Results 291 to 300 of about 96,830 (337)

Discrete Lattice Wavelet Transform

IEEE Transactions on Circuits and Systems II: Express Briefs, 2007
The 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
openaire   +4 more sources

Discrete Wavelets and Fast Wavelet Transform

1991
The 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
openaire   +3 more sources

Spherical wavelet transform and its discretization

Advances in Computational Mathematics, 1996
Starting from continuous wavelet transform on the sphere the authors describe a continuous version of spherical multiresolution. Next, using a scale discretization they construct spherical counterparts to wavelet packets and scale discrete wavelets.
Freeden, Willi, Windheuser, U.
openaire   +5 more sources

Discrete Wavelet Transform

1998
In general, discrete wavelet transforms are generated by samplings (in the time—scale plane) of a corresponding continuous wavelet transform. Such a discrete wavelet transform is specified by the choice of items: 1. a time—scale sampling set (a countable set of points), and 2. an analyzing wavelet.
Anthony Teolis, Anthony Teolis
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The Discrete Wavelet Transform

2013
Introduction Here we introduce the discrete wavelet transform (DWT), which is the basic tool needed for studying time series via wavelets and plays a role analogous to that of the discrete Fourier transform in spectral analysis. We assume only that the reader is familiar with the basic ideas from linear filtering theory and linear algebra
Andrew T. Walden, Donald B. Percival
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Hardware implementation of Discrete Wavelet Transform and Inverse Discrete Wavelet Transform on FPGA

2010 IEEE 18th Signal Processing and Communications Applications Conference, 2010
In this paper, hardware implementation of the Discrete Wavelet Transform (DWT) and Inverse Discrete Wavelet Transform (IDWT) based on FPGA is explained. DWT and IDWT algorithms are implemented on the Altera Cyclone-II FPGA. Filtering processes of rows and columns are seriatim applied as in level-by-level architecture. But both addressing for read/write
Fuat Karakaya, Mehmet Ali Cavuslu
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Discrete Wavelet Transform

2010
According to the definition of the continuous wavelet transform (CWT) given in (3.7), Chap. 3, the scale parameter s and translation parameter \(\tau\) can be varied continuously. As a result, performing the CWT on a signal will lead to the generation of redundant information.
Ruqiang Yan, Robert X. Gao
openaire   +2 more sources

The Discrete Wavelet Transform [PDF]

, 1991
Abstract : In a general sense, this report represents an effort to clarify the relationship of discrete and continuous wavelet transforms. More narrowly, it focuses on bringing together two separately motivated implementations of the wavelet transform, the algorithm a trous and Mallat's multiresolution decomposition.
openaire   +1 more source

Implementation of discrete wavelet transform

2014 12th IEEE International Conference on Solid-State and Integrated Circuit Technology (ICSICT), 2014
The discrete wavelet transform (DWT) has a very wide and important application in digital signal processing. Daubechies order 4 wavelet transform (db4) is elected to discuss in this work. The advantages of DWT are analyzed, and a three-level Mallat algorithm is implemented in this paper, and db4 low-pass and high-pass filters are selected in each level.
Zunchao Li, Yuanfa Wang, Lichen Feng, Chuang Wang, Zhi Yun Zhang   +4 more
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CONVERGENCE OF THE DISCRETE WAVELET TRANSFORM

International Journal of Wavelets, Multiresolution and Information Processing, 2012
The discrete wavelet transform; depending of the pair of integers (m, n), applied to functions f in L2(R) with respect to an admissible function h in L2(R) of class C∞ with compact support, is used to prove that f is continuous at x = 0, and furthermore at any x = b in R if and only if there exists the convergence of the discrete wavelet transform, as
Jaime Navarro, Oscar Herrera
openaire   +2 more sources