Construction of Orthogonal Vector-valued Wavelets and Characteristics of Vector-valued Wavelet Packets

The notion of vector-valued multiresolution analysis is introduced and the concept of orthogonal vector-valued wavelets with 3-scale is proposed. A necessary and sufficient condition on the existence of orthogonal vector-valued wavelets is given by means of paraunitary vector filter bank theory. An algorithm for constructing a class of compactly supported orthogonal vector-valued wavelets is presented. Their characteristics is discussed by virtue of operator theory, time-frequency method. Moreover, it is shown how to design various orthonormal bases of space L^2（R, C^n） from these wavelet packets.

Characterizations of Orthogonal Vector-valued Multivariate Wavelet Packets

In this paper, the notion of orthogonal vector-valued wavelet packets of space L2 （R^s, C^n） is introduced. A procedure for constructing the orthogonal vector-valued wavelet packets is presented. Their properties are characterized by virtue of time-frequency analysis method, matrix theory and finite group theory, and three orthogonality formulas are obtained. Finally, new orthonormal bases of space L2（R^s,C^n） are extracted from these wavelet packets.

The Biorthogonality of Multiple Vector-valued Bivariate Wavelet Packets

The notion of a sort of biorthogonal multiple vector-valued bivariate wavelet packets,which are associated with a quantity dilation matrix,is introduced.The biorthogonality property of the multiple vector-valued wavelet packets in higher dimensions is studied by means of Fourier transform and integral transform biorthogonality formulas concerning these wavelet packets are obtained.

Efficient simulation of spatially correlated non-stationary ground motions by wavelet-packet algorithm and spectral representation method

Although the classical spectral representation method(SRM)has been widely used in the generation of spatially varying ground motions,there are still challenges in efficient simulation of the non-stationary stochastic vector process in practice.The first problem is the inherent limitation and inflexibility of the deterministic time/frequency modulation function.Another difficulty is the estimation of evolutionary power spectral density(EPSD)with quite a few samples.To tackle these problems,the wavelet packet transform(WPT)algorithm is utilized to build a time-varying spectrum of seed recording which describes the energy distribution in the time-frequency domain.The time-varying spectrum is proven to preserve the time and frequency marginal property as theoretical EPSD will do for the stationary process.For the simulation of spatially varying ground motions,the auto-EPSD for all locations is directly estimated using the time-varying spectrum of seed recording rather than matching predefined EPSD models.Then the constructed spectral matrix is incorporated in SRM to simulate spatially varying non-stationary ground motions using efficient Cholesky decomposition techniques.In addition to a good match with the target coherency model,two numerical examples indicate that the generated time histories retain the physical properties of the prescribed seed recording,including waveform,temporal/spectral non-stationarity,normalized energy buildup,and significant duration.

Enhanced Fourier Transform Using Wavelet Packet Decomposition

Many domains, including communication, signal processing, and image processing, use the Fourier Transform as a mathematical tool for signal analysis. Although it can analyze signals with steady and transitory properties, it has limits. The Wavelet Packet Decomposition (WPD) is a novel technique that we suggest in this study as a way to improve the Fourier Transform and get beyond these drawbacks. In this experiment, we specifically considered the utilization of Daubechies level 4 for the wavelet transformation. The choice of Daubechies level 4 was motivated by several reasons. Daubechies wavelets are known for their compact support, orthogonality, and good time-frequency localization. By choosing Daubechies level 4, we aimed to strike a balance between preserving important transient information and avoiding excessive noise or oversmoothing in the transformed signal. Then we compared the outcomes of our suggested approach to the conventional Fourier Transform using a non-stationary signal. The findings demonstrated that the suggested method offered a more accurate representation of non-stationary and transient signals in the frequency domain. Our method precisely showed a 12% reduction in MSE and a 3% rise in PSNR for the standard Fourier transform, as well as a 35% decrease in MSE and an 8% increase in PSNR for voice signals when compared to the traditional wavelet packet decomposition method.

A Study on B-Spline Wavelets and Wavelet Packets

In this paper, we discuss the B-spline wavelets introduced by Chui and Wang in [1]. The definition for B-spline wavelet packets is proposed along with the corresponding dual wavelet packets. The properties of B-spline wavelet packets are also investigated.

Radar Target Discrimination based on waveletPackets for Reduced data Storage

In order to storage resource of a radar recognition system, schemes for reducing data storage and for correlation discrimination of radar based on wavelet packets were proposed Experiment results at various signal-to-noise ratios were given The given.ability of the reduced data method's validity are supported by experimental results. Using optimal basis can get higher successful recognition rate using rigid wavelet basis.

