H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 71 Citations 46,961 252 World Ranking 758 National Ranking 464

Research.com Recognitions

Awards & Achievements

2008 - IEEE Claude E. Shannon Award

2008 - Jack S. Kilby Signal Processing Medal For contributions to vector quantization and signal compression techniques.

2007 - Member of the National Academy of Engineering For contributions to information theory and data compression.

1981 - Fellow of John Simon Guggenheim Memorial Foundation

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Artificial intelligence
  • Algorithm

His main research concerns Algorithm, Vector quantization, Quantization, Artificial intelligence and Speech coding. Robert M. Gray has included themes like Information theory, Theoretical computer science and Coding in his Algorithm study. Robert M. Gray is involved in the study of Vector quantization that focuses on Linde–Buzo–Gray algorithm in particular.

His Quantization research integrates issues from Linear prediction, Descent algorithm, Nonlinear programming and Learning vector quantization. His biological study spans a wide range of topics, including Measure, Computer vision and Pattern recognition. His study in Speech coding is interdisciplinary in nature, drawing from both Algorithm design, Computation and Speech processing.

His most cited work include:

  • An Algorithm for Vector Quantizer Design (7039 citations)
  • Vector Quantization and Signal Compression (5749 citations)
  • Vector quantization (2710 citations)

What are the main themes of his work throughout his whole career to date?

The scientist’s investigation covers issues in Vector quantization, Artificial intelligence, Algorithm, Pattern recognition and Quantization. His research integrates issues of Codebook, Image compression and Data compression in his study of Vector quantization. His research on Artificial intelligence often connects related topics like Computer vision.

His Algorithm study also includes

  • Theoretical computer science which intersects with area such as Decoding methods,
  • Mathematical optimization which is related to area like Entropy. His work carried out in the field of Pattern recognition brings together such families of science as Contextual image classification and Markov model. As a part of the same scientific family, he mostly works in the field of Quantization, focusing on Speech coding and, on occasion, Speech processing.

He most often published in these fields:

  • Vector quantization (35.22%)
  • Artificial intelligence (35.22%)
  • Algorithm (28.76%)

What were the highlights of his more recent work (between 2003-2020)?

  • Artificial intelligence (35.22%)
  • Pattern recognition (26.34%)
  • Entropy (9.41%)

In recent papers he was focusing on the following fields of study:

Robert M. Gray mainly investigates Artificial intelligence, Pattern recognition, Entropy, Algorithm and Vector quantization. His Artificial intelligence research is multidisciplinary, relying on both Markov model and Computer vision. The various areas that Robert M. Gray examines in his Pattern recognition study include Contextual image classification and Cluster analysis.

His work deals with themes such as Block code, Data compression, Rate–distortion theory and Asymptotically optimal algorithm, Mathematical optimization, which intersect with Entropy. In his research, Theoretical computer science is intimately related to Signal processing, which falls under the overarching field of Algorithm. His Vector quantization research includes elements of Codebook, Distortion and Quantization.

Between 2003 and 2020, his most popular works were:

  • Coding for noisy channels (433 citations)
  • An introduction to statistical signal processing (175 citations)
  • Image retrieval using color histograms generated by Gauss mixture vector quantization (112 citations)

In his most recent research, the most cited papers focused on:

  • Statistics
  • Artificial intelligence
  • Algorithm

Robert M. Gray mostly deals with Artificial intelligence, Pattern recognition, Algorithm, Entropy and Quantization. His study focuses on the intersection of Artificial intelligence and fields such as Computer vision with connections in the field of Noise measurement. His Pattern recognition research integrates issues from Markov chain, Markov model and Cluster analysis.

His studies in Algorithm integrate themes in fields like Communication channel, Channel capacity, Synchronization, Conditional probability distribution and Coding. His studies deal with areas such as Asymptotically optimal algorithm, Mathematical optimization and Data compression, Rate–distortion theory as well as Entropy. His research in Quantization focuses on subjects like Vector quantization, which are connected to Distortion, Color image and Color quantization.

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.

Top Publications

An Algorithm for Vector Quantizer Design

Y. Linde;A. Buzo;R. Gray.
IEEE Transactions on Communications (1980)

10744 Citations

Vector Quantization and Signal Compression

Allen Gersho;Robert M. Gray.
(1991)

9317 Citations

Vector quantization

R. Gray.
IEEE Assp Magazine (1984)

4332 Citations

Toeplitz and circulant matrices

Robert M. Gray.
(1977)

2707 Citations

Entropy and information theory

Robert M. Gray.
(1990)

2310 Citations

Speech coding based upon vector quantization

A. Buzo;A. Gray;R. Gray;J. Markel.
IEEE Transactions on Acoustics, Speech, and Signal Processing (1980)

905 Citations

Entropy-constrained vector quantization

P.A. Chou;T. Lookabaugh;R.M. Gray.
IEEE Transactions on Acoustics, Speech, and Signal Processing (1989)

831 Citations

Coding for noisy channels

Robert M. Gray.
(2011)

665 Citations

On the asymptotic eigenvalue distribution of Toeplitz matrices

R. Gray.
IEEE Transactions on Information Theory (1972)

656 Citations

An Improvement of the Minimum Distortion Encoding Algorithm for Vector Quantization

Chang-Da Bei;R. Gray.
IEEE Transactions on Communications (1985)

656 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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