Signal Processing Using Chaotic Dynamics

Reconstructed Dynamics and Chaotic Signal Modeling

A nonlinear AR model is derived from the reconstructed dynamics of a signal. The underlying system is assumed to be nonlinear, autonomous, and determinstic. In this formulation, the output error scheme is shown to be more suitable than the equation error scheme in training a network as a NAR model of the signal. A method to incorporate the information of the dynamical invariants in signal model...

P81: Detection of Epileptic Seizures Using EEG Signal Processing

Epilepsy is the most common brain diseases that cause many problems in the daily life of the patient. In most attempts to automatic detection, the attack used an EEG. In this paper, The complete data set consists of five sets recorded from normal and epileptic patients. Each set containing 100 single-channel EEG segments. Here we used first and last sets (A and E). Set A consisted of segments r...

Chaotic Dynamics Using Electrical

Signal Representation and Signal Processing Using Operators Signal Representation and Signal Processing Using Operators

The topic of this report is signal representation in the context of hierarchical image processing. An overview of hierarchical processing systems is included as well as a presentation of various approaches to signal representation, feature representation and feature extraction. It is claimed that image hierarchies based on feature extraction, so called feature hierarchies, demand a signal repre...

Digital Information Transmission Using Discrete Chaotic Signal

In this work the authors thoroughly investigated a digital information transmission system using discrete chaotic signal over cable. As an example in their work the authors consider the non-autonomous 2nd order non-linear oscillator system presented in Tamaševičious, Čenys, Mycolaitis, and Namajunas (1998) which is particularly suitable for digital communications and present the experimental re...