Lack of robustness against noise uncertainty is a bottleneck of current spectrum sensing strategies to detect the primary signals. Due to noise uncertainty, the performance of tra...
This study develops a least squares support vector machines (LS-SVM) based model for bivariate process to diagnose abnormal patterns of process mean vector, and to help identify a...
In recent years, compressive sensing attracts intensive attentions in the field of statistics, automatic control, data mining and machine learning. It assumes the sparsity of the ...
In this paper, a new particle filter (PF) which we refer to as the decentralized PF (DPF) is proposed. By first decomposing the state into two parts, the DPF splits the filtering p...
—Detection of the number of sinusoids embedded in noise is a fundamental problem in statistical signal processing. Most parametric methods minimize the sum of a data fit (likeli...