Narayan Kovvali

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Probability hypothesis density (PHD) filtering, implemented using particle filters, is a Bayesian technique used to non-linearly track multiple objects. In this paper, we propose a new approach based on PHD particle filters (PHD-PF) to automatically track the number of magnetoencephalography (MEG) neural dipole sources and their unknown states. In(More)
The effective and reliable detection of explosive compounds in complex environments is an important problem in many environment and security-related applications. This paper develops an explosive detection approach based on multi-modal sensing and sensor data fusion. A least-squares feature extraction technique is designed to isolate explosive signatures in(More)