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arXiv · 1011.0786

Gaussian Process Techniques for Wireless Communications

Mr. Chong Han·Dr. Ido Nevat·Dr. Gareth Peters·Prof. Jinhong Yuan
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Abstract

Bayesian filtering is a general framework for recursively estimating the state of a dynamical system. Classical solutions such that Kalman filter and Particle filter are introduced in this report. Gaussian processes have been introduced as a non-parametric technique for system estimation from supervision learning. For the thesis project, we intend to propose a new, general methodology for inference and learning in non-linear state-space models probabilistically incorporating with the Gaussian process model estimation.

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Mr. Chong Han, Dr. Ido Nevat, Dr. Gareth Peters, Prof. Jinhong Yuan. 2010-11-03. Gaussian Process Techniques for Wireless Communications. https://arxiv.org/abs/1011.0786

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