A CLASS OF BIDIMENSIONAL NONSEPARABLEWAVELET PACKETS

2-band wavelet packets in L-2 (R-s) were constructed in [3]. In this note, a way to construct bidimensional orthonormal wavelet packets related to the dilation matrix M = ((1)(1) (1)(-1)) is obtained. M-wavelets are used ill quincunx subsampling in two dimensions for image processing. What is more., the approach of this paper can be generalized to construct wavelet packets in L-2 (R-s) related to a general diltion matrix.

Configuration for Predicting Travel-Time Using Wavelet Packets and Support Vector Regression

Travel-time prediction has gained significance over the years especially in urban areas due to increasing traffic congestion. In this paper, the basic building blocks of the travel-time prediction models are discussed, with a small review of the previous work. A model for the travel-time prediction on freeways based on wavelet packet decomposition and support vector regression (WDSVR) is proposed, which used the multi-resolution and equivalent frequency distribution ability of the wavelet transform to train the support vector machines. The results are compared against the classical support vector regression (SVR) method. Our results indicated that the wavelet reconstructed coefficient when used as an input to the support vector machine for regression performed better (with selected wavelets only), when compared with the support vector regression model (without wavelet decomposition) with a prediction horizon of 45 minutes and more. The data used in this paper was taken from the California Department of Transportation (Caltrans) of District 12 with a detector density of 2.73, experiencing daily peak hours except most weekends. The data was stored for a period of 214 days accumulated over 5-minute intervals over a distance of 9.13 miles. The results indicated MAPE ranging from 12.35% to 14.75% against the classical SVR method with MAPE ranging from 12.57% to 15.84% with a prediction horizon of 45 minutes to 1 hour. The basic criteria for selection of wavelet basis for preprocessing the inputs of support vector machines are also explored to filter the set of wavelet families for the WDSVR model. Finally, a configuration of travel-time prediction on freeways is presented with interchangeable prediction methods.

Deep neural network based on multi-level wavelet and attention for structured illumination microscopy

Structured illumination microscopy(SIM)is a popular and powerful super-resolution(SR)technique in biomedical research.However,the conventional reconstruction algorithm for SIM heavily relies on the accurate prior knowledge of illumination patterns and signal-to-noise ratio(SNR)of raw images.To obtain high-quality SR images,several raw images need to be captured under high fluorescence level,which further restricts SIM’s temporal resolution and its applications.Deep learning(DL)is a data-driven technology that has been used to expand the limits of optical microscopy.In this study,we propose a deep neural network based on multi-level wavelet and attention mechanism(MWAM)for SIM.Our results show that the MWAM network can extract high-frequency information contained in SIM raw images and accurately integrate it into the output image,resulting in superior SR images compared to those generated using wide-field images as input data.We also demonstrate that the number of SIM raw images can be reduced to three,with one image in each illumination orientation,to achieve the optimal tradeoff between temporal and spatial resolution.Furthermore,our MWAM network exhibits superior reconstruction ability on low-SNR images compared to conventional SIM algorithms.We have also analyzed the adaptability of this network on other biological samples and successfully applied the pretrained model to other SIM systems.

Diagnosis of Gearbox Typical Fault in Rolling Mills Based on the Wavelet Packets Technology

The early impulse fault diagnosis of the gearbox in rolling mills is often difficult and labour intensive because the gearbox of that high speed machine is multi-shafting transmission system,in which many gearsets and rolling bears work together at the same time and there are much complex frequency structure and various disturb.A new time-frequency method based on the wavelet packets technique was developed and used to extract the impact feature from signals collected from faulty data of one rolling mills gearbox.The method improves the signal to noise ration so that results obtained using this method represents features with fine resolution in both low-frequency and the high frequency bands.The results of analysis indicate the validity and the practicability of the method proposed here.

THEORY OF ORTHONORMAL M-BAND WAVELET PACKETS

In recent years, M-band orthonormal wavelet bases, due to their good characteristics, have attracted much attention. The ability of 2-band wavelet packets to decompose high frequency channels can be employed to improve the performance of wavelets for time-frequency localization, which makes more kinds of signals for analyzing by wavelets. Similar to the notations from the extension of 2-band wavelets to 2-band wavelet packets, the theoretic framework of M-band wavelet packets is developed, a generalization of the notations and properties of 2-band wavelet packets to that of M-band wavelet packets is made and the corresponding proofs are given.

Some Results on Wavelet Frame Packets

The aim of this paper is to study wavelet frame packets in which there are many frames. It is a generalization of wavelet packets. We derive few results on wavelet frame packets and have obtained the corresponding frame bounds.

