| Paper: | MLSP-P4.1 | ||
| Session: | Audio and Communication Applications | ||
| Time: | Thursday, May 18, 14:00 - 16:00 | ||
| Presentation: | Poster | ||
| Topic: | Machine Learning for Signal Processing: Communications Applications | ||
| Title: | Gaussian Processes for digital communications | ||
| Authors: | Fernando Pérez-Cruz, Gatsby Computational Neuroscience Unit. UCL., United Kingdom; Juan José Murillo-Fuentes, Universidad de Sevilla, Spain | ||
| Abstract: | We present Gaussian Processes (GPs) for Digital communications. GPs can be used to construct analytical nonlinear regression functions, which can be suitable for digital communications in which linear solutions under perform. GPs can be cast as nonlinear MMSE and its hyperparameters can be easily learnt by maximum likelihood. We present some experimental results regarding multi-user detection in CDMA systems and show the GPs outperform linear and nonlinear state-of-the-art solutions. | ||
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