A Research on the Characteristics of Mexican-hat Mother Wavelet Used in Optic Realization

The Mexican hat mother wavelet used in optic realization is analysed. Its characteristics on time frequency domain localization, accurate reconstruction condition, regularity order and orthonormality are discussed. The error concept for the Mexican hat wavelet that the non tensor product two dimensional form of mother wavelet is obtained from the turning of its one dimensional form is corrected. The reason is explained for that the Mexican hat mother wavelet can't be used in conventional discrete wavelet transform for image data compression,but when it is used in 2 D image wavelet transform realized by optic way, it features excellent energy localization.     

Optimal Design of Plane Cascades Based on Wavelet Theory

Based on the optimal control theory and Lagrange interpolation an optimal design model of plane cascades of 3D blade in an arbitrary surface of revolution is established. Using wavelet theory to solve the model, and lots of numerical results are obtained. The results show that the wavelet method is more effective than the conventional methods.     

VBR Coding Algorithm Based on Wavelet Transform

The introduction of the asynchronous transfer mode(ATM) concept has significantly influenced the coding theory.According to the characteristics of the ATM network,using the advantages based on the wavelet transform,how to apply the wavelet transform to plane separation and how to apply VBR coding to the layered data are discussed.The results of experiment are described respectively.     

Multi-yesolution Encoding of Medical Image in PACS

It is necessary to transmit and review medical images effectively in PACS (Picture Archive & Communication System, PACS) , and multi -resolution encoding can improve image compression efficiency. The progressive property of 2D image wavelet transform is studied, and a multi - resolution medical image encoding method is described. This encoding method means that, the lower frequency subimage in wavelet domain should be encoded prior to those higher frequency subimage. Also, in the medical image process of transmission and reviewing, the same order will be followed. The experiment has improved that the proposed method can speedup the medical image transmission and reviewing in PACS effectively.     

Realizing Continuous Wavelet Transform with linear Analog filter

A method of realizing wavelet transform with linear analog filter is proposed. It shows another new way of obtaining fast wavelet transform. It has also given out a procedure of constructing such a filter network and verified by the Mexican hat Wavelet.     

Two Channel Filter Banks and Wavelet Transform of Discrete Sequences

Multirate filter banks and wavelet transform are closely related theoretically and practically. This paper researches the wavelet transform of discrete-time sequences basing on dendriform filer banks in the signal processing field, analyses the theory and design method of two channel conjugate quadrature mirror filter banks and fast implement of discrete orthogonal wavelet transform and generation of orthogonal wavelets, and points out the internal relationship between them.     

Parameter optimized Morlet wavelet de noising method based on cross validation method

A new de noising method based on parameter optimized Morlet wavelet is put forward. The Morlet wavelet is chosen as the mother wavelet because its shape is similar to the mechanical shock signals. The mother Morlet wavelet is improved by adding two parameters which decide the shape of the mother wavelet in time domain. The added parameters and the appropriate scale parameter for the wavelet transformation are designed by the cross validation method. Finally, the useful components of the signal can be obtained by the improved Morlet wavelet de noising method. The gear fault diagnosis experimental result shows that the proposed method has a good de nosing performance and it is effective in fault feature extraction.     

Intellectual prediction of a permeability index for blast furnaces

The permeability index for blast furnaces is an important monitoring parameter in their operation. Proper trend prediction of the permeability index is important for good operation. Support vector machines (SVM) combined with wavelet analysis are adopted to build a forecasting model. Four historic values of a permeability index are analyzed by a wavelet analysis via seven levels. Based on eight wavelet analyzed values and combined with operating parameters, eight sub models are built using the least square support vector machines method. The prediction components are reconstructed to obtain a forecast. The details of modeling, validation and result analyses are presented.     

