2011 - IEEE Fellow For contributions to error-resilient compression systems
His primary areas of study are Algorithm, Multiple description coding, Source code, Data compression and Theoretical computer science. Particularly relevant to Quantization is his body of work in Algorithm. His Multiple description coding study combines topics in areas such as Optimization problem, Mathematical optimization and Encoding.
Vinay A. Vaishampayan works mostly in the field of Data compression, limiting it down to topics relating to Communication channel and, in certain cases, Generalization, Scalar and Block code, as a part of the same area of interest. In his study, Robustness, Wavelet transform and Truncated binary encoding is inextricably linked to Coding, which falls within the broad field of Theoretical computer science. His Decoding methods research incorporates themes from Binary code and Speech recognition.
Vinay A. Vaishampayan mainly focuses on Algorithm, Discrete mathematics, Combinatorics, Decoding methods and Lattice. His studies in Algorithm integrate themes in fields like Encoder, Theoretical computer science, Communication channel and Coding. His Theoretical computer science study incorporates themes from Data compression and Multiple description coding.
His research in Discrete mathematics intersects with topics in Codebook, Multiple description, Rate–distortion theory and Topology. His study in the fields of Lattice under the domain of Combinatorics overlaps with other disciplines such as Differential entropy. His Decoding methods study combines topics from a wide range of disciplines, such as Binary code and Error detection and correction.
His primary scientific interests are in Algorithm, Discrete mathematics, Erasure, Lattice and Probability of error. The concepts of his Algorithm study are interwoven with issues in Upper and lower bounds, Markov process, Base station, Exponential distribution and Scheduling. Vinay A. Vaishampayan has researched Markov process in several fields, including Conditional probability table, Probability distribution, Probability mass function and Theoretical computer science.
His Scheduling research also works with subjects such as
Algorithm, Computer network, Erasure code, Cellular network and Proportionally fair are his primary areas of study. Algorithm and Erasure are two areas of study in which Vinay A. Vaishampayan engages in interdisciplinary research. His work on Distributed data store and Server is typically connected to Concave function and Function as part of general Computer network study, connecting several disciplines of science.
Vinay A. Vaishampayan combines subjects such as Fountain code, Error detection and correction and Online codes, Tornado code, Sequential decoding with his study of Erasure code. His Cellular network research integrates issues from Channel allocation schemes, Channel state information, Scheduling and Base station. His Proportionally fair investigation overlaps with other areas such as Throughput, Communication channel and Leverage.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Design of multiple description scalar quantizers
V.A. Vaishampayan.
IEEE Transactions on Information Theory (1993)
Multiple description coding using pairwise correlating transforms
Yao Wang;M.T. Orchard;V. Vaishampayan;A.R. Reibman.
IEEE Transactions on Image Processing (2001)
Optimal quantizer design for noisy channels: An approach to combined source - channel coding
N. Farvardin;V. Vaishampayan.
IEEE Transactions on Information Theory (1987)
On the performance and complexity of channel-optimized vector quantizers
N. Farvardin;V. Vaishampayan.
IEEE Transactions on Information Theory (1991)
Multiple description wavelet based image coding
S.D. Servetto;K. Ramchandran;V.A. Vaishampayan;K. Nahrstedt.
IEEE Transactions on Image Processing (2000)
Multiple-description vector quantization with lattice codebooks: design and analysis
V.A. Vaishampayan;N.J.A. Sloane;S.D. Servetto.
IEEE Transactions on Information Theory (2001)
Apparatus and method for providing three dimensional media content
Chao Tian;Vinay Anant Vaishampayan;Yifu Zhang.
(2015)
Design of entropy-constrained multiple-description scalar quantizers
V.A. Vaishampayan;J. Domaszewicz.
IEEE Transactions on Information Theory (1994)
Quality monitoring of video over a packet network
A.R. Reibman;V.A. Vaishampayan;Y. Sermadevi.
IEEE Transactions on Multimedia (2004)
Modeling packet-loss visibility in MPEG-2 video
S. Kanumuri;P.C. Cosman;A.R. Reibman;V.A. Vaishampayan.
IEEE Transactions on Multimedia (2006)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:
OEIS Foundation Inc.
Texas A&M University
Purdue University West Lafayette
AT&T (United States)
University of California, Riverside
Purdue University West Lafayette
University of California, Los Angeles
Stevens Institute of Technology
Duke University
Columbia University
Google (United States)
Chinese Academy of Sciences
Carlsberg Laboratory
University of British Columbia
Cornell University
INRAE : Institut national de recherche pour l'agriculture, l'alimentation et l'environnement
Los Alamos National Laboratory
Ikerbasque
University of East Anglia
University of Sydney
Alfred Wegener Institute for Polar and Marine Research
University of Maryland, Baltimore County
National Autonomous University of Mexico
University of New Mexico
Cleveland Clinic
Brown University