Recovering or estimating the initial state of a high-dimensional system can require a potentially large number of measurements. In this paper, we explain how this burden can be …
We propose new Bayesian algorithms to automatically track current dipole sources of neural activity in real time. We integrate multiple particle filters to track the dynamic parameters of a …
Abstract Wireless Visual Sensor Networks (WVSNs) have gained significant importance in the last few years and have emerged in several distinctive applications. The main aim is to …
M Najimi, VS Sadeghi - International Journal of Communication …, 2022 - Wiley Online Library
Wireless visual sensor networks (WVSN) have vital roles in surveillance applications. In these networks, wireless visual sensors include camera and transceiver module and collect …
XP Zhang, AS Khwaja, JA Luo… - IEEE Journal of …, 2015 - ieeexplore.ieee.org
In this paper, we present a multiple imputations particle filter (MIPF) to deal with non-linear state estimation when part of the observations are missing. The MIPF uses randomly drawn …
Recovery of the initial state of a high-dimensional system can require a large number of measurements. In this paper, we explain how this burden can be significantly reduced when …
A computationally-efficient method for recovering sparse signals from a series of noisy observations, known as the problem of compressed sensing (CS), is presented. The theory …
In this paper, we propose an application of a compressive imaging system to the problem of wide-area video surveillance systems. A parallel coded aperture compressive imaging …
Many systems for which compressive sensing is used today are dynamical. The common approach is to neglect the dynamics and see the problem as a sequence of independent …