Although isolated phoneme classification using features from time-domain phase space reconstruction has been investigated recently, the best representation of feature vectors for the discriminability over phoneme classes is still an open question. This paper applies Principal Component Analysis (PCA) to feature vectors from the reconstructed phase space. By using PCA projection, the basis of th...

Extreme cold events in natural gas demand are characterized by unusual dynamics that makes modeling the characteristics of the gas demand during extreme cold events a challenging task. This unusual dynamics is in the form of hysteresis, possibly due to human behavioral response to extreme weather conditions. To natural gas distribution utilities, extreme cold events represent high risk events g...

Safety [1] is an important property for nuclear power plants in order to obtain permission from government authorities for their operation and possible export of power plant construction technology. As the nuclear reactor protection system (RPS) makes decisions for emergent reactor shutdown, RPS software should be verified throughout the entire software development life cycle (SDLC). Recent com...

Background: Epilepsy is a brain disorder that changes the basin geometry of the oscillation of trajectories in the phase space. Nevertheless, recent studies on epilepsy often used the statistical characteristics of this space to diagnose epileptic seizures. Objectives: We evaluated changes caused by the seizures on the mentioned basin by focusing on phase space sorted by Poincaré sections. Ma...

A novel method for speech recognition is presented, utilizing nonlinear/chaotic signal processing techniques to extract timedomain based, reconstructed phase space derived features. By exploiting the theoretical results derived in nonlinear dynamics, a distinct signal processing space called a reconstructed phase space can be generated where salient features (the natural distribution and trajec...

Although isolated phoneme classification using features from time-domain phase space reconstruction has been investigated recently, the best representation of feature vectors for the discriminability over phoneme classes is still an open question. This paper applies Principal Component Analysis (PCA) to feature vectors from the reconstructed phase space. By using PCA projection, the basis of th...

We propose an algorithm for the detection of recurrence domains of complex dynamical systems from time series. Our approach exploits the characteristic checkerboard texture of recurrence domains exhibited in recurrence plots (RP). In phase space, RPs yield intersecting balls around sampling points that could be merged into cells of a phase space partition. We construct this partition by a rewri...