نتایج جستجو برای: wavelet packet decomposition wpd
تعداد نتایج: 172818 فیلتر نتایج به سال:
Extended Abstract Wavelet packets 14] represent a generalization of the method of multires-olution decomposition and comprise the entire family of subband coded (tree) decompositions 11, 15]. Whereas in the wavelet case the decomposition is applied recursively to the coarse scale approximations (leading to the well known (pyramidal) wavelet decomposition tree), in the wavelet packet decompositi...
In this era, big data applications including biomedical are becoming attractive as the data generation and storage is increased in the last years. The big data processing to extract knowledge becomes challenging since the data mining techniques are not adapted to the new requirements. In this study, we analyse the EEG signals for epileptic seizure detection in the big data scenario using Rotati...
Corresponding author. Abstract In this paper, we present an efficient model for reliable fault diagnosis of the induction motor. This is now a growing demand for high classification accuracy in fault diagnosis. However, the system performance is highly dependable on superior feature analysis. But, it’s still crucial and computational complex to select discernment features, thus, a new genetic a...
This paper presents a rolling bearing fault diagnosis approach by integrating wavelet packet decomposition (WPD) with multi-scale permutation entropy (MPE). The approach uses MPE values of the sub-frequency band signals to identify faults appearing in rolling bearings. Specifically, vibration signals measured from a rolling bearing test system with different defect conditions are decomposed int...
The importance of speech command recognition in a human-machine interaction system is increased recent years. In this study, we propose deep neural network-based for acoustic and throat recognition. We apply preprocessed pipeline to create the input learning model. Firstly, commands are decomposed into components using well-known signal decomposition techniques. Mel-frequency cepstral coefficie...
In order to analyze the nature of electrical demand series in deregulated electricity markets, various forecasting tools have been used. All these models developed improve accuracy reliability model. Therefore, a Wavelet Packet Decomposition (WPD) was implemented decompose into subseries. Each subseries has forecasted individually with help features that series, and were chosen on basis mutual ...
We discuss features extracted from a wavelet packet decomposition for image classification. Statistical features computed from wavelet packet coefficients are compared to structural features which are derived from an image dependent wavelet packet decomposition subband structure. Primary application area is the classification of pit pattern structures in zoom-endoscopic colon imagery, while res...
This paper explains a study conducted based on wavelet packet transform techniques. In this paper the key idea underlying the construction of wavelet packet analysis (WPA) with various wavelet basis sets is elaborated. Since wavelet packet decomposition can provide more precise frequency resolution than wavelet decomposition the implementation of one dimensional wavelet packet transform and the...
Wavelet/wavelet packet decomposition has become a very useful tool in describing nonstationary processes. Important examples of nonstationary processes encountered in practice are cyclostationary processes or almost-cyclostationary processes. In this paper, we study the statistical properties of the wavelet packet decomposition of a large class of nonstationary processes, including in particula...
In image compression, the wavelet transformation is a state-of-the-art component. Recently, wavelet packet decomposition has received quite an interest. A popular approach for wavelet packet decomposition is the near-best-basis algorithm using nonadditive cost functions. In contrast to additive cost functions, the wavelet packet decomposition of the near-best-basis algorithm is only suboptimal....
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