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Digital pulse shape discrimination (PSD) systems are widely used to extract various kinds of information from the shape of output pulses of radiation detectors. Such systems replace the traditional analog PSD circuits with numerical algorithms running on a digital processor, which makes them more flexible for implementing various PSD methods. However, the available digital PSD algorithms have been generally tailored to the characteristics of the concerned detectors, which limit their general use. Here, for the purpose of building a general-purpose digital PSD module, we present a PSD algorithm that, with minimum alterations, can be used with a wide range of radiation detectors. Our approach is based on using the cosine similarity measure to quantify the variations in the shape