scholarly journals Minimization of Harmonics Noise Using Wavelet Transformation Technology

2011 ◽  
pp. 216-223
Author(s):  
Mr. Debasis Dash ◽  
Mr. Shatyaprakasha Satapathy ◽  
Dr. Chittaranjan Panda
Keyword(s):  
Wavelet Analysis ◽  
Wavelet Packet ◽  
Statistical Significance ◽  
Audio Signal ◽  
Design Procedure ◽  
Wavelet Packets ◽  
Threshold Function ◽  
Analysis Tool ◽  
Real Time Processing ◽  
Wavelet Spectra

The field programmable gate array technology can design high performance system at low cost for wavelet analysis. Wavelet transform has gained the reputation of being a very effective signal analysis tool for much practical application. Implementation of transform needs the meeting of real-time processing for most application. The objectives of this paper are to compare the Haar and Daubeches technology and to calculate the bit error rate (BER) between the input audio signal and reconstructed output signal. It is seen that the BER using Daubechies wavelet technology is less than Haar wavelet. The design procedure is explained using the stat of art electronic design. Automation tools for system design on FPGA, simulation, synthesis and implementation on the FPGA technology has been carried out. The power hovmoller, cross wavelet spectra and coherence are described. A Practical step-up-step guide to wavelet analysis is given with examples taken from time series. The guide includes a comparison to the windowed Fourier transform. New statistical significance test for wavelet power spectra are developed by deriving theoretical wavelet spectra for white and red noise. Empirical formula is given for the effect of smoothing on significance levels and filtering. The notion of orthogonal no separable trivet wavelet packets, which is the generation of orthogonal university wavelet packets is introduced. A de-noising method based on wavelet packet shrinkage is developed. The principle of wavelet packet shrinkage for de-noising and the section of thresholds and threshold function are analyzed.

scholarly journals COMPARISON BETWEEN HAAR AND DAUBECHIES WAVELET TRANSFORMIONS ON FPGA TECHNOLOGY

2014 ◽  
pp. 23-29
Author(s):  
Fatma H. Elfouly ◽  
Mohamed I. Mahmoud ◽  
Moawad I. M. Dessouky ◽  
Salah Deyab
Keyword(s):  
High Performance ◽  
Low Cost ◽  
Audio Signal ◽  
Design Procedure ◽  
Discrete Wavelet ◽  
Analysis Tool ◽  
Daubechies Wavelet ◽  
Daubechies Wavelets ◽  
Real Time Processing ◽  
Practical Applications

Recently, the Field Programmable Gate Array (FPGA) technology offers the potential of designing high performance systems at low cost. The discrete wavelet transform has gained the reputation of being a very effective signal analysis tool for many practical applications. However, due to its computation-intensive nature, current implementation of the transform falls short of meeting real-time processing requirements of most application. The objectives of this paper are implement the Haar and Daubechies wavelets using FPGA technology. In addition, the comparison between the Haar and Daubechies wavelets is investigated. The Bit Error Rat (BER) between the input audio signal and the reconstructed output signal for each wavelet is calculated. It is seen that the BER using Daubechies wavelet techniques is less than Haar wavelet. The design procedure has been explained and designed using the stat-of-art Electronic Design Automation (EDA) tools for system design on FPGA. Simulation, synthesis and implementation on the FPGA target technology has been carried out.

Optimally Sensitive and Efficient Compact Loudspeakers for Low Audio Frequencies

2007 ◽  
Vol 38 (7) ◽  
pp. 11-17
Author(s):  
Ronald M. Aarts
Keyword(s):  
Optimality Criterion ◽  
Low Frequency ◽  
Audio Signal ◽  
Design Procedure ◽  
Frequency Range ◽  
Force Factor ◽  
Low Frequencies ◽  
Limited Frequency ◽  
The Cost ◽  
Higher Sensitivity

Conventionally, the ultimate goal in loudspeaker design has been to obtain a flat frequency response over a specified frequency range. This can be achieved by carefully selecting the main loudspeaker parameters such as the enclosure volume, the cone diameter, the moving mass and the very crucial “force factor”. For loudspeakers in small cabinets the results of this design procedure appear to be quite inefficient, especially at low frequencies. This paper describes a new solution to this problem. It consists of the combination of a highly non-linear preprocessing of the audio signal and the use of a so called low-force-factor loudspeaker. This combination yields a strongly increased efficiency, at least over a limited frequency range, at the cost of a somewhat altered sound quality. An analytically tractable optimality criterion has been defined and has been verified by the design of an experimental loudspeaker. This has a much higher efficiency and a higher sensitivity than current low-frequency loudspeakers, while its cabinet can be much smaller.