Detection Method for R-Wave of ECG Signal With Wavelet Transform

The R-wave of ECG signal represents the electrical activation of the ventricles, which initiates ventricle contraction, and the typical peak value singular signal, so the R-wave of ECG signal is localized precisely and analyzed accurately using the wavelet transform. The principium of the precise detection method for R-wave in ECG signal is researched. The special properties of Mexican hat wavelet in time-domain are analyzed, too. This wavelet has every order continuity, symmetry, exponential attenuation and one vanishing moment. For this reason, the mexican hat wavelet basis has the excellent localization and analyzing precision. Using the MIT/BIH (Massachusetts Institute of Technology / Boston's Beth Israel Hospital) Arrhythmia Database and the applications in clinic, the precise detection method can detect accurately and localize precisely to the R-wave in ECG signal in the serious noise signal. This method has the quite high locating precision (its error is not more than one sampling point and the points of the R-wave in ECG signal about 80 percent are localized precisely) and analyzing accuracy (no accumulative error). The real-time of the method is excellent, and the real-time detection to the R-wave of ECG signal can achieve using this method.     

Pulse Signal Analysis of Druggers with the Wavelet and Neural Network

The most significant difference between the human pulse signals collected from heroin druggers and healthy persons is at their amplitude waveforms as time functions. That is, the amplitude values and change rates of two types of signals, within a particular time range, appear different features. However, the partial components of the scaling and wavelet coefficients of the pulse signals obtained by using wavelet transform can reveal such key features. The pulse signals of 15 heroin druggers and 15 healthy persons are analyzed through using the muhiresolution analysis of wavelet transform. By using db2 orthogonal wavelet, every pulse signal is decomposed into three levels and the absolute values of the sixth component of scaling coefficients and the second component of the wavelet coefficients in the third level are combined to form a feature vector. A probabilistic neural network with good detection performance is successfully designed for automatically detecting 30 feature vectors. During the network design, 20 feature vectors are used as training samples. The remained 10 feature vectors are used as testing samples. Based on these steps, 15 heroin druggers and 15 healthy persons are all correctly identified. In other words, the detection rate arrives at 100%. druggers.     

Colour Hologram Making with Diffraction Colour Separation Method

Colour hologram making is an important part of research hologram display technology. Nowadays it has great influece upon improving the hologram display. Although different ways of producing colour hologram exist ,to get the better quality of colour hologram,a new way is found to produce it by diffraction colour separation method. The red,green and blue information code of a colour transparent film can be recorded on a black-and-white film with a three-colour grating. Monochromatic laser is used to reproduce at the same time the distributions of the recorded three-color colour information, and to record them on a holographic film to make a colour holographic image. The remarkable advantage is that there is no need to make three holographic images with information covered with colour selection, that the diffraction efficiency is high,and that the reproduced image is of clear and bright colour.     

A Virtual Wavelet Transform Analyzer for the Signal Analysis Based on the Direct Algorithm

A virtual wavelet transform analyzer for the signal analysis based on the direct algorithm is introduced so that the discrete wavelet transform and continuous wavelet transform is maken to signal in the direct algorithm. The authors first introduce the direct algorithm of the WT, which is numerical algorithm obtained from the original formula of the wavelet transform by directly numericalizing. Then some conclusions are drawn on the direct algorithm. The examples are the sampling principle and technology for the wavelets, the limitation of the scale range of the wavelets and the measures to solve the edge phenomenal in the direct algorithm of the discrete wavelet transform, and some conclusions in the direct algorithm of the continuous wavelet transform. The virtual wavelet transform analyzer for the signal analysis based on the direct algorithm explored based on these studies and combined with virtual instrument technique can make the discrete wavelet transform and continuous wavelet transform to signal with any basic wavelet. It can be applied in studying the property of any basic wavelet and learning the theory on the wavelet transform, and also in making some engineering signal analysis. In the end, the authors give some typical examples for the application of the virtual analyzer. These examples show that the analyzer can be applied in many situations.     

A New Method of Diesel Engine Fuel System Fault Diagnosis

A method of diesel engine fuel system fault diagnosis based on wavelet transform and fuzzy C-means clustering is presented. Five characteristic parameters of reflecting fault state are distilled with wavelet transform of pressure wave of high-pressure oil pipe of diesel. The theory and generic approach of fuzzy C-means clustering algorithm (FCM) is given, and the validity of evaluating fuzzy clustering making use of partition coefficient, partition entropy and parting coefficient is pointed out. Identification of fault mode can be completed utilizing standard fault character modes established by FCM algorithm, and calculating and comparing the similarity degree between this standard mode and sample. The arithmetic is applied to all kinds of typical faults diagnose in the diesel engine fuel system. Measuring results indicate that the precision of fault diagnosis is increased with the analysis of wavelet and FCM.     