Matrix Expression of the Orthogonal Wavelet (Packets) Transform

Matrix expression of finite orthogonal wavelet transform of finite impulse response signal is more valuable for theoretical analysis and understanding. However, clear deduction for matrix expression has not been provided yet. In this paper, the formulation to generate the re-lated matrix is put forward and the theorem on the orthogonality of this matrix proved. This effort deploys a basis for more deeper and wider applications in chemical processes. *

Effect of Diversity and Filtering on the Performance of Wavelet Packets Base Multicarrier Multicode CDMA System

In Wavelet Packets Based Multicarrier Multicode CDMA system, the multicode (MCD) part ensures the transmission for high speed and flexible data rate, the multicarrier (MC) part ensures the flexibility of handling multiple data rates, and wavelet packets modulation technique contributes to the mitigation of the interference problems. The CDMA system can suppress a given amount of interference. In this paper, the receiver employs suppression filter (SF) to mitigate the effect of narrow-band jammer interference and diversity techniques to reduce multiple access interference. The framework for the system and the performance evaluation are presented in terms of bit error rate (BER) over a Nakagami fading channel. Also, we investigate how the performance is influenced by various parameters, such as the number of taps of the SF, the ratio of narrow-band interference bandwidth to the spread-spectrum bandwidth, the diversity order, the fading parameter and so on. Finally, the performance of the system is compared with the performance Sinusoidal (Sin) based MC/MCD CDMA system.

NON-ORTHOGONAL P-WAVELET PACKETS ON THE HALF-LINE

In this paper, the notion of p-wavelet packets on the positive half-line P＋ is introduced. A new method for constructing non-orthogonal wavelet packets related to Walsh functions is developed by splitting the wavelet subspaces directly instead of using the lowpass and high-pass filters associated with the multiresolution analysis as used in the classical theory of wavelet packets. Further, the method overcomes the difficulty of constructing non-orthogonal wavelet packets of the dilation factor p 〉 2.

Orthogonal Matrix-Valued Wavelet Packets

In this paper, we introduce matrix-valued multiresolution analysis and matrix- valued wavelet packets. A procedure for the construction of the orthogonal matrix-valued wavelet packets is presented. The properties of the matrix-valued wavelet packets are investigated. In particular, a new orthonormal basis of L2(R, Cs×s) is obtained from the matrix-valued wavelet packets.

Theoretical research on structural damage alarming of long-span bridges using wavelet packet analysis

The state equation and observation equation of the structural dynamic systems under various analysis scales are derived based on wavelet packet analysis. The time-frequency properties of structural dynamic response under various scales are further formulated. The theoretical analysis results reveal that the wavelet packet energy spectrum （WPES） obtained from wavelet packet decomposition of structural dynamic response will detect the presence of structural damage. The sensitivity analysis of the WPES to structural damage and measurement noise is also performed. The transfer properties of the structural system matrix and the observation noise under various analysis scales are formulated, which verify the damage alarming reliability using the proposed WPES with preferable damage sensitivity and noise robusticity.

Acoustic emission source identification based on harmonic wavelet packet and support vector machine

In order to solve the fatigue damage identification problem of helicopter moving components, a new approach for acoustic emission （AE） source type identification based on the harmonic wavelet packet （HWPT） feature extraction and the hierarchy support vector machine （H-SVM） classifier is proposed. After a four-level decomposition of the HWPT, the energy feature of AE signals in different frequency bands is extracted, which overcomes the shortcomings of the traditional wavelet packet including energy leakage, and inflexible frequency band selection and different frequency resolutions on different levels. The H-SVM classifier is trained with a subset of the experimental data for known AE source types and tested using the remaining set of data. The results of pressure-off experiments on the specimens of carbon fiber materials indicate that the proposed approach can effectively implement the AE source type identification, and has a better performance in terms of computational efficiency and identification accuracy than the wavelet packet （WPT） feature extraction.

Performance of STBC-MC-CDMA system based on complex wavelet packet and turbo coding

On the basis of analyzing the principle of the space-time coding technique and the multi-carrier code division multiple access （MC-CDMA） technique, adopting the turbo codes as channel coding and the optimized complex wavelet packet as multi-carrier modulation, a novel space-time block coded the MC-CDMA system based on complex wavelet packet and turbo coding is proposed, and the system bit error rate （BER） performance in the Rayleigh fading channel is investigated. The system can make full use of space-time block codes＇ transmit diversity and turbo codes＇ good ability against fading channel to improve the BER performance significantly, and it can also avoid the decrease of spectrum efficiency of conventional MC-CDMA due to inserting cyclic prefix （CP） by utilizing superior characteristics of the optimized complex wavelet packet. Simulation results show that the proposed space-time block coded MC-CDMA system based on the complex wavelet packet performs better than the conventional space-time block coded MC-CDMA （STBC-MC-CDMA） system, and slightly outperforms the STBC-MC-CDMA with CP. Moreover, the application of the space-time block coding technique concatenated with turbo codes strengthens the system ability to combat various interferences in fading channel further.