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Recent advances in robust self-calibration have made it possible to estimate microphone positions and at least partial sound source positions using ambient sound. However, there are limits on how well sound source paths can be recovered using state-of-the-art techniques. In this paper we develop and evaluate several techniques to extend partial and incomplete solutions. We present minimal solvers

In this paper we propose a novel technique to estimate the parameters of two Gaussian envelope oscillatory signals, with the same time-locations and oscillatory frequencies but possibly different phases. The phase difference and the length of the Gaussian envelope are estimated directly from the slopes of the corresponding cross-spectrogram reassignment vectors. Including the phase difference and

Wireless sensor networks are susceptible to jamming attacks that can result in communication breakdowns. Preemptive measures to prevent jamming attacks is an active research field, but to stop an ongoing attack often requires that one is able to locate jammers in order to neutralize them. Several methods exist for the case when the network is corrupted by a single jammer, although these generally

This paper proposes an iterative algorithm to reconstruct missing samples from non-stationary signals. The proposed algorithm is based on the well-known amplitude-modulation frequency-modulation model for non-stationary signals. The method initially estimates the instantaneous frequencies of the observed multi-component signal. The estimated IFs are then used to de-chirp the corresponding componen

The Amazon forest is increasingly vulnerable to dieback and encroachment of grasslands and agricultural fields. Threats to these forested ecosystems include drying, deforestation, and fire, but feedbacks among these make it difficult to determine their relative importance. Here, we reconstruct the central and western Amazon tree cover response to aridity and fire in the mid-Holocene—a time of less

The multiple-year drought that started in 2011 and reached climax in 2015 was the most severe and prolonged one in the semiarid northeastern (NE) Brazil in recent decades. This study aimed to investigate the reservoir surface water volume (SWV) variation in NE Brazil from 2009 to 2017 in four representative regions covering a total area of approximately 10,000 km2 there and encompassing 2,140 rese

Prior results on target localization and circumnavigation with bearing measurements in $\mathbb {R}^{2}$ are extended with integral action, resulting in a control system that is robust to bounded load disturbances on the control inputs. Such disturbances may arise in practice due to modeling errors and need to be considered to ensure small tracking errors. The control inputs are modeled as the sys

This work considers direction-finding using a monostatic multiple-input multiple-output (MIMO) radar in the presence of impulsive noise. Employing a novel low-order covariance-based exponential kernel function, the proposed maximum likelihood (ML) formulation exploits an introduced quantum whale optimization algorithm (QWOA) to form the direction estimates. The resulting estimates are shown to be

Jump models switch infrequently between states to fit a sequence of data while taking the ordering of the data into account We propose a new framework for joint feature selection, parameter and state-sequence estimation in jump models. Feature selection is necessary in high-dimensional settings where the number of features is large compared to the number of observations and the underlying states d

Understanding the loss surface of neural networks is essential for the design of models with predictable performance and their success in applications. Experimental results suggest that sufficiently deep and wide neural networks are not negatively impacted by suboptimal local minima. Despite recent progress, the reason for this outcome is not fully understood. Could deep networks have very few, if

In this paper we study the problem of estimating receiver and sender positions using time-difference-of-arrival measurements. For this, we use a stratified, two-tiered approach. In the first step the problem is converted to a low-rank matrix estimation problem. We present new, efficient solvers for the minimal problems of this low-rank problem. These solvers are used in a hypothesis and test manne

Given a network of receivers and transmitters, the process of determining their positions from measured pseudoranges is known as network self-calibration. In this paper we consider 2D networks with synchronized receivers but unsynchronized transmitters and the corresponding calibration techniques, known as Time-Difference-Of-Arrival (TDOA) techniques. Despite previous work, TDOA self-calibration i

The task of reconstructing detailed 3D human body models from images is interesting but challenging in computer vision due to the high freedom of human bodies. This work proposes a coarse-to-fine method to reconstruct detailed 3D human body from multi-view images combining Voxel Super-Resolution (VSR) based on learning the implicit representation. Firstly, the coarse 3D models are estimated by lea

In this paper we target the color transfer estimation problem, when we have pixel-to-pixel correspondences. We present a feature-based method, that robustly fits color transforms to data containing gross outliers. Our solution is based on an optimal inlier maximization algorithm that maximizes the number of inliers in polynomial time. We introduce a simple feature detector and descriptor based on

In this paper we present a unified formulation for a large class of relative pose problems with radial distortion and varying calibration. For minimal cases, we show that one can eliminate the number of parameters down to one to three. The relative pose can then be expressed using varying calibration constraints on the fundamental matrix, with entries that are polynomial in the parameters. We can

Ice multiplication by fragmentation during collision-freezing of supercooled rain or drizzle is investigated. A zero-dimensional dynamical system describes the time evolution of number densities of supercooled drops and ice crystals in a mixed-phase cloud. The characteristic time scale for this collision-freezing ice fragmentation is controlled by the collision efficiency, the number of ice fragme

Over the last couple of years both cameras, audio and radio sensors have become cheaper and more common in our everyday lives. Such sensors can be used to create maps of where the sensors are positioned and the appearance of the surroundings. For sound and radio, the process of estimating the sender and receiver positions from time of arrival (TOA) or time-difference of arrival (TDOA) measurements

Real-time fault monitoring and control of the Vacuum Assisted Resin Transfer Moulding production process requires knowledge of the position of the epoxy flow-front inside the mould. Therefore, a fast and accurate flow-front tracking system is highly prized. Physics-informed grey-box models deliver a good trade-off between high fidelity and data-driven black-box models for designing such a flow-fro