Support Vector Machine is a very good solution to the classification problem of small sample, but when the input feature vector dimension is larger, the classifier has complex structure, long training time and degraded performance. In order to solve this problem, a feature extraction method based on wavelet coefficients cluster was put forward. All the wavelet coefficients was clustered, the en...

A new method based on principal component analysis (PCA) and artificial neural networks (ANN) is proposed for fault diagnosis of gearboxes. Firstly the six different base wavelets are considered, in which three are from real valued and other three from complex valued. Two wavelet selection criteria Maximum Energy to Shannon Entropy ratio and Maximum Relative Wavelet Energy are used and compared...

The present article describes a image segmentation technique using M -band wavelet packet frames features. Those wavelet features are evaluated and selected using an efficient neuro-fuzzy feature evaluation techniqu. Both the feature extraction and neuro-fuzzy feature evaluation processes are of unsupervised type. They do not require the knowledge of number and distribution of classes correspon...

The present paper describes a feature extraction method based on -band wavelet packet frames for segmenting remotely sensed images. These wavelet features are then evaluated and selected using an efficient neurofuzzy algorithm. Both the feature extraction and neurofuzzy feature evaluation methods are unsupervised, and they do not require the knowledge of the number and distribution of classes c...

Using wavelet transform to handle auto-mobile image with complex background for license localization, then preprocess license characters on vehicle licenses, and extracting the textural features of license characters in wavelet space, this paper proposed a novel algorithm for vehicle license localization and character recognition which is based on adaptive wavelet neural networks. Firstly, it u...

The effective noise reduction schemes in ultrasonic inspection have shown significant role for detection of flaws in materials. This paper presents the comparative result of noise reducing schemes based on Hilbert-Huang transform and Wavelet transform. The basic principle of HHT scheme includes two parts which are empirical mode decomposition (EMD) algorithm and a sum of intrinsic mode function...

In this work an automatic fault classification system is developed for bearing fault classification of three phase induction motor. The system uses the wavelet packet decomposition using ‘db8’ mother wavelet function for feature extraction from the vibration signal, recorded for various bearing fault conditions. The selection of best node of wavelet packet tree is performed by using best tree a...