M. Goodwin and M. Vetterli, "Atomic decompositions of audio signals," in Proc. IEEE ASSP Workshop Appl. Signal Process. Audio Acoust., Oct. 1997. Home/Search Document Details and Download
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Matching Pursuit and Atomic Signal Models Based on Recursive .. - Goodwin, Vetterli (1999) (5 citations) Self-citation (Goodwin Vetterli) (Correct)
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M. Goodwin and M. Vetterli, "Atomic decompositions of audio signals," in Proc. IEEE ASSP Workshop Appl. Signal Process. Audio Acoust., Oct. 1997.
Matching Pursuit and Atomic Signal Models Based on Recursive .. - Goodwin, Vetterli (1902) (5 citations) Self-citation (Goodwin Vetterli) (Correct)
....atoms constructed by coupling causal and anticausal damped sinusoids. In Section VII, computational costs are considered. Section VIII provides a summary of the paper and discusses directions for future research. Some of the results herein have been presented in preliminary form in [6] 21] [22]. II. Signal Decompositions In signal processing applications it is often useful to decompose a signal into elementary building blocks. In such a decomposition, a signal x[n] is represented as a linear combination of expansion functions dm [n] x[n] M X m=1 ff m dm [n] 1) which can be ....
....The shortcoming of basis expansions results from the attempt to represent arbitrary signals using a limited set of functions. Better models can be derived by using expansion functions that are signal adaptive; this can be achieved by using a parametric approach such as the sinusoidal model [6] [22], 23] or by choosing the expansion functions in a signal dependent fashion from an overcomplete set of time frequency atoms as in adaptive wavelet packets or matching pursuit [3] 6] 10] The term overcomplete refers to a set of vectors that spans the signal space but includes more functions ....
M. Goodwin and M. Vetterli. Atomic decompositions of audio signals. Proceedings of the IEEE ASSP Workshop on Applications of Signal Processing to Audio and Acoustics, October 1997.
Adaptive Signal Models: Theory, Algorithms, and Audio Applications - Goodwin (1997) (2 citations) Self-citation (Goodwin) (Correct)
....basis expansions result from the attempt to represent arbitrary signals in terms of a very limited set of functions. Better representations can be derived by using expansion functions that are signal adaptive; signal adaptivity can be achieved via parametric approaches such as the sinusoidal model [57, 36, 62], by using adaptive wavelet packets or best basis methods [40, 41, 60] or by choosing the expansion functions from an overcomplete set of time frequency atoms [38] These are fundamentally all examples of expansions based on an overcomplete set of vectors; this section focuses on the latter two, ....
....models and related algorithms. 1.6.2 Themes This thesis has a number of underlying and recurring themes. In a sense, this text is about the relationships between these themes. The basic conceptual framework of this thesis has been central to several preliminary presentations in the literature [91, 62], but in this document the various issues are explored in greater detail; furthermore, considerable 31 attention is given to review of fundamental background material. The themes of this thesis are as follows. Filter banks and multiresolution Filter bank theory and design appear in several ....
M. Goodwin and M. Vetterli, "Atomic decompositions of audio signals," in Proceedings of the IEEE ASSP Workshop on Applications of Signal Processing to Audio and Acoustics, October 1997.
Matching Live Sources With Physical Models - Paul Brossier Mark (Correct)
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M. Goodwin and M. Vetterli, "Atomic decompositions of audio signals," in Proc. IEEE Workshop on Audio Signal Processing, 1997.
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