1 School of Information Technology, Jiangxi University of Finance and Economics, Nanchang 330013, China, [email protected]; [email protected] 2 School of Software and Communication Engineering, Jiangxi University of Finance and Economics, Nanchang 330013, China, [email protected], (corresponding author) 3 College of Biomedical Engineering, South-Central University for Nationalities, Wuh...

The environmental mismatch caused by additiv e noise and/or channel distortion often degrades th e perform ance of a s peech reco gnition sys tem seriously . V arious ro bustness techniques have been proposed to reduce this mismatch, and one category of them aim s to normalize the statistics of speech fea tures in both training and testing conditions. In general, these statistics norm alization...

Two wavelet-based noise reduction methods are discussed here. First, we improve the tradtional spatially selective noise filtration technique proposed by Xu et al. Second, we introduce a new thresholdbased denoising algorithm based on undecimated discrete wavelet transform. Simulations and comparisons are given.

his report reviews the history, theory and mathematics of wavelet analysis. Examination of the Fourier Transform and Short-time Fourier Transform methods provides information about the evolution of the wavelet analysis technique. This overview is intended to provide readers with a basic understanding of wavelet analysis, define common wavelet terminology and describe wavelet analysis algorithms...

In this paper human normal and epileptic Electroencephalogram signals are analyzed with popular and efficient signal processing techniques like Fourier and Wavelet transform. The delta, theta, alpha, beta and gamma sub bands of EEG are obtained and studied for detection of seizure and epilepsy. The extracted feature is then applied to ANN for classification of the EEG signals. Keywords—EEG, Epi...

The relationship between stock market returns and economic activity is investigated using signal decomposition techniques based on wavelet analysis. After the application of the maximum overlap discrete wavelet transform (MODWT) to the DJIA stock price index and the industrial production index for the US over the period 1961:1-2006:10wavelet variance and cross-correlations analyses are used to ...

With the advent of digital video and digital broadcasting, copyright protection of video data has been one of the most important issues. We present in this paper a novel method of digital watermark for video data based on the discrete wavelet transform. In this method, we embed the watermark in the lowest frequency components of each frame in the uncoded video by using a controlled quantization...

DEFINITION Wavelets are a useful mathematical tool for hierarchically decomposing functions in ways that are both efficient and theoretically sound. Broadly speaking, the wavelet transform of a function consists of a coarse overall approximation together with detail coefficients that influence the function at various scales. The wavelet transform has a long history of successful applications in...

As one of the major directions in applied and computational harmonic analysis, the classical theory of wavelets and framelets has been extensively investigated in the function setting, in particular, in the function space L2(R). A discrete wavelet transform is often regarded as a byproduct in wavelet analysis by decomposing and reconstructing functions in L2(R) via nested subspaces of L2(R) in ...