Filter Design of Wavelet Transform for 2-D Image

The filter design is the key to 2-D image wavelet transform. Based on the studying of image properties and 1-D wavelet theory,the authors describe a parasymmetry boundary extension method and realize 2-D discrete wavelet transform by means of 1-D wavelet transform according to correlation of adjacent pixels. Also,it is proved that the discrete wavelet transform of inverse data stream in row and the sign of discrete detail signal will be inversed,and that a filter of wavelet transform based on symmetry of bi_orthogonal filter is constructed. The test has proved the fine reconstruction and perfect SNR.     

Systems Analysis Based on Continuous Wavelet Transform

The linear time invariant vibration system is analyzed by Continuous Wavelet Transform(CWT),the relationship of wavelet transform of output signal with the pulse response of system and input signal is put forward.As an exapmle,the wavelet transform of the output signal of system with single degree of freedom is calculated and compared with the direct wavelet transform result of the actual output signal,it shows that the two results are in complete agreement.     

Effective Coefficient Threshold for Complex Wavelet Transform

This paper constructs complex wavelet which used for suppressing white noise in PD,and then analyses some disadvantages of several existing wavelet threshold and presents a method of Effective Wavelet Coefficient(EWC) according to the characteristic of modulus maximum of PD signals.Then it is compared with maximin theory threshold selection and Stein unbiased risk estimate theory threshold selection.The findings suggest that the method of EWC is adaptive,and it can suppress noise completely with small distortion of PD signal.     

Application of Wavelet & Multi-Resolution Analysis to Detection of the Time of PN Code Acquisition

In the field of CDMA system, DS-SS technology has been used widely. Thereby, a great deal research on acquisition method of PN code is based on DS-SS. In the traditional way, the power detection method of judgment is used widely. Based on the characteristic of PN code acquired signal (namely BPSK signal or QPSK signal) and characteristic of un acquired signal (namely white Gaussian noise), this paper introduces the wavelet detection method of PN code acquisition time. Meanwhile, the performance of wavelet threshold is also studied. In the end, the statistics of parameters in this detection method is made. The result indicates that the wavelet & multi resolution has practical value in the signal processing.     

Choosing Method of Wavelet Neuron Based on ECG Data Compression

The paper discusses a wavelet network for the ECG data compression and proposes the method for choosing its wavelet neuron.According to the spectrum range of the ECG data,we decide the time-frequency field of ECG.And the time-frequency field of wavelet is also determined by the spectrum range of it.The wavelet neuron is fixed preliminarily by the first two steps.Then the preliminary wavelet neuron is screened by using OLS algorithm.We choose Morlet as the mother wavelet,and use the ECG signal to validate by the method.The result demonstrates that the number of Morlet whose spectrums locate at the ECG's is up to 152.But after screening by the OLS algorithm,it reduces sharply.This method can make the size of the wavelet network driving to optimum and also reduce the training time of the wavelet network sharply.     

Quantitative Phase Analysis of Weight Factors of X-ray Intensity

A new method is applied in this article to the quantitative phase analysis for weight factors of X-ray diffraction intensity. This method overcame the defect of traditional sampling and quantitative analysis method which only single out one plane web diffraction peaks for quantitative analysis from the phases of the sample to be tested. The method applied in this article is that the sample processing and taking measurements to the samples only once, then determining the weight factors by the intensity corresponding to n X-ray diffraction peaks from the phases of the sample to be tested. Thus we can get the relative percentage of each phase in the sample.     

Fetal electrocardiogram extraction based on radial basis function neural networks

A novel method for extracting fetal electrocardiogram (FECG) from the abdominal composite signal of a pregnant woman is proposed. The maternal component in the abdominal electrocardiogram (ECG) signal is a nonlinearly transformed version of the mother's ECG (MECG). This nonlinear relationship was identified using radial basis function (RBF) neural networks. The FECG is extracted by subtracting the nonlinearly transformed version of the MECG from the abdominal ECG signal. The baseline shift and noise in the FECG are suppressed by wavelet packet denoising technique. Experimental results obtained from the actual ECG signals demonstrate the effectiveness of the proposed method in extracting FECG even when it is totally embedded within the maternal(QRS) complex.