Complex discriminative learning Bayesian neural equalizer

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Traditional approaches to channel equalization are based on the inversion of the global (linear or nonlinear) channel response. However, in digital links the complete channel inversion is neither required nor desirable. Since transmitted symbols belong to a discrete alphabet, symbol demodulation can be e ectively recasted as a classi

Mirko Solazzi, Aurelio Uncini, Elio D. Di Claudio,

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Classical Neural Equalizers | Complete Channel Inversion | Hardware | ISCAS 1999 | Neural Equalizers |

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Added	03 Aug 2010
Updated	03 Aug 2010
Type	Conference
Year	1999
Where	ISCAS
Authors	Mirko Solazzi, Aurelio Uncini, Elio D. Di Claudio, Raffaele Parisi

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Complex discriminative learning Bayesian neural equalizer

Classical Neural Equalizers | Complete Channel Inversion | Hardware | ISCAS 1999 | Neural Equalizers |

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