wavelet

The continuous wavelet transform (CWT) has been used to measure harmonics due to its excellent time-frequency character.

Wavelet transform has been used for pitch detection in real time . and two algorithms (multi-scale and single scale) are compared.

The result shows that this kind of representation used to obtain the wavelet filters directly is effective in time domain.

This kernel is proposed in this paper and is proved to be able to improve training speed and precision of the wavelet SVM.

Chirplet transform is the general form of Fourier transform, short-time Fourier transform and Wavelet transform.

The improved gradient descent algorithm has been used to train the wavelet neural network.

The results show that this method can fuse geometry model efficiently and the effect by EMD is better than that of wavelet.

Wavelet believe that such a random girl, and he certainly is not one person had sexual relations.

The experimental results show that this algorithm is superior to the zero tree wavelet image compression algorithm.

The emergence of wavelet analysis is the result of a multidisciplinary effort that brought together many intersect fields.

Finally, wavelet analysis and neural network theory are used to analyze the acceleration signals to determine the direction of car crash.

At last, we have added this wavelet filter module in testing system, proved that this system is real-time, veracity, agile.

Meanwhile, wavelet transform idea is applied to this paper and a new wavelet de-noising method in OFDM channel estimation is proposed.

It is desirable to have an accurate wavelet extraction approach that has no hypothesis on the wavelet phase form.

Conclusion Its remarkable features will enable wavelet transform to be of good prospects in the practice of medical image processing.

The simulation result shows that the best wavelet denoising threshold parameter can be chosen effectively by this algorithm.

Conclusion The method that combines wavelet transform and shape filter can be used for ECG denoising during spaceflight.

Wavelet transform zero-crossing detection method can be used for the coding and recognition of human iris.

Influence of different wavelet basis, different threshold selection standard and decomposing scale on denoising result is analyzed as well.

In this paper, nonseparable multivariate wavelet transforms of the general form are presented.

In complicated frequency components domain, wavelet scalogram and assigned wavelet scalogram were used to further analyze vibration signals.

Different sequential morphological wavelet transform and processing for high-frequency coefficient were used to enhance biochip images.

In a process of seismic data processing, the wavelet processing with mixed phase is always an important project.

Harmonic wavelet analysis was applied to the non-linear vibration signal analysis in the low frequency segment of a cracked rotor.

And the wavelet transform itself is of so long basic functions that serious ghost appears in the decompressed images at low bit rate.

The simulation results show that the intrusion can be fully detected by the energy difference of the wavelet coefficients.

The main purpose is to discuss the stationarity of two classes of nonstationary processes after wavelet transformations.

Then we calculate the resulting wavelet coefficients through multi-resolution interpolation using a time-varied weight function.

It is one of the important research fields to apply the methods of wavelet analysis and partial differential equations in image processing.

Since the introduction of wavelet tree and certain pass, SPIHT can achieve high compression ratio as well as high image quality.

Moreover, some digital signal processing methods which are wavelet analysis and digital filtering are used for signal de-noising.

Fundamental theory of denoise by wavelet introduced, wavelet transfer is applied to the denoise of body-surface electrogastrogram signals.

The results showed that the wavelet had a reasonable and clear process , and its outcome measures were time saving .

The method of digital filter and wavelet transform were also used for analyzing and dealing with the signal.

Apparently they must have done something about it before they figured out the wavelet transform. . . ?

seismic wavelet extraction is one of the very important part of seismic inversion.

The maximum positive or upward deflection, also known as the crest, of the seismic wavelet.

It first proposes an approximate model of time-varying channels by means of wavelet multi-resolution decomposition.

applying wavelet analysis and statistics analysis to post process the long term identification results.

Wavelet is paid much attention due to its excellent performance in transient line selection fields.

The definition of the biorthogonal multiple vector-valued multivariate wavelet packets and a procedure for constructing them were given.

Through a steel beam damage experiment, the validity of structural damage alarming method based wavelet packet energy spectrum was proved.

