In this paper a method of classifying phonemes by combining a dynamical systems approach with subband decomposition of speech signals is presented. The ability of reconstructed phase spaces to effectively model sub-bands of phonemes in different phonological classes is demonstrated. Experiments performed over the TIMIT database show how well phonemes from different phonological classes can be r...

Time series analysis is a statistical analysis of sequences of data, where temporal correlations are to be characterized and interpreted. Depending on the hypothesis about the source of such correlations, different techniques can be employed. In this talk we focus on the reconstruction of vector valued auxillary spaces from the observed data, which serve as a state space for the dynamics of the...

In this paper, we present an approach for image reconstruction from local phase vectors in the monogenic scale space. The local phase vector contains not only the local phase but also the local orientation of the original signal, which enables the simultaneous estimation of the structural and geometric information. Consequently, the local phase vector preserves a lot of important information of...

Background/introduction MR temperature mapping based on the proton resonance frequency (PRF) shift is used in MR-guided focused ultrasound procedures for dosimetry and safety monitoring. While conventional PRF-shift thermometry is based on calculating a phase difference between two reconstructed MR images, Gaur et al [1,2] have recently described two algorithms that estimate temperatureinduced ...

Phase space reconstruction is investigated as a diagnostic tool for determining the structure of detected nonlinear processes in regression residuals. Empirical evidence supporting this approach is provided using simulations from an Ikeda mapping and the S&P 500. Results in the form of phase portraits (e.g., scatter plots of reconstructed dynamical systems) provide qualitative information to di...

The paper introduced a new method based on probability density function (PDF) and phase space diagram method for photoplethysmography (PPG) signal extracting. In the paper, PPG information was generated from human fingertips by smartphones. The pulse wave period was then separated and reconstructed into probability density function (PDF) by the phase space diagram algorithm. The difference betw...

INTRODUCTION Multivariate pattern classification and prediction offers an alternative to standard univariate analysis techniques, and has recently been applied in MR imaging using support vector machines (SVM) [1], and used to attain real-time feedback [2]. The standard approach has been to use reconstructed image magnitude data. However, additional information may be contained in the image pha...

We analyze seismic signals produced by explosion-quakes at Stromboli Volcano. We use standard nonlinear procedures to search a low-order effective dynamics. The dimension of the reconstructed phase space depends on the number of samples. Namely larger time lengths correspond to dynamical systems of different complexity. If we restrict the analysis to the signal associated directly to the source...

We formulate a phase-field, or diffuse-interface, model for the evolution of stepped surfaces under surface diffusion in the presence of distinct material parameters across nanoscale terraces. In the sharp-interface limit, our model reduces to a Burton-Cabrera-Frank (BCF)-type theory for the motion of noninteracting steps separating inhomogeneous terraces. This setting aims to capture features ...