CONSTRUCTING MULTIPLE WAVELET PACKETS WITH FIFS

Fractals ◽  
2001 ◽  
Vol 09 (02) ◽  
pp. 165-169
Author(s):  
GANG CHEN ◽  
ZHIGANG FENG
Keyword(s):  
Multiresolution Analysis ◽  
Wavelet Packet ◽  
Wavelet Packets ◽  
Scaling Functions ◽  
Wavelet Packet Decomposition ◽  
Fractal Interpolation ◽  
Fractal Interpolation Functions ◽  
Interpolation Functions

By using fractal interpolation functions (FIF), a family of multiple wavelet packets is constructed in this paper. The first part of the paper deals with the equidistant fractal interpolation on interval [0, 1]; next, the proof that scaling functions ϕ1, ϕ2,…,ϕr constructed with FIF can generate a multiresolution analysis of L2(R) is shown; finally, the direct wavelet and wavelet packet decomposition in L2(R) are given.

scholarly journals Wavelet analysis of the dynamics of waves of coronavirus infection in France, Sweden and Chine.

2021 ◽  
Vol 2021 (8) ◽  
Author(s):  
A. P. Anyutin ◽  
◽  
T. M. Khodykina ◽  
Keyword(s):  
Time Series ◽  
Wavelet Analysis ◽  
Population Size ◽  
Geographic Location ◽  
Coronavirus Infection ◽  
Wavelet Spectra

In this work, the wavelet spectra were calculated and studied for time series representing the dynamics of the new cases of coronavirus infection in France, Sweden and China. It was found that the Wavelet spectra for these countries have characteristic different-scale internal cycles, the number of which depends on the nature of the quarantine activities. It was detected that structure of the Wavelet spectra, their duration is practically independent of the geographic location, density and population size.

scholarly journals On Generalized Carleson Operators of Periodic Wavelet Packet Expansions

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Shyam Lal ◽  
Manoj Kumar
Keyword(s):  
Wavelet Packet ◽  
Wavelet Packets ◽  
Arithmetic Means ◽  
Periodic Wavelet

Three new theorems based on the generalized Carleson operators for the periodic Walsh-type wavelet packets have been established. An application of these theorems as convergence a.e. for the periodic Walsh-type wavelet packet expansion of block function with the help of summation by arithmetic means has been studied.

Study on the Method of Vibration Signal De-Noising Using Wavelet Packet Based on QPSO

2014 ◽  
Vol 599-601 ◽  
pp. 1738-1744
Author(s):  
Kai Zhao ◽  
Ben Wei Li ◽  
Jing Chen
Keyword(s):  
Experimental Verification ◽  
Wavelet Packet ◽  
Vibration Signal ◽  
Wavelet Function ◽  
Threshold Function ◽  
Vibration Signals ◽  
Selection Of

Although many wavelet de-noising methods have been studied and proposed, the parameters of them are obtained by experience mostly, which makes the de-noising effect instable. To solve the issues, the solutions, such as the selection of wavelet function and threshold function, the calculation of decomposition levels, the optimal wavelet packet basis and the thresholds obtained based on QPSO, have been studied in this paper. Every parameter is obtained by calculation. This method is applied to the de-noising experiment of sine and vibration signals. Through the experimental verification, the effect of this de-noising method is obvious.

scholarly journals Enhancement of Fault Feature Extraction from Displacement Signals by Suppressing Severe End Distortions via Sinusoidal Wave Reduction

Energies ◽  
2019 ◽  
Vol 12 (18) ◽  
pp. 3536 ◽  
Author(s):  
Binqiang Chen ◽  
Qixin Lan ◽  
Yang Li ◽  
Shiqiang Zhuang ◽  
Xincheng Cao
Keyword(s):  
Feature Extraction ◽  
Wavelet Analysis ◽  
Low Frequency ◽  
Wavelet Packets ◽  
Discrete Wavelet ◽  
Sinusoidal Wave ◽  
Displacement Signal ◽  
Fault Features ◽  
Reconstructed Signal ◽  
Weak Fault