The disadvantages of wavelet analysis have made scientists try to look for better tools from various angles.

The application perspective of wavelet transforms to ECG characteristic points recognition is predicted through the analysis of the results.

In addition, on the base of the theory of wavelet, a detailed description of the wavelet registration with a number of issues is given.

The VLSI implementation of the CWT(continuous wavelet transform) can be divided into two methods: time-domain and frequency-domain.

However, the design of optimized wavelet bases matched some types of given signal is a problem which has not been solved.

The image was diffused nonlinearly by the diffusion function of the nonlinear diffusion equation in the estimation of wavelet parameter.

Finding Boundary Layer Top : Application of a Wavelet Covariance Transform to Lidar Backscatter Profiles .

And then, quincunx sampling lifting scheme wavelet transform was used to fuse the images of polarization feature and total intensity.

Stationary wavelet transform and the mask of image were used to reduce truncation artifacts, and the experimental results indic. . .

The subject on the representation of signal in tight wavelet frame and the selection of the best wavelet base was discussed.

Wavelet transform is a signal processing techniques to overcome the other deficiencies of a signal analysis method.

Wavelet transform was used to obtain the position, thickness and speeds of the geologic strata.

the fourth chapter discusses the huffman coding method , anticipating coding method and wavelet transform coding method used in this paper.

The experiment results show that wavelet neural network has the better ability to the fine structure difference between the spectra.

The paper describes a simple method of wavelet analysis theory and meaning, and the MCG signal wavelet analysis were carried out in detail.

In this method a wavelet neural network model is built, through a gradient descent error algorithm, the network updates its parameters.

The combined method synthetizes the merits of two wavelet extraction methods, thus improves the whole computational efficiency.

Signal and noise shows different properties through wavelet transform, so wavelet can be used to separate the signal and the noise.

Wavelet denoising is one of the important application aspects.

Wavelet packet is used for noise speech decomposition, which is better than the traditional orthogonal wavelet threshold de- noising method.

Biggest advantage of using wavelet analysis Is a partial analysis of the signal, at any time or spatial domain analysis of signals.

The existence of an orbit maneuver is judged by observing the trend of the wavelet transform result.

Using high-order cumulants to extract wavelet becomes one of the hot research problems in recent years.

The paper has made some research of mechanical fault around the lifting wavelet analysis algorithm.

In light of the shortage of single-wavelet in image transform, research subject has been progressed to multi-wavelet field.

Though multiscale analysis is applied to logging data generally, the selection of wavelet base is not studied in detail.

Due to the introduction of wavelet tree and the certain pass, high compression ratio was obtained as well as high quality of image or video.

To PSNR and PMSE as the criterion, the wavelet algorithm with the traditional approach of denoising algorithm for comparison and conclusion.

After decomposing signal of wavelet, threshold value can be chosen in different level to suppress noises, that means the method is flexible.

Wavelet theory is an excellent analytic tool in signal processing field, and is a powerful tool to reveal fractallocal scale property.

Wavelet analysis has good localization and can be used in multi-resolution analysis of time domain and frequency domain.

To complete our discussion of the DWT, let's look at how the wavelet coefficient matrix is applied to the data vector.

We describe here an efficient thresholding technique for denoising by analysing the statistical parameters of the wavelet coefficients.

A new finite element space is studied in which the scaling function of B-spline wavelet is considered as the shape function of tetrahedron.

In fact, the chip implementation of 2D DWT is that of a set of biorthogonal wavelet FIR filters.

The statistics of image wavelet coefficients is non-Gaussian and can be described by generalized Gaussian distribution (GGD).

Vibration acceleration signal is easy to obtain, and with high precision, wavelet packet energy method is a good way for damage locating.

And on this basis, a detecting system united by the wavelet ideas and chaotic oscillator detection method is proposed.

We applied the wavelet domain inversion method to determine the mechanisms of middle and small earthquakes by regional waveform records.

The small wave packet transformation is the wavelet transformation promotion, constituted the wavelet analysis together.

