Various time-frequency methods have been used to study time-varying properties of non-stationary neurophysiological signals. In the present study, a time-frequency coherence estimate using continuous wavelet transform (CWT) together with its confidence intervals are proposed to evaluate the correlation between two non-stationary processes. The approach is based on averaging over repeat trials. ...

A filter bank in which cyclic convolutions are used in place of linear convolutions will be referred to as a cyclic convolution filter bank (CCFB). A dyadic tree-structured CCFB can be used to perform a discrete wavelet transform suitable for coding based on symmetric extension methods. This paper derives an implementation technique for the tree-structured CCFB that can be realized by FFT proce...

In 1992 Unser and colleagues proved that the sequence of normalized and scaled B-splines Bm tends to the Gaussian function as the order m increases, [1]. In this article the result of Unser et al. is extended to the derivatives of the B-splines. As a consequence, a certain sequence of wavelets defined by B-splines, tends to the famous Mexican hat wavelet. Another consequence can be observed in ...

A novel analysis method for binaural room impulse responses (BRIRs) is presented. It is based on the analysis of ear canal signals with continuous wavelet transform (CWT). Then, the crosswavelet transform (XWT) is used for detection of the direct sound and individual reflections from a BRIR. The new method seems to time-localize the reflections quite accurately. In addition, the proposed analys...

The aim of this study is to evaluate a machine-learning method in which symbolic representations of folk songs are segmented and classified into tune families with Haar-wavelet filtering. The method is compared with previously proposed Gestaltbased method. Melodies are represented as discrete symbolic pitch-time signals. We apply the continuous wavelet transform (CWT) with the Haar wavelet at s...

This paper is designed to be partly tutorial in nature and partly a summary of recent work by the authors in applying wavelets to various image processing problems. The tutorial part describes the lter-bank implementation of the discrete wavelet transform (DWT) and shows that most wavelets which permit perfect reconstruction are similar in shape and scale. We then discuss an important drawback ...

Image denoising is an important step in eliminating any noise impact image transmission process. Recently we presented two approaches for Bivariate based denoising. They were Double Density Discrete Wavelet Transform (DD DWT) and Dual Tree Complex CWT). In both techniques decomposed noisy images with either DD DWT or CWT decompositions then applied the technique removal. this paper propose adap...

The aim of this work is to investigate quantitatively the capability of the Continuous Wavelet Transform (CWT) as a tool to estimate (calculate) Jitter and Shimmer, assessing the error between these indices calculated in each Wavelet decomposition and the ones for the original signal, for several dilatation levels. Two synthetic vowels /a/ were generated with the fundamental frequencies of 120 ...

This paper presents a high dynamic range (HDR) image zero watermarking method based on dual tree complex wavelet transform (DT-CWT) and quaternion. In order to be against tone mapping (TM), DT-CWT is used the three RGB color channels of HDR for obtaining low-pass sub-bands, respectively, since can extract contour change small after TM. The provides wide range, thus, three-color channel correlat...

The presence of noise in a nonstationary signal (i.e., whose frequency content varies with time) complicates the extraction of meaningful information from the signal. The classical Fourier domain of such a signal can only separate the noise from the useful signal energy if they have different frequency content. For nonstationary signals the windowed Fourier transform has been introduced to loca...