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Distributional Wavelet Transform
Proceedings of the National Academy of Sciences, India Section A: Physical Sciences, 2016zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Pathak, R. S., Singh, Abhishek
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Wavelets and Wavelet Transform
2017Wavelet transforms are the most powerful and the most widely used tool in the field of image processing. Wavelet transform has received considerable attention in the field of image processing due to its flexibility in representing non-stationary image signals and its ability in adapting to human visual characteristics. Wavelet transform is an efficient
Aparna Vyas, Soohwan Yu, Joonki Paik
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Discrete Wavelets and Fast Wavelet Transform
1991The wavelet analysis, introduced by J. MORLET and Y. MEYER in the middle of the eighties, is a processus of time-frequency (or time-scale) analysis which consists of decomposing a signal into a basis of functions (o jk ) called wavelets. These wavelets are in turn deduced from the analyzing wavelet o by dilatations and translations. More precisely:
Bonnet, Pierre, Rémond, Didier
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Wavelet transform for Fresnel-transformed mother wavelets
Chinese Physics B, 2011In this paper, we propose the so-called continuous Fresnel-wavelet combinatorial transform which means that the mother wavelet undergoes the Fresnel transformation. This motivation can let the mother-wavelet-state itself vary from |〉 to F†r,s|〉, except for variation within the family of dilations and translations. The Parseval's equality, admissibility
Shu-Guang Liu, Jun-Hua Chen, Hong-Yi Fan
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Wavelet and wavelet Stieltjes transforms
Proceedings of 32nd IEEE Conference on Decision and Control, 2002Some fundamental and useful properties of wavelet transforms are presented. A unified approach for both discrete and continuous time-frequency localization is introduced. >
T. Bielecki, J. Chen, S. Yau, E.B. Lin
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Lossless integer wavelet transform
IEEE Signal Processing Letters, 1997Signal compression can be obtained by wavelet transformation of integer input data followed by quantification and coding. As the quantification is usually lossy, the whole compression/decompression scheme is lossy too. We define a critical wavelet coefficient quantification, i.e., the coarsest quantification that allows perfect reconstruction.
Steven Dewitte, Jan Cornelis 0001
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Discrete Lattice Wavelet Transform
IEEE Transactions on Circuits and Systems II: Express Briefs, 2007The discrete wavelet transform (DWT) has gained a wide acceptance in denoising and compression coding of images and signals. In this work we introduce a discrete lattice wavelet transform (DLWT). In the analysis part, the lattice structure contains two parallel transmission channels, which exchange information via two crossed lattice filters.
Olkkonen, H., Olkkonen, Juuso
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International Journal of Geometric Methods in Modern Physics, 2006
We introduce the notion of extended wavelet transform for locally compact topological groups that are semidirect products with abelian normal factor, and we study its main properties. In particular, we show that this notion allows to define a weak wavelet transform — enjoying 'essentially' the same properties as a standard wavelet transform ...
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We introduce the notion of extended wavelet transform for locally compact topological groups that are semidirect products with abelian normal factor, and we study its main properties. In particular, we show that this notion allows to define a weak wavelet transform — enjoying 'essentially' the same properties as a standard wavelet transform ...
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1995 International Conference on Acoustics, Speech, and Signal Processing, 2002
Most machine speech analysis and processing is based on a warped spectral representation. The intent of the paper is to present a method by which proper warped representations can be computed efficiently. In the case of log-warping functions, the methods of the paper produce a wavelet-like transform as a linear convolution of a single log-warped ...
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Most machine speech analysis and processing is based on a warped spectral representation. The intent of the paper is to present a method by which proper warped representations can be computed efficiently. In the case of log-warping functions, the methods of the paper produce a wavelet-like transform as a linear convolution of a single log-warped ...
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Wavelets, Wavelet Filters, and Wavelet Transforms
2013Spectral characteristics of speech are known to be particularly useful in describing a speech signal such that it can be efficiently reconstructed after coding or identified for recognition. The wavelets are considered one of such efficient methods for representing the spectrum of speech signals.
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