It is pointed out that continuous wavelet transform is useful in weak signal detection which help itself to be used in fault diagnosis.

The experimental results show that wavelet neural network is an effective method in signal denoising of ultrasonic detection.

In this paper the traffic signal is analyzed with its Wavelet Transform so as to watch the approximation and details more accurately.

Using wavelet transform carry on the decomposition of the original information of signal, get different characteristic vector of signal.

Traditional wavelet extraction methods usually have the hypothesis that the wavelet is in a certain form, such as the minimum phase.

because of the heavy computational cost , software implementations of wavelet transform cannot be used in real - time signal processing.

The emphasis is to discuss the two dimensional discrete wavelet forward transform and backward transform in picture compress.

The simulations of a random wind field with spatial correlativity presented using wavelet bases.

We develop a technique using stochastic resonance (SR)-based wavelet transform for the enhancement of unclear diagnostic ultrasound images.

In this paper, the principles, contents and realization means of monitored subsidence data analysis based on wavelet theory are introduced.

The HMT is a tree-structured probabilistic graph that captures the statistical properties of the coefficients of the wavelet transform.

The wavelet transform has become a key tool for image de-noising owing to its energy compressing property.

Moreover we studied also the natural boundary integral equations and its wavelet solutions. (3) estimation of the covariance matrix.

A novel digest structure, two-layered wavelet tree, and its correspondent burst detection algorithm are proposed.

Abstract: We developed a real-time wideband speech codec adopting a wavelet packet based methodology.

Recently, the statistical methods of seismic wavelet estimation achieved comprehensive application in real seismic data processing.

The forecasted peak load can be obtained by wavelet reconstruction with the forecasted linear part and non-linear part.

In this paper, structural response which have transformed by wavelet packet establish damage index of the structure, then damage detection.

The principles of the wavelet analysis and resonance cleavage and their application in the machinery fault detection are introduced.

Utilizing wavelet analysis of energy information as features, then use fuzzy identification method to determined a single signal types.

As a new method of signal processing, wavelet transform refines different spatial domain signal, setting up variant scale parameters.

The sufficient condition for system model and its inversion approximated by wavelet networks are presented.

The rate control problem in such video coder can be regarded as a problem of bit-allocation among different wavelet sub-bands.

Compared with the wavelet-based homogenization methods, the improved wavelet-based method further improve the calculation accuracy.

The intrinsic relationship between the wavelet analysis and resonance cleavage is discussed.

And an algorithm to simulate anywhere pressure wavelet base on the near-field pressure wavelet observations was presented in this paper.

We present a wavelet correlation filter for diagnosing the incipient faults of a rolling bearing.

The Fourier transform and the wavelet transform are two important mathematical transforms used in industry.

currently , application of wavelet analysis on wireless communication mainly focuses on algorithm of adaptive equalization.

Recently, the statistical methods of wavelet extraction achieved comprehensive application in real seismic data processing.

a wavelet descriptor is presented, which is suitable for contours constructed with a set of points.

The basic theory of wavelet analysis that applied to vibrational signal analysis is presented.

A wavelet exponential denoising method that the wavelet coefficient divided by exponential denoising factor is proposed.

Cardioversion outcome prediction based on the wavelet technique increased the specificity up to 66% at the 95% sensitivity level.

Wavelet denoising technique was used to remove noise, and it improved the monitoring of the echo signal-to-noise ratio.

The experiment result shows the Wiener filter is better than the standard wavelet thresholding method.

Conventional analytical methods in the wavelet domain are used to present an analysis of terahertz (THz) waveguide modes.

CWT has been used to analyze EEG in order to choose the most fitness wavelet basis.

we establish the methods to set up pre warning models by wavelet analysis in line case, and extend it to general situation.

For those noisy images, the wavelet theory is taken to preliminarily process for the next analysis for the image.

Motivated by its application in signal denoising, image compression, etc. , wavelet frames have interested many mathematicians.

This article will introduce the latest exploration results of the combination of economic model and wavelet analysis. . .

