2008 - Jack S. Kilby Signal Processing Medal For contributions to vector quantization and signal compression techniques.
2008 - IEEE Claude E. Shannon Award
2007 - Member of the National Academy of Engineering For contributions to information theory and data compression.
1981 - Fellow of John Simon Guggenheim Memorial Foundation
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.
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
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.
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.
An Algorithm for Vector Quantizer Design
Y. Linde;A. Buzo;R. Gray.
IEEE Transactions on Communications (1980)
Vector Quantization and Signal Compression
Allen Gersho;Robert M. Gray.
IEEE Assp Magazine (1984)
Entropy and information theory
Robert M. Gray.
Toeplitz and circulant matrices
Robert M. Gray.
Speech coding based upon vector quantization
A. Buzo;A. Gray;R. Gray;J. Markel.
international conference on acoustics, speech, and signal processing (1980)
Entropy-constrained vector quantization
P.A. Chou;T. Lookabaugh;R.M. Gray.
IEEE Transactions on Acoustics, Speech, and Signal Processing (1989)
On the asymptotic eigenvalue distribution of Toeplitz matrices
IEEE Transactions on Information Theory (1972)
An Improvement of the Minimum Distortion Encoding Algorithm for Vector Quantization
Chang-Da Bei;R. Gray.
IEEE Transactions on Communications (1985)
Quantization noise spectra
IEEE Transactions on Information Theory (1990)
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: