Statistical Learning Theory and State of the Art in SVM
ICCI '03 Proceedings of the 2nd IEEE International Conference on Cognitive Informatics
Detection of FHMA/MFSK signals based on SVM techniques
Proceedings of the 2006 international conference on Wireless communications and mobile computing
Nonlinear multiantenna detection methods
EURASIP Journal on Applied Signal Processing
Adaptive minimum error-rate filtering design: A review
Signal Processing
Digital communication receivers using gaussian processes for machine learning
EURASIP Journal on Advances in Signal Processing
Gaussian process regressors for multiuser detection in DS-CDMA systems
IEEE Transactions on Communications
Adaptive minimum bit error rate beamforming assisted receiver for QPSK wireless communication
Digital Signal Processing
Application of support vector machines to bandwidth reservation in sectored cellular communications
Engineering Applications of Artificial Intelligence
Reduced RBF centers based multi-user detection in DS-CDMA systems
ICHIT'06 Proceedings of the 1st international conference on Advances in hybrid information technology
Low-complexity equalization based on least squares support vector classifiers for DS-UWB systems
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Blind multiuser detector for chaos-based CDMA using support vector machine
IEEE Transactions on Neural Networks
Probabilistic tangent subspace method for multiuser detection
ICAPR'05 Proceedings of the Third international conference on Advances in Pattern Recognition - Volume Part I
Blind multiuser detection based on kernel approximation
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part III
Least squares support vector machines for bandwidth reservation in wireless IP networks
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
A unified SVM framework for signal estimation
Digital Signal Processing
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The problem of constructing an adaptive multiuser detector (MUD) is considered for direct sequence code division multiple access (DS-CDMA) signals transmitted through multipath channels. The emerging learning technique, called support vector machines (SVM), is proposed as a method of obtaining a nonlinear MUD from a relatively small training data block. Computer simulation is used to study this SVM MUD, and the results show that it can closely match the performance of the optimal Bayesian one-shot detector. Comparisons with an adaptive radial basis function (RBF) MUD trained by an unsupervised clustering algorithm are discussed