Using time domain analysis and wavelet packet method and approximate entropy theory to analyze the characteristics of the signal.

Wavelet and Partial Differential Equation(PDE) are the main methods in removing image noise.

The wavelet packet transform can be used to compress seismic data in large batch processing.

Multidimensional edge detection on the basis of wavelet decomposition detail was applied to detect image edge.

The concept of biorthogonal vector-valued wavelet were introduced.

A study has been made of applications of wavelet theory to data processing of economy and finance data.

Wavelet analysis is a time-frequency analysis method which is a powerful tool to deal with non-stationary signals.

The multiple-layer search strategy based on lifting wavelet transform was used to improve the performance of the algorithm.

The theory of wavelet transform was firstly introduced, and removing the noise of weight signal using wavelet was further presented.

Based on that, this paper constructed a new morphological undecimated wavelet (MUDW) and applied it to power quality disturbances location.

Compared with the wavelet denoising method the proposed method is easier to use and possesses a good denoising effect and good adaptability.

The numeric example showed that the wavelet packet analysis can resist noise disturbs and detect the structural damage effectively.

Wavelet recurrent neural network was used to establish the model of long range batch process.

Experiments demonstrate that the coherent processing results of wavelet domain decrease as SNR deteriorates.

Biorthogonal wavelet packet decomposition overcomes the weakness of the conventional orthogonal wavelet transform.

The ultimate simulation test indicates that the traveling wave fault location by wavelet transformation has high accuracy.

Both simulated and tested results demonstrate that the wavelet entropy based indexes are sensitive to structural local damage.

The lifting wavelet transform does not depend on Fourier transform, so the calculation is simple and the operating speed is fast.

Under a fixed seismic frequency, wavelet side lobes may increase the difficulty of interpreting and recognizing thin sand bodies.

At present wavelet package method is a time-frequency analysis method of orthogonal decomposition based on multi-resolution analysis.

We developed a real-time wideband speech codec adopting a wavelet packet based methodology.

Wavelet analysis is one kind of multiscale analysis method which analyses matters in a series of nesting air space.

Wavelet transform is an efficient mathematical tool for singularity detection.

Firstly, the collectivity vectors that express the wavelet energy distribution of response signal of intact structure are established.

Then the algorithm that the color watermark is embedded into original color image using discrete wavelet transform is analyzed.

The quality of the noise removal was improved by combining wavelet packet transform with latent variable regression (LVR).

In the dissertation, the research involves power quality disturbance detection and identification by wavelet transform and data mining.

Wavelet transform is attracting much attention from mathematicians and engineers for its excellent time-frequency character.

The features of the wavelet transformation in signal analysis and the frequently-used wavelet filtering methods are introduced.

Authors have made initial research on phase characteristic of seismic wave under wavelet transform. It is shown that the me. . .

Wavelet transform is widely used in harmonic analysis domain because of its good characteristic of time-frequency analysis.

In this paper, the wavelet transform of a modulation Gaussian function is introduced.

By wavelet analysis, the cutting force signals of the bulk amorphous alloy was disposed to get it signal characterizations.

Then, by making quantization and entropy coding on these wavelet coefficients, the work of compressing the image is finished.

This algorithm combining wavelet de-noising with Kalman filtering algorithm could eliminate outliers more effectively.

Wavelet theory and time-domain theory are used in the processing of vibrant information for character information extraction.

Results showed the wavelet transform is a more efficient method in comparison with Fourier transform.

Finally, deviation data of the band prediction are compressed by three-dimensional wavelet transform coding.

Multiscale boundary detection is equivalent to searching out the local extremum of wavelet transform modulo of image.

Signals from the anti-Juanji Juanji blind separation of the original signal, signal can be used to reduce the seismic wavelet extraction.

The wavelet analysis procedure is to adopt a wavelet prototype function, called an analyzing wavelet or mother wavelet.

In this paper , developed a set of comprehensive test system for the mechanical parameters of high-voltage switch based on wavelet analysis.

