640 research outputs found
Oscillons: an encounter with dynamical chaos in 1953?
We present evidences that Ben F. Laposky (1914-2000) might have been the
first person who created a family of nonlinear analog circuits that allowed him
to observe chaotic attractors and other trademarks of nonlinear science as
early as 1953.Comment: accepted to Chao
Constructing multiwing attractors from a robust chaotic system with non-hyperbolic equilibrium points
We investigate a three-dimensional (3D) robust chaotic system which only holds two nonhyperbolic equilibrium points, and finds the complex dynamical behaviour of position modulation beyond amplitude modulation. To extend the application of this chaotic system, we initiate
a novel methodology to construct multiwing chaotic attractors by modifying the position and amplitude parameters. Moreover, the signal amplitude, range and distance of the generated multiwings can be easily adjusted by using the control parameters, which enable us to enhance the potential application in chaotic cryptography and secure communication. The effectiveness of the theoretical analyses is confirmed by numerical simulations. Particularly, the multiwing
attractor is physically realized by using DSP (digital signal processor) chip
New artificial neural network design for Chua chaotic system prediction using FPGA hardware co-simulation
This study aims to design a new architecture of the artificial neural networks (ANNs) using the Xilinx system generator (XSG) and its hardware co-simulation equivalent model using field programmable gate array (FPGA) to predict the behavior of Chua’s chaotic system and use it in hiding information. The work proposed consists of two main sections. In the first section, MATLAB R2016a was used to build a 3×4×3 feed forward neural network (FFNN). The training results demonstrate that FFNN training in the Bayesian regulation algorithm is sufficiently accurate to directly implement. The second section demonstrates the hardware implementation of the network with the XSG on the Xilinx artix7 xc7a100t-1csg324 chip. Finally, the message was first encrypted using a dynamic Chua system and then decrypted using ANN’s chaotic dynamics. ANN models were developed to implement hardware in the FPGA system using the IEEE 754 Single precision floating-point format. The ANN design method illustrated can be extended to other chaotic systems in general
Identification of single- and double-well coherence-incoherence patterns by the binary distance matrix
The study of chimera states or, more generally, coherence-incoherence
patterns has led to the development of several tools for their identification
and characterization. In this work, we extend the eigenvalue decomposition
method to distinguish between single-well and double-well patterns. By applying
our method, we are able to identify the following four types of dynamical
patterns in a ring of nonlocally coupled Chua circuits and nonlocally coupled
cubic maps: single-well cluster, single-well coherence-incoherence pattern,
double-well cluster, and double-well coherence-incoherence. In a ring-star
network of Chua circuits, we investigate the influence of adding a central node
on the spatio-temporal patterns. Our results show that increasing the coupling
with the central node favors the occurrence of single-well
coherence-incoherence states. We observe that the boundaries of the attraction
basins resemble fractal and riddled structure
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