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In this paper, we address the problem of robust adaptive beamforming of signals received by a linear array. The challenge associated with the beamforming problem is twofold. Firstly, the process requires the inversion of the usually ill-conditioned covariance matrix of the received signals. Secondly, the steering vector pertaining to the direction of arrival of the signal of interest is not known precisely. To tackle these two challenges, the standard capon beamformer is manipulated to a form where the beamformer output is obtained as a scaled version of the inner product of two vectors.

In this poster, we propose to face the problem of event detection from single images, by exploiting both background information often containing revealing contextual clues and details, which are salient for recognizing the event. Such details are visual objects critical to understand the underlying event depicted in the image and were recently defined in the literature as ”event-saliency”. Adopting the Multiple-Instance Learning (MIL) paradigm we propose a hierarchical approach analyzing first the entire picture and then refining the decision on the basis of the event-salient objects.

Frequency estimation, especially with sampling rates below the Nyquist rate, has abundant applications in engineering. Recently, Chinese remainder theorem(CRT)-based frequency reconstruction from undersampled complex-value waveforms becomes one of the frontier focuses in the fields of signal processing, electromagnetism and optics etc. In this paper, we present several CRT-based algorithms for determining multiple frequencies via symmetric polynomials. The computational complexity of these algorithms is in the polynomial class (P).

In heterogeneous networks (HetNets) system, the exploitation of small cells (SCs) will be enhanced spectral efficiency that means guarantee QoS and coverage area to user terminals. We propose a joint linear precoder designproblem to maximize the energy efficiency of the HetNet model. To tackle the cross-tier interference in the HetNets, we exploit zero-forcing precoding where the interference at the users is cancelled out by block diagonalization scheme.

We present a novel, three-stage method to solve the fluorescence lifetime imaging problem under low-photon conditions. In particular, we reconstruct the fluorophore concentration along with its support and fluorescence lifetime from the time-dependent measurements of scattered light exiting the domain. Because detectors used for these problems are photon counting devices, measurements are corrupted by Poisson noise. Consequently, we explicitly consider Poisson noise in conjunction with SPIRAL-$\ell_p$ -- a sparsity-promoting nonconvex optimization method -- to solve this problem.

In this paper, we propose a new characteristic measure for relative people density and motion dynamics for the purpose of long-term crowd monitoring. While many related works focus on direct people counting and absolute density estimation, we will show that relative densities provide reliable information on crowd behaviour. Furthermore, we will discuss the derivation of a so-called Congestion Level of local areas in the crowd, which takes the current dynamics and density within a certain image region into account.

This paper investigates cyber-attacks compromising the data integrity of 100% inverter-interfaced islanded microgrids featuring an energy storage system (ESS), a wind turbine generator (WTG), a photovoltaic system (PV) and controllable loads. The ESS operates as the isochronous generator, responsible for forming the microgrid voltage and frequency, whereas the WTG and PV distributed energy resources (DER) operate in maximum-power-point-tracking (MPPT) mode.

We study the problem of remote reconstruction of a continuous signal from its multiple corrupted versions. We are interested in the optimal number of samples and their locations for each corrupted signal to minimize the total reconstruction distortion of the remote signal. The correlation among the corrupted signals can be utilized to reduce the sampling rate.