This paper aims at investigating a novel solution to the problem of defect detection from images, that can find applications in the design of robust quality control systems for the production of furniture, textile, integrated circuits, etc. The suggested solution focuses on detecting defects from their wavelet transformation and vector quantization related properties of the associated wavelet c...

This paper suggests the nonlinear parameter of self-similarity as a novel feature to be employed in wavelet packet based voice signal analysis. Two groups of normal and pathological voice signals have been decomposed using wavelet packets. Next, self similar characteristics of reconstructed signals in each node have been calculated. Consequently, discrimination ability of each node has been obt...

The prediction of outliers plays an important role in stock arbitrage and risk avoiding. While most of researches focused on detecting outliers and removing them to forecast time series data, few focused on forecasting the occurrence of outliers. The main goal of this work is to forecast outlier occurrence in Chinese stock market. Firstly, we detect abnormal points of two market indexes and six...

To accurately diagnose the mechanical failure of the fan, two diagnostic methods based on the wavelet packet energy feature and sample entropy feature are proposed. Vibration signals acquisition of 13 kinds of running states are achieved on the 4-73 No. 8D centrifugal fan test bench. The wavelet packet energy feature vector of each vibration signal is rapidly extracted through the wavelet packe...

Wavelet transforms and other multi-scale analysis functions have been used for compact signal and image representations in de-noising, compression and feature detection processing problems for about twenty years. Numerous research works have proven that space-frequency and spacescale expansions with this family of analysis functions provided a very efficient framework for signal or image data. ...

New rotationally invariant texture feature extraction methods are introduced that utilise the dual tree complex wavelet transform (DT-CWT). The complex wavelet transform is a new technique that uses a dual tree of wavelet filters to obtain the real and imaginary parts of complex wavelet coefficients. When applied in two dimensions the DT-CWT produces shift invariant orientated subbands. Both is...

In order to obtain the useful information from the raw data which contain the state data reflecting the structure condition and the noise, de-noising and feature extraction techniques based on Wavelet analysis were studied. An improved wavelet thresholding algorithm to eliminate the noise for vibration signals was proposed. Comparison analysis with other thresholding algorithms shows that the n...

At present, much more soft sensing have been widely used in industrial process control to improve the quality of product and assure safety in production. A novel method using Hilbert-Huang transform (HHT) combined with wavelet support vector machine (WSVM) is put forward. Firstly the method analyzes the intrinsic mode function (IMF) obtained after the empirical mode decomposition (EMD), then ex...