The model combines good time domain, frequency domain resolving ability of wavelet transformation and nonlinear learning ability of SVM.

In recent years, wavelet transform has been widely used in noise reduction for its well time-frequency analysis features.

By combining wavelet transform with increment sign correlation, an efficient and robust image registration method is presented.

A novel handwritten numeral recognition approach was presented using multi-wavelet neural network clusters to expand contour shell.

The welding processes of two CO2 arc-welding machines were tested and analyzed using a self-developed welding dynamic arc wavelet analyzer.

A hybrid network traffic prediction algorithm, is provided, in which Kalman filter (KF) and wavelet are combined.

The optimal wavelet shrinkage threshold in this method is determined by the root mean square value of high frequency wavelet coefficient.

Each node contains a set of 40 complex Gabor wavelet coefficients at different scales and orientations (phase, amplitude).

This article investigates the medical digital enhancing methods of histogram equilibrium and wavelet transform.

The wavelet representation naturally facilitates the construction of such spatially adaptive algorithms.

Here, the cyclostationarity analysis is combined with wavelet filtering for detection of rolling element bearing early faults.

All the algorithms referred hereinbefore are compared with standard wavelet transform.

Finally these images are reconstructed with composite wavelet coefficients and by performing the inverse IHS transform.

In this study, a damage detection index, namely, wavelet packet energy rate index, is proposed for the damage detection of structures.

Wavelet transform has upstanding quality at time domain and frequency domain, which can effectively characterize signals.

The paper presents a new wavelet transform based generator split phase transverse differential protection scheme with sampled values.

The compression of video images using wavelet theory is an important image compression technique.

Two different methods were used to denoise the wavelet coefficients.

This paper presents a ship detection method combining wavelet analysis and directional filtering for cloudy remote sensing images.

Due to wavelet contrast's indication of the luminance contrast of the image, this algorithm could achieve adaptively embedding.

We survey the various applications in MRS of the wavelet transform and related time-frequency methods.

Wavelet enhancement considers the spatial domain and frequency domain of image signal, but not the nonlinearity of vision.

Wavelet filtering and averaging method are used to extract the weak VEP signal from strong background noise.

The mechanisms of one foreshock and four aftershocks of Yushu earthquake were determined by the wavelet domain inversion method.

wavelet decomposition The weighted approach is highlighted by the weighted weak image edges and change the details.

At present, the common frequency domain watermarking algorithm primarily adopts wavelet transformation or DCT.

S transform inherits the advantages of the wavelet transform and short time Fourier transform. It is suitable for medical image processing.

The relationships between ECG characteristic points and the modulus maximum pairs of their wavelet transforms are expounded.

This paper introduces two methods of detecting harmonics. By comparison we find wavelet packet transform has apparent advantages.

Firstly, the wavelet transform theory and image edge detection theory have been deeply researched on.

Generalized dyadic wavelet is given, and its application in signal processing is disused.

This paper proposes a new textured image segmentation algorithm which integrates wavelet transform and Gaussian mixture models.

Using the multi-resolution capability analytical property of the wavelet analysis hence improved the optimization iteration speed.

Conclusion: Wavelet threshold transformation can better process non-stationary signals like ECG signals.

After the best decomposition level was determined, the best wavelet base was chosen by image fusion evaluation methods.

Recently, wavelet neural networks have become a popular tool for non-linear functional approximation.

Contrast to wavelet transforms, Directional Filter Banks(DFB) can extract directional and edge information of images better.

A cascaded hybrid wavelet neural network (WNN) adaptive blind equalizer is proposed for severe nonlinear distortion channel.

Application of wavelet threshold denoising method for image denoising will result in mosaic appearance and image distortion.

Using wavelet transform and the improved minimum distance method can choose the image segmentation thresholds automatically.

Describes the definition and type of Wavelet Transform and then explains mainly the advantage and typical application of wavelet transform.

wavelet transform and its application in power system frequency tracking .

