Publications

Least Squares Support Vector Machines for Direction of Arrival Estimation with Error Control and Validation

Rohwer, Judd A.; Abdallah, Chaouki T.; Christodoulou, Christos G.

This paper presents a multiclass, multilabel implementation of Least Squares Support Vector Machines (LS-SVM) for direction of arrival (DOA) estimation in a CDMA system. For any estimation or classification system the algorithm's capabilities and performance must be evaluated. Specifically, for classification algorithms a high confidence level must exist along with a technique to automatically tag misclassifications. The learning algorithm presented in this paper includes error control and validation steps for generating statistics on the multiclass evaluation path and the signal subspace dimension. The error statistics provide a confidence level of the classification accuracy.