Dynamical Behavior of Three-Order Cellular Neural Network with Application in Image Secure Communication

2007 ◽  
Author(s):  
Fei Xiang ◽  
Huijuan Xiao ◽  
Shuisheng Qiu ◽  
Chengliang Deng
Keyword(s):  
Neural Network ◽  
Secure Communication ◽  
Dynamical Behavior ◽  
Cellular Neural Network

A SC–CNN-BASED CHAOTIC MASKING SYSTEM WITH FEEDBACK

2004 ◽  
Vol 14 (01) ◽  
pp. 245-256 ◽  
Author(s):  
RECAI KILIÇ ◽  
MUSTAFA ALÇI ◽  
ENIS GÜNAY
Keyword(s):  
Neural Network ◽  
Secure Communication ◽  
Spectral Characteristics ◽  
Cellular Neural Network ◽  
Simulation Experiments ◽  
Information Signal ◽  
Wide Range ◽  
Feedback Algorithm ◽  
Feedback Connections ◽  
Secure Transmission

A secure transmission application of the State Controlled Cellular Neural Network (SC–CNN)-based circuit is presented. Since the SC–CNN-based circuit has feedback connections between the cells, it is potentially very suitable for realizing a chaotic masking system with feedback algorithm. So, we have constructed a chaotic masking system with feedback using the SC–CNN-based circuit. PSpice simulation experiments verify that the proposed SC–CNN-based secure communication system exhibits a good performance for a wide range of amplitude and spectral characteristics of the information signal.

Image Encryption Scheme Based on Dual Hyper-Chaotic Recurrent Neural Networks

2011 ◽  
Vol 474-476 ◽  
pp. 599-604
Author(s):  
En Zeng Dong ◽  
Yang Du ◽  
Cheng Cheng Li ◽  
Zai Ping Chen
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Image Encryption ◽  
Recurrent Neural Networks ◽  
Dynamical Behavior ◽  
Security Analysis ◽  
Hopfield Neural Network ◽  
Cellular Neural Network ◽  
Encryption Scheme ◽  
Secret Key

Based on two hyper-chaotic recurrent neural networks, a new image encryption scheme is presented in this paper. In the encryption scheme, the shuffling matrix is generated by using a Hopfield neural network, which is used to shuffle the pixels location; the diffusing matrix is generated by using a cellular neural network, which is used to diffuse the pixels grey value by OXRoperation. Finally, through numerical simulation and security analysis, the effectiveness of the encryption scheme is verified. Duo to the complex dynamical behavior of the hyper-chaotic systems, the encryption scheme has the advantage of large secret key space and high security, and can resist brute-force attacks and statistical attacks effectively.

Optimizing Time-multiplexing Raster Cellular Neural Network simulator using genetic algorithms with RK8(6)

2011 ◽  
Vol 3 (6) ◽  
pp. 87-90
Author(s):  
O. H. Abdelwahed O. H. Abdelwahed ◽  
◽  
M. El-Sayed Wahed ◽  
O. Mohamed Eldaken
Keyword(s):  
Neural Network ◽  
Genetic Algorithms ◽  
Cellular Neural Network ◽  
Network Simulator

scholarly journals Dynamical Behavior in a Four-Dimensional Neural Network Model with Delay

2012 ◽  
Vol 2012 ◽  
pp. 1-11
Author(s):  
Changjin Xu ◽  
Peiluan Li
Keyword(s):  
Neural Network ◽  
Hopf Bifurcation ◽  
Network Model ◽  
Neural Network Model ◽  
Center Manifold ◽  
Dynamical Behavior ◽  
Normal Form Theory ◽  
Form Theory ◽  
Explicit Formulae ◽  
Delay Differential

A four-dimensional neural network model with delay is investigated. With the help of the theory of delay differential equation and Hopf bifurcation, the conditions of the equilibrium undergoing Hopf bifurcation are worked out by choosing the delay as parameter. Applying the normal form theory and the center manifold argument, we derive the explicit formulae for determining the properties of the bifurcating periodic solutions. Numerical simulations are performed to illustrate the analytical results.

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