Digital Communication Receivers Using Gaussian Processes for Machine Learning
We propose Gaussian processes (GPs) as a novel nonlinear receiver for digital communication systems. The GPs framework can be used to solve both classification (GPC) and regression (GPR) problems. The minimum mean squared error solution is the expectation of the transmitted symbol given the informat...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2008-07-01
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| Series: | EURASIP Journal on Advances in Signal Processing |
| Online Access: | http://dx.doi.org/10.1155/2008/491503 |