63,828 research outputs found
Neural Control of Chaos and Aplications
Signal processing is an important topic in technological research today. In the areas of nonlinear
dynamics search, the endeavor to control or order chaos is an issue that has received increasing attention over
the last few years. Increasing interest in neural networks composed of simple processing elements (neurons) has
led to widespread use of such networks to control dynamic systems learning. This paper presents
backpropagation-based neural network architecture that can be used as a controller to stabilize unsteady periodic
orbits. It also presents a neural network-based method for transferring the dynamics among attractors, leading to
more efficient system control. The procedure can be applied to every point of the basin, no matter how far away
from the attractor they are. Finally, this paper shows how two mixed chaotic signals can be controlled using a
backpropagation neural network as a filter to separate and control both signals at the same time. The neural
network provides more effective control, overcoming the problems that arise with control feedback methods.
Control is more effective because it can be applied to the system at any point, even if it is moving away from the
target state, which prevents waiting times. Also control can be applied even if there is little information about the
system and remains stable longer even in the presence of random dynamic noise
Magic number 7 2 in networks of threshold dynamics
Information processing by random feed-forward networks consisting of units
with sigmoidal input-output response is studied by focusing on the dependence
of its outputs on the number of parallel paths M. It is found that the system
leads to a combination of on/off outputs when , while for , chaotic dynamics arises, resulting in a continuous distribution of
outputs. This universality of the critical number is explained by
combinatorial explosion, i.e., dominance of factorial over exponential
increase. Relevance of the result to the psychological magic number
is briefly discussed.Comment: 6 pages, 5 figure
Synchronization of spatiotemporal semiconductor lasers and its application in color image encryption
Optical chaos is a topic of current research characterized by
high-dimensional nonlinearity which is attributed to the delay-induced
dynamics, high bandwidth and easy modular implementation of optical feedback.
In light of these facts, which adds enough confusion and diffusion properties
for secure communications, we explore the synchronization phenomena in
spatiotemporal semiconductor laser systems. The novel system is used in a
two-phase colored image encryption process. The high-dimensional chaotic
attractor generated by the system produces a completely randomized chaotic time
series, which is ideal in the secure encoding of messages. The scheme thus
illustrated is a two-phase encryption method, which provides sufficiently high
confusion and diffusion properties of chaotic cryptosystem employed with unique
data sets of processed chaotic sequences. In this novel method of cryptography,
the chaotic phase masks are represented as images using the chaotic sequences
as the elements of the image. The scheme drastically permutes the positions of
the picture elements. The next additional layer of security further alters the
statistical information of the original image to a great extent along the
three-color planes. The intermediate results during encryption demonstrate the
infeasibility for an unauthorized user to decipher the cipher image. Exhaustive
statistical tests conducted validate that the scheme is robust against noise
and resistant to common attacks due to the double shield of encryption and the
infinite dimensionality of the relevant system of partial differential
equations.Comment: 20 pages, 11 figures; Article in press, Optics Communications (2011
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