Displacement signals, acquired by eddy current sensors, are extensively used in condition monitoring and health prognosis of electromechanical equipment. Owing to its sensitivity to low frequency components, the displacement signal often contains sinusoidal waves of high amplitudes. If the digitization of the sinusoidal wave does not satisfy the condition of full period sampling, an effect of severe end distortion (SED), in the form of impulsive features, is likely to occur because of boundary extensions in discrete wavelet decompositions. The SED effect will complicate the extraction of weak fault features if it is left untreated. In this paper, we investigate the mechanism of the SED effect using theories based on Fourier analysis and wavelet analysis. To enhance feature extraction performance from displacement signals in the presence of strong sinusoidal waves, a novel method, based on the Fourier basis and a compound wavelet dictionary, is proposed. In the procedure, ratio-based spectrum correction methods, using the rectangle window as well as the Hanning window, are employed to obtain an optimized reduction of strong sinusoidal waves. The residual signal is further decomposed by the compound wavelet dictionary which consists of dyadic wavelet packets and implicit wavelet packets. It was verified through numerical simulations that the reconstructed signal in each wavelet subspace can avoid severe end distortions. The proposed method was applied to case studies of an experimental test with rub impact fault and an engineering test with blade crack fault. The analysis results demonstrate the proposed method can effectively suppress the SED effect in displacement signal analysis, and therefore enhance the performance of wavelet analysis in extracting weak fault features.

Structural Neuroimaging in First-Episode Psychosis: a review of neuroimaging practice in an early intervention service

2011 ◽  
Vol 26 (S2) ◽  
pp. 947-947
Author(s):  
S. Otero ◽  
R. Mehrotra
Keyword(s):  
Early Intervention ◽  
Statistical Significance ◽  
First Episode Psychosis ◽  
First Episode ◽  
Analysis Tool ◽  
Early Intervention Service ◽  
Structural Neuroimaging ◽  
Intervention Service ◽  
Episode Psychosis ◽  
Significant Difference

IntroductionThe UK NICE technology guidance “Structural Neuroimaging in First-Episode Psychosis” concludes that CT/MRI is not routinely recommended as an initial investigation for first-episode psychosis.ObjectivesTo evaluate the use of CT/MRI in a group of Early Intervention Service (EIS) patients with a first-episode psychosis aged 18–35 years at presentation.AimsTo develop practice guidelines for use of neuroimaging in first-episode psychosis.MethodsAll 107 patients registered with the EIS in Hounslow, London, UK, were eligible for inclusion in this review. Data was collected from the medical records and the Picture Archiving and Communications System. Data was analysed using a microsoft excel data analysis tool. Additionally, comparisons were made between the group of patients with normal scans and that with abnormal scans. Statistical significance was determined using the chi-squared method with a significance of P < 0.05.Results17 patients had documented neuroimaging results. 4 scans were abnormal. There was no significant difference between the group with normal and abnormal scans in terms of gender, abnormalities of physical/neurological health, blood tests and whether the patient had any additional medical conditions. Abnormal scan results did not influence treatment or outcome for any patient.ConclusionsThe abnormal scans were not correlated to clinical indices of history, examination and laboratory tests. Abnormal scans appear to have a low yield in terms of clinical effectiveness. The findings support selective use of neuroimaging in this cohort of patients. The indications for it usage would appear to rely on clinical judgement as well clinical findings.

The Energy Distribution of Tire-Road Noise and Noisy Speech Based on Wavelet Packet

2011 ◽  
Vol 464 ◽  
pp. 721-724 ◽  
Author(s):  
Zhi Yong He ◽  
Li Heng Luo
Keyword(s):  
Energy Distribution ◽  
Speech Enhancement ◽  
Mobile Communications ◽  
Wavelet Packet ◽  
Noise Signal ◽  
Wavelet Packets ◽  
Road Noise ◽  
Noisy Speech ◽  
Time Frequency ◽  
The Difference

Speech enhancement is very important for mobile communications or some other applications in car. The energy distribution of signal is the basis of algorithms which denoise noisy speech in time-frequency domain. In this work, the noise regarded is the tire-road noise when driving in expressway. Wavelet packets transform is used in the analysis. After decomposing noise signal and noisy speech signal by wavelet packet transform, the analysis for the difference of the energy distribution between noisy speech and noise is finished.

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