NDLI: Online denoising of discrete noisy data

Content Provider	IEEE Xplore Digital Library
Author	Khadivi, P. Tandon, R. Ramakrishnan, N.
Copyright Year	2015
Description	Author affiliation: Dept. of Comput. Sci., Virginia Tech, Blacksburg, VA, USA (Khadivi, P.; Tandon, R.; Ramakrishnan, N.)
Abstract	Real-time data-driven systems often utilize discrete valued time series data and their functionality is highly dependent on the accuracy of such data. In order to improve the performance of these systems, an important pre-processing step is the denoising of data before performing any action (e.g. forecasting or control activities). Existing algorithms have primarily focused on the offline denoising problem, which requires the entire data to be collected before the denoising process. In this paper, the problem of online discrete denoising is considered. The online denoising problem is motivated by real-time applications, where the data must be utilizable soon after it is collected. Three online denoising algorithms are proposed which can strike a tradeoff between delay and accuracy of denoising. It is also shown that the proposed online algorithms asymptotically converge to a class of optimal offline block denoisers.
Starting Page	671
Ending Page	675
File Size	265684
Page Count	5
File Format	PDF
ISSN	21578117
e-ISBN	9781467377041
DOI	10.1109/ISIT.2015.7282539
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-06-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Noise reduction Context Noise measurement Accuracy Delays Noise Real-time systems Discrete Denoising Online Denoising
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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