Based on phase space reconstruction and fractal dynamics in nonlinear dynamics, a method is proposed to extract and analyze the dynamics of the rotating stall in the impeller of centrifugal compressor, and some numerical examples are given to verify the results as well. First, the rotating stall of an existing low speed centrifugal compressor (LSCC) is numerically simulated, and the time series...

An approach is presented in this paper for vowel classification by analyzing the dynamics of speech production in a reconstructed phase space. The proposed approach has the ability of capturing nonlinearities that may exist in speech production. Global flow reconstruction is used to generate a quantitative description of the structure and trajectory of vowel attractors in a reconstructed phase ...

Time series forecasting by fuzzy inference systems based on optimal non-uniform attractor embedding in the multidimensional delay phase space is analyzed in this paper. A near-optimal set of time lags is identified by evolutionary algorithms after the optimal dimension of the reconstructed phase space is determined by the FNN (false nearest neighbors) algorithm. The fitness function is construc...

This paper presents a study of the attractor variation in the reconstructed phase spaces of isolated phonemes. The approach is based on recent work in timedomain signal classification using dynamical signal models, whereby a statistical distribution model is obtained from the phase space and used for maximum likelihood classification. Two sets of experiments are presented in this paper. The fir...

The longitudinal phase space distribution of electron beam plays critical role in ultra-short electron bunch production, coherent radiation, free electron laser (FEL) and many other applications. Photocathode RF gun is capable of controlling not only the transverse emittance of electron beam, but also longitudinal emittance. The longitudinal phase space distribution of photoelectron beam was in...

Empirical Mode Decomposition (EMD), due to its adaptive decomposition property for the non-linear and non-stationary signals, has been widely used in vibration analyses for rotating machinery. However, EMD suffers from mode mixing, which is difficult to extract features independently. Although the improved EMD, well known as the ensemble EMD (EEMD), has been proposed, mode mixing is alleviated ...

proposed that is comparable to the traditional FE methods used in automatic speech recognition systems. Unlike the conventional spectral-based FE methods, the proposed method evaluates the similarities between an embedded speech signal and a set of predefined speech attractor models in the reconstructed phase space (RPS) domain. In the first step, a set of Gaussian mixture models is trained to ...

This paper presents a method of classifying phonemes by combining a dynamical system approach with sub-band decomposition of speech signals. The ability of reconstructed phase spaces to effectively model sub-bands of phonemes in different phonological classes is studied. The current results are taken from a small speaker-independent set. For the final version of this paper, the entire TIMIT dat...