The relevance vector machine technique for channel equalization application

IEEE Transactions on Neural Networks

Volumn 12, Issue 6, 2001, Pages 1529-1532

  Chen, S ^a   Gunn, S R ^a   Harris, C J ^a  

^a UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

Author keywords

Bayesian classification; Equalization; Relevance vector machines (RVMs); Support vector machines (SVMs)

Indexed keywords

ADAPTIVE ALGORITHMS; BIT ERROR RATE; COMMUNICATION CHANNELS (INFORMATION THEORY); PROBABILITY; SIGNAL FILTERING AND PREDICTION; WHITE NOISE;

BAYESIAN CLASSIFICATION; EQUALIZATION; RELEVANCE VECTOR MACHINES; SUPPORT VECTOR MACHINES;

NEURAL NETWORKS;

EID: 0035506174     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/72.963792     Document Type: Letter

References (12)

1. A clustering technique for digital communications channel equalization using radial basis function networks
2. Decision feedback equalizer design using support vector machines
3. Support vector machine techniques for nonlinear equalization
4. The application of support vector machines with Gaussian kernels for overcoming cochannel interference
5. Support vector machine multiuser receiver for DS-CDMA signals in multipath channels
6. The relevance vector machine
7. Bayesian interpolation
8. The evidence framework applied to classification networks
9. Efficient training of RBF networks for classification
10. Adaptive minimum error rate training for neural networks with application to multiuser detection in CDMA communication systems