…

Information Theory · Computer Science 2012-09-27 Graeme Pope , Annina Bracher , Christoph Studer

Recurrence entropy $(\cal S)$ is a novel time series complexity quantifier based on recurrence microstates. Here we show that $\mathsf{max}(\cal S)$ is a \textit{parameter-free} quantifier of time correlation of stochastic and chaotic…

Data Analysis, Statistics and Probability · Physics 2020-02-19 Sergio Roberto Lopes , Thiago de Lima Prado , Gilberto Corso , Gustavo Zampier dos Santos Lima , Jurgen Kurths

We report a systematic investigation of universal quantum chaotic signatures in the transverse field Ising model on an Erd\H{o}s-R\'enyi network. This is achieved by studying local spectral measures such as the level spacing and the level…

Disordered Systems and Neural Networks · Physics 2025-02-18 András Grabarits , Kasturi Ranjan Swain , Mahsa Seyed Heydari , Pranav Chandarana , Fernando J. Gómez-Ruiz , Adolfo del Campo

This article is talking about the study constructive method of structural identification systems with chaotic dynamics. It is shown that the reconstructed attractors are a source of information not only about the dynamics but also on the…

Dynamical Systems · Mathematics 2014-03-04 Evgeny Nikulchev , Oleg Kozlov

This paper presents an adaptive and intelligent sparse model for digital image sampling and recovery. In the proposed sampler, we adaptively determine the number of required samples for retrieving image based on space-frequency-gradient…

Computer Vision and Pattern Recognition · Computer Science 2017-11-27 Ali Taimori , Farokh Marvasti

The linear response of synchronized time-delayed chaotic systems to small external perturbations, i.e., the phenomenon of chaos pass filter, is investigated for iterated maps. The distribution of distances, i.e., the deviations between two…

Chaotic Dynamics · Physics 2015-06-12 Steffen Zeeb , Johannes Kestler , Ido Kanter , Wolfgang Kinzel

We study the problem of recovering the underlining sparse signals from clean or noisy phaseless measurements. Due to the sparse prior of signals, we adopt an L0regularized variational model to ensure only a small number of nonzero elements…

Optimization and Control · Mathematics 2016-12-09 Yuping Duan , Chunlin Wu , Zhi-Feng Pang , Huibin Chang

The success of the compressed sensing paradigm has shown that a substantial reduction in sampling and storage complexity can be achieved in certain linear and non-adaptive estimation problems. It is therefore an advisable strategy for…

Information Theory · Computer Science 2014-08-27 Peter Jung , Philipp Walk

In this work we describe a simple method of encoding information at real time in the inter-spike intervals of a homoclinic chaotic system. This has been experimentally tested by means of an instantaneous synchronization between the laser…

Chaotic Dynamics · Physics 2007-05-23 I. P. Marino , E. Allaria , R. Meucci , S. Boccaletti , F. T. Arecchi

We study the compressed sensing reconstruction problem for a broad class of random, band-diagonal sensing matrices. This construction is inspired by the idea of spatial coupling in coding theory. As demonstrated heuristically and…

Information Theory · Computer Science 2015-03-19 David L. Donoho , Adel Javanmard , Andrea Montanari

Fusion frames are collection of subspaces which provide a redundant representation of signal spaces. They generalize classical frames by replacing frame vectors with frame subspaces. This paper considers the sparse recovery of a signal from…

Information Theory · Computer Science 2018-04-09 Ulaş Ayaz

A method for the quantitative analysis of the degree and parameters of synchronization of the chaotic oscillations in two coupled oscillators is proposed, which makes it possible to reveal a change in the structure of attractors. The…

Chaotic Dynamics · Physics 2011-08-30 A. V. Makarenko
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