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On Sampling Theorem, Wavelets and Wavelet Transforms
Proceedings. IEEE International Symposium on Information Theory, 1993Summary: The classical Shannon sampling theorem has resulted in many applications and generalizations. From a multiresolution point of view, it provides the sinc scaling function. In this case, for a band-limited signal, its wavelet series transform (WST) coefficients below a certain resolution level can be exactly obtained from the samples with a ...
Xiang-Gen Xia, Zhen Zhang
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Proceedings of IEEE Antennas and Propagation Society International Symposium and URSI National Radio Science Meeting, 1995
Summary form only given, as follows. One attractive application of the wavelet is as a basis function that is of compact support both in the original and in the transform domain. However, this is not possible from a theoretical point of view. Namely, a pulse that is limited in time cannot simultaneously be limited in frequency.
T. K. Sarkar +4 more
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Summary form only given, as follows. One attractive application of the wavelet is as a basis function that is of compact support both in the original and in the transform domain. However, this is not possible from a theoretical point of view. Namely, a pulse that is limited in time cannot simultaneously be limited in frequency.
T. K. Sarkar +4 more
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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. >
Jie Chen +3 more
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Wavelets, Wavelet Filters, and Wavelet Transforms [PDF]
, 2013 Spectral 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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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
Soohwan Yu, Aparna Vyas, Joonki Paik
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IFAC Proceedings Volumes, 1994
Abstract This is a tutorial about nonparametric nonlinear system identification. Advantages and limitations of this approach are discussed from the engineer’s point of view. Classical as well as modem techniques are discussed. Both practical and mathematical issues are investigated.
P-Y. Glorennec +4 more
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Abstract This is a tutorial about nonparametric nonlinear system identification. Advantages and limitations of this approach are discussed from the engineer’s point of view. Classical as well as modem techniques are discussed. Both practical and mathematical issues are investigated.
P-Y. Glorennec +4 more
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On trigonometric wavelets [PDF]
Constructive Approximation, 1993 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hrushikesh N. Mhaskar, Charles K. Chui
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Super-Wavelets and Decomposable Wavelet Frames
Journal of Fourier Analysis and Applications, 2005A wavelet frame is called decomposable whenever it is equivalent to a superwavelet frame of length greater than one. Decomposable wavelet frames are closely related to some problems on super-wavelets. In this article we first obtain some necessary or sufficient conditions for decomposable Parseval wavelet frames.
Gu, Qing, Han, Deguang, Heil, Chris
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, 2000 Despite the previous few chapters, the term “wavelets” usually refers to wavelets on ℝ, examples of which we construct in this chapter. The first two sections present the basics of Fourier analysis on ℝ.
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