TY - GEN
T1 - Simplified wavelet-domain hidden Markov models using contexts
AU - Crouse, Matthew S.
AU - Baraniuk, Richard G.
N1 - Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 1998
Y1 - 1998
N2 - Wavelet-domain hidden Markov models (HMMs) are a potent new tool for modeling the statistical properties of wavelet transforms. In addition to characterizing the statistics of individual wavelet coefficients, HMMs capture the salient interactions between wavelet coefficients. However, as we model an increasing number of wavelet coefficient interactions, HMM-based signal processing becomes increasingly complicated. In this paper, we propose a new approach to HMMs based on the notion of context. By modeling wavelet coefficient inter-dependencies via contexts, we retain the approximation capabilities of HMMs, yet substantially reduce their complexity. To illustrate the power of this approach, we develop new algorithms for signal estimation and for efficient synthesis of nonGaussian, long-range-dependent network traffic.
AB - Wavelet-domain hidden Markov models (HMMs) are a potent new tool for modeling the statistical properties of wavelet transforms. In addition to characterizing the statistics of individual wavelet coefficients, HMMs capture the salient interactions between wavelet coefficients. However, as we model an increasing number of wavelet coefficient interactions, HMM-based signal processing becomes increasingly complicated. In this paper, we propose a new approach to HMMs based on the notion of context. By modeling wavelet coefficient inter-dependencies via contexts, we retain the approximation capabilities of HMMs, yet substantially reduce their complexity. To illustrate the power of this approach, we develop new algorithms for signal estimation and for efficient synthesis of nonGaussian, long-range-dependent network traffic.
UR - http://www.scopus.com/inward/record.url?scp=0031628803&partnerID=8YFLogxK
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U2 - 10.1109/ICASSP.1998.681603
DO - 10.1109/ICASSP.1998.681603
M3 - Conference contribution
AN - SCOPUS:0031628803
SN - 0780344286
SN - 9780780344280
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 2277
EP - 2280
BT - Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 1998
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 1998 23rd IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 1998
Y2 - 12 May 1998 through 15 May 1998
ER -