The differential equations can be transformed into the integral equations by using the continuous wavelet transform.

The changes in grain output in Hunan province have been analyzed at multi-time scales with Monet wavelet technique.

Clearly, wavelet packet transform detection system is feasible to detect signal in the context of the Bimodal Noise.

Wavelet transform is a very useful method for image features extraction and pattern recognition.

A methods using stationary wavelet transform with inter-scale and intra-scale dependencies for infrared image denoising is proposed.

This paper presents an online identification method for guided bomb based adaptive wavelet orthogonal basis neural network.

A combustion instability detection method that uses the wavelet detail of combustion pressure fluctuations was put forward.

In this thesis a method combining wavelet analysis and artificial neural network (ANN) is presented to forecast Market Clearing Price (MCP).

The combination of wavelet analysis and support vector machine is introduced to automatically diagnose power supply line fault.

An analysis of spatial context conditioning and run-length coding in embedded progressive, wavelet-based image coding is presented.

Wavelet transform was utilized for correction for spectral background of signals in ICP-AES and satisfactory results were obtained.

It obtained good results that the rubbing fault of slow-varying rotor system diagnosed by wavelet time-frequency contour map.

It is introduced that the method of wavelet analysis is applied to recognizing the defects of plate form in rolling process.

two victoria wavelet decomposition provides the image analysis with the direction selectivity.

This method in combination with the wavelet small-scale edge detecting method can effectively detect fault and suppress noise.

This project is accomplished by license plate location with wavelet and character recognition with improved BP neural network.

Multi-resolution analysis character of wavelet transform can well reflect signal local characteristic.

The algorithm embedded dual watermark using complementary approach in wavelet packet modulation field.

A method of signal mutative symptom extraction is presented, in which the theory of wavelet transform is applied.

The basis idea of wavelet analysis comes from the method of stretching and translating in classical reconciliation analysis.

This paper discussed the wavelet base type and the wavelet decomposition progression in wood texture wavelet multi-resolution analysis.

The principal properties of human visual system are analysed, then a wavelet-based algorithm for image contrast enhancement is proposed.

Simulation showed both two multiscale wavelet transform algorithms have good results in elimination of outliers.

Orthogonal wavelet transform plays a part of whiting, turning the input signals of adaptive filter orthogonal.

A wavelet de-noising method is introduced, and feasibility of the method is verified by numerical calculation.

Dual-tree complex wavelet pocket transform is dedicated to try to resolve the problem of fault line selection.

Wavelet packet analysis is an abundant means to wavelet analysis, and it played better at high-frequency information subdivision.

In fact, wavelet transform filter equal to analysis signal by a set of band-pass filters.

Application of Gauss wavelet to demarcate log stratigraphic sequence automatically .

Finally, we reconstruct the morphing result images through inverse wavelet transformation.

Signal Acquisition; Wavelet Transform; Wavelet Packet; Fault Diagnosis.

A new filtering algorithm of ECG signal is proposed. It is combined with wavelet absolute maximum value, and its prior rule is R wave.

In the paper, the application of wavelet transform to the ultrasonic imaging detection of coarse grain materials is discussed.

The wavelet entropy was used to explore the information contained in the EPSP.

This paper focuses on an audio watermarking algorithm research based on lifting wavelet transform and chaotic encryption.

Aiming at the problem of VDR radar image compression, the integer wavelet transform and asymmetric shift ROI coding algorithm are presented.

Obtained from the wavelet transform and the multi-resolution analysis, it discussed the fast algorithm of orthogonal wavelet transform.

This paper presented the signal denoising method of second-generation wavelet combining new improved threshold function.

This paper evaluates the performance of an image compression system based on wavelet-based subband decomposition and vector quantization.

Finally, the output image can be obtained through inverse wavelet transform.

The wavelet analysis is a type of new mathematic analysis tool and has characteristic multi-resolution.

A Wavelet-Based Reduced Rank Kalman Filter for Assimilation of Stratospheric Chemical Tracer Observations.