The selection of an embedding scheme is an important step in the modeling and prediction of chaotic dynamical systems. Theoretical work in embedding selection abounds in the literature. However in neural network research, mostly compute intensive methods for embedding selection exist. In this paper, we propose a novel embedding selection scheme based on cluster analysis. A neural network implem...

This paper presents a simulation of a biological olfactory neural system with a KIII set, which is a high-dimensional chaotic neural network. The KIII set differs from conventional artificial neural networks by use of chaotic attractors for memory locations that are accessed by, chaotic trajectories. It was designed to simulate the patterns of action potentials and EEG waveforms observed in ele...

Siek, M. and Solomatine, D.P., 2011. Real-time data assimilation for chaotic storm surge model using NARX neural network. Journal of Coastal Research, SI 64 (Proceedings of the 11th International Coastal Symposium), 1189 – 1194. Szczecin, Poland, ISSN 0749-0208 This paper introduces a real-time data assimilation technique where Nonlinear AutoRegressive with eXogenous inputs (NARX) neural networ...

This paper presents a simulation of a biological olfactory neural system with a KIII set, which is a high-dimensional chaotic neural network. The KIII set differs from conventional artificial neural networks by use of chaotic attractors for memory locations that are accessed by, chaotic trajectories. It was designed to simulate the patterns of action potentials and EEG waveforms observed in ele...

Medical information digitization makes the medical information storage and extraction more convenient. Medical image information security and copyright protection is also gradually being taken seriously, and some medical image watermarking has been applied. According to the characteristics of three-dimensional medical images, this paper proposes a robust zero-watermarking algorithm for medical ...

Various approaches of incorporating chaos into artificial neural networks have recently been proposed, and used successfully to solve combinatorial optimisation problems. This paper investigates three such approaches: 1) Chen & Aihara's transiently chaotic neural network with chaotic simulated annealing, which has a gradually decaying negative selfcoupling term; 2) Wang & Smith's chaotic simula...

The optimum Multiuser Detection Problem in the presence of noise is a quadratic integer programming problem which has been shown to be NP-complete. In this paper, we propose a novel neural network based Multiuser Detector for Direct-Sequence Code Division Multiple Access system. The proposed detector combines the paradigms of chaotic neural networks and methods from Sequential Unconstrained Min...

Studies on spatio-temporal phenomena observed from coupled chaotic networks, namely coupled systems of many chaotic cells, are classified into two categories; namely discrete time systems and continuous time systems. For discrete time systems Kaneko’s coupled map lattice is the most interesting and well-studied system [l]. He discovered various nonlinear spatiotemporal chaotic phenomena such as...

This paper proposes a hybrid control scheme for the synchronization of two chaotic Duffing oscillator system, subject to uncertainties and external disturbances. The novelty of this scheme is that the Linear Quadratic Regulation (LQR) control, Sliding Mode (SM) control and Gaussian Radial basis Function Neural Network (GRBFNN) control are combined to chaos synchronization with respect to extern...

The goal of any cryptographic system is the exchange of information among the intended users without any leakage of information to others who may have unauthorized access to it. In 1976, Diffie and Hellmann found that a common secret key could be created over public channel accessible to any opponent. Since then many public key cryptography have been presented which are based on number theory a...