Results 261 to 270 of about 254,430 (319)

Digit pipelined discrete wavelet transform

Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing, 2002
The paper describes a digit pipelined architecture for the 1D discrete wavelet transform, assuming a digit-serial model of computation. The use of simple operations and data movement makes it suitable for VLSI implementation and it can be easily mapped onto fine-grain custom VLSI and FPGA-based architectures.
C. Nagendra, M.J. Irwin, R.M. Owens
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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.
Yuanfa Wang, Zunchao Li, Chuang Wang, Lichen Feng, Zhiyun Zhang   +4 more
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The Discrete Wavelet Transform

2004
The MRA structure allows for the convenient, fast, and exact calculation of the wavelet coefficients of an L 2 function by providing a recursion relation between the scaling coefficients at a given scale and the scaling and wavelet coefficients at the next coarser scale. In order to specify this relation, let {V j × be an MRA with scaling function φ(x).
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Discrete Wavelet Transform Signal Analyzer

IEEE Transactions on Instrumentation and Measurement, 2007
This paper addresses the problem of processing biological data, such as cardiac beats in the audio and ultrasonic range, and on calculating wavelet coefficients in real time, with the processor clock running at a frequency of present application-specified integrated circuits and field programmable gate array.
Cox, Pedro Henrique, de Carvalho, Aparecido Augusto   +1 more
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Numerical Condition of Discrete Wavelet Transforms

SIAM Journal on Matrix Analysis and Applications, 1997
In many applications biorthogonal wavelets have been used rather than orthogonal ones, since the latter might exclude other useful properties like symmetry in the case of compactly supported wavelets. Thus one would like to study stability of biorthogonal wavelets and obtain quantitative information about sensitivity to noise in the data or ...
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Efficient inverse discrete wavelet transformer

2017 6th Mediterranean Conference on Embedded Computing (MECO), 2017
This paper describes the efficient one-dimensional inverse discrete wavelet transformer with 5/3 filter. The described design makes use of the same registers for both low-pass and high-pass filtering in different time slots. The design utilizes 33% less registers, 17% less logic elements, has 7% higher maximum operating frequency and 2% lower total ...
Goran Savic, Milan Prokin, Vladimir Rajovic, Dragana Prokin   +3 more
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CONVOLUTION FOR THE DISCRETE WAVELET TRANSFORM

International Journal of Wavelets, Multiresolution and Information Processing, 2011
Translation and convolution associated with the discrete wavelet transform are investigated using properties of Calderón–Zygmund operator and Riesz fractional integral operator. Dual convolution is also studied. The wavelet convolution is applied to approximate functions belonging to certain Lp-spaces.
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Discrete Wavelet Transform Domain Techniques

2013 International Conference on Informatics and Creative Multimedia, 2013
In this paper we focus on the process of embedding and retrieving on DWT domain in format of video. We therefore have chosen some proposed technique in DWT. We choose DWT because as it provides both spatial and frequency domain characteristic of the signal.
Farnaz Arab, Salwani Mohd Daud, Siti Zaiton Hashim   +2 more
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Discrete Wavelet Transform (DWT)

2015
The wavelet transform can be seen as a wavelet-based expansion (decomposition) of a finite-energy signal. In the discrete wavelet transform (DWT), economy in the representation of the signal and possibility of perfect signal reconstruction (PR) are crucial.
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Discrete wavelet transforms in VLSI

[1992] Proceedings of the International Conference on Application Specific Array Processors, 2003
Three architectures, based on linear systolic arrays, for computing the discrete wavelet transform, are described. The AT/sup 2/ lower bound for computing the DWT in a systolic model is derived and shown to be AT/sup 2/= Omega (N/sup 2/N/sub w/k). Two of the architectures are within a factor of log N from optimal, but they are of practical importance ...
M. Vishwanath, R.M. Owens, M.J. Irwin
openaire   +1 more source