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2005, Monographs on statistics and applied probability (Series), ISBN 9781584884323, Volume 104, 263
Gaussian Markov Random Field (GMRF) models are most widely used in spatial statistics - a very active area of research in which few up-to-date reference works... 
Gaussian Markov random fields | Statistical Theory & Methods | Statistical Computing | Geostatistics
Book
IEEE Transactions on Aerospace and Electronic Systems, ISSN 0018-9251, 10/2011, Volume 47, Issue 4, pp. 2376 - 2390
Journal Article
IEEE transactions on information theory, ISSN 1557-9654, 04/2019, Volume 65, Issue 4, pp. 2492 - 2506
It is well known that the problem of computing the feedback capacity of a stationary Gaussian channel can be recast as an infinite-dimensional optimization... 
Limiting | Gaussian feedback capacity | Channel capacity | Gaussian noise | Feedback capacity | stationary Gaussian channel | Gaussian processes | Covariance matrices | Optimization | Zinc | Random noise | Gaussian process | Algorithms | Noise | Feedback | Normal distribution | Autoregressive moving average | Dimensional changes | Polynomials | Autoregressive processes
Journal Article
01/2017, ISBN 0412051710, 629
This book serves as a standard reference, making this area accessible not only to researchers in probability and statistics, but also to graduate students and... 
Gaussian distribution | Gaussian processes
Book
2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP), ISSN 2161-0363, 09/2016, Volume 2016-, pp. 1 - 6
This paper provides an algorithm for simulating improper (or noncircular) complex-valued stationary Gaussian processes. The technique utilizes recently... 
Gaussian noise | noncircular | Signal processing algorithms | Gaussian processes | improper | Circulant embedding | Eigenvalues and eigenfunctions | Matrix decomposition | complex-valued | Covariance matrices | fractional Gaussian noise
Conference Proceeding
Computer speech & language, ISSN 0885-2308, 04/2011, Volume 25, Issue 2, pp. 404 - 439
We describe a new approach to speech recognition, in which all Hidden Markov Model (HMM) states share the same Gaussian Mixture Model (GMM) structure with the... 
Subspace Gaussian Mixture Model | Gaussian Mixture Model | Speech recognition | Computer Science, Artificial Intelligence | Technology | Computer Science | Science & Technology | Voice recognition | Markov processes | Models | Mathematical analysis | C (programming language) | Speech | Gaussian | Mathematical models | Vectors (mathematics) | Standards
Journal Article
IEEE Transactions on Image Processing, ISSN 1057-7149, 05/2014, Volume 23, Issue 5, pp. 2246 - 2261
Journal Article