This article proposes an effective rotor fault diagnosis model of induction motor (IM) based on local mean decomposition (LMD) and wavelet packet (WPD)-based multilayer signal analysis hybrid genetic binary chicken swarm optimization (HGBCSO) for feature selection. Based the analysis, this technique can reduce dimension raw data, extract potential features, remove background noise. To compare v...

0167-8655/$ see front matter 2010 Elsevier B.V. A doi:10.1016/j.patrec.2010.04.016 * Corresponding author. Tel.: +86 10 62788613x810 E-mail addresses: [email protected] edu.cn (W. Xu), [email protected] (Q. Dai). The most widely used basis selection algorithm for adaptive wavelet packets is the optimal basis selection method, which first grows a full wavelet packet tree and then...

This paper explains a study conducted based on wavelet based transform techniques. We have used discrete wavelet transform and wavelet packet decomposition. The database is created by using Malayalam (one of the south Indian Languages) language spoken words. Daubechies type of mother wavelet was used for the experiment. Six hundred and forty samples are collected, for the experiment. The featur...

Eye state classification acts as a vital part of the biomedical sector, for instance, smart home device control, drowsy driving recognition, and so on. The modifications in cognitive levels can be reflected via transforming electroencephalogram (EEG) signals. deep learning (DL) models automated extract features often showcased improved outcomes over conventional model recognition processes. Thi...

In this paper, we propose a hybrid video coder using the wavelet packet transform and motion compensation. To reduce the computational complexity of the wavelet packet decomposition, a novel criterion based on the rate-distortion function is proposed. After the wavelet packet transform, the successive quantization scheme and the adaptive arithmetic coder are applied for lossy wavelet coe cient ...

Wavelet packet decomposition is used to investigate the time-varying characteristics of clinical EEG signals. On the basis of the nonstationary nature of clinical EEG rhythms, wavelet packet analysis is employed for designing filters with different frequency characteristics to detect 4 kinds of EEG rhythms. The coefficients of wavelet transformation corresponding to the rhythms are used to form...

Electroencephalography is frequently used for diagnostic evaluation of various brain-related disorders due to its excellent resolution, non-invasive nature and low cost. However, manual analysis EEG signals could be strenuous a time-consuming process experts. It requires long training time physicians develop expertise in it additionally experts have inter-rater agreement (IRA) among themselves....

Two main issues arise when working in the area of texture segmentation: the need to describe the texture accurately by capturing its underlying structure, and the need to perform analyses on the boundaries of textures. Herein, we tackle these problems within a consistent probabilistic framework. Starting from a probability distribution on the space of infinite images, we generate a distribution...

This paper describes a new design of a psychoacoustic model for audio coding following the model used in the standard MPEG-1 audio layer 3 using an appropriate wavelet packet decomposition of the speech/audio signal. The design of a psychoacoustic model is achieved by wavelet packet decomposition whose connections are selected in such a way that sub bands correspond to the best possible one to ...