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Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/26359

Title
Estimation of 1/f noise
Author/Creator
Ninness, Brett
Description
Several models have emerged for describing 1/fγ noise processes. Based on these, various techniques for estimating the properties of such processes have been developed. This paper provides theoretical analysis of a new wavelet-based approach which has the advantages of having low computational complexity and being able to handle the case where the 1/fγ noise might be embedded in a further white-noise process. However, the analysis conducted here shows that these advantages are balanced by the fact that the wavelet-based scheme is only consistent for spectral exponents γ in the range γ∈(0, 1). This is in contradiction to the results suggested in previous empirical studies. When γ∈(0, 1) this paper also establishes that wavelet-based maximum-likelihood methods are asymptotically Gaussian and efficient. Finally, the asymptotic rate of mean-square convergence of the parameter estimates is established and is shown to slow as γ approaches one. Combined with a survey of non-wavelet-based methods, these new results give a perspective on the various tradeoffs to be considered when modeling and estimating 1/fγ noise processes.
Relation
IEEE Transactions on Information Theory Vol. 44, Issue 1, p. 32-46
Publisher Link
http://dx.doi.org/10.1109/18.650986
Date
1998
Publisher
Institute of Electrical and Electronics Engineers
Keyword(s)
1/fγ noise processes;  wavelet-based approach;  white-noise process
Resource Type
journal article
Rights
Copyright © 1998 IEEE. Reprinted from IEEE Transactions on Information Theory.
Identifier
http://hdl.handle.net/1959.13/26359
Identifier
ISSN:0018-9448
Reviewed
Reviewed
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Subject
"IEEE Transactions on Information Theory"
 
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