NDLI: Generalized approximate message passing estimation from quantized samples

Content Provider	IEEE Xplore Digital Library
Author	Kamilov, U. Goyal, V.K. Rangan, S.
Copyright Year	2011
Description	Author affiliation: EPFL, Switzerland (Kamilov, U.) \|\| Polytechnic University of New York University, USA (Rangan, S.) \|\| Massachusetts Institute of Technology, USA (Goyal, V.K.)
Abstract	Estimation of a vector from quantized linear measurements is a common problem for which simple linear techniques are sometimes greatly suboptimal. This paper summarizes the development of generalized approximate message passing (GAMP) algorithms for minimum mean-squared error estimation of a random vector from quantized linear measurements, notably allowing the linear expansion to be overcomplete or undercomplete and the scalar quantization to be regular or non-regular. GAMP is a recently-developed class of algorithms that uses Gaussian approximations in belief propagation and allows arbitrary separable input and output channels. Scalar quantization of measurements is incorporated into the output channel formalism, leading to the first tractable and effective method for high-dimensional estimation problems involving non-regular scalar quantization. Non-regular quantization is empirically demonstrated to greatly improve rate-distortion performance in some problems with oversampling or with undersampling combined with a sparsity-inducing prior. Under the assumption of a Gaussian measurement matrix with i.i.d. entries, the asymptotic error performance of GAMP can be accurately predicted and tracked through the state evolution formalism.
Starting Page	365
Ending Page	368
File Size	236461
Page Count	4
File Format	PDF
ISBN	9781457721045
e-ISBN	9781457721052
DOI	10.1109/CAMSAP.2011.6136027
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-12-13
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Message passing Estimation Quantization Approximation algorithms Distortion measurement Slabs Belief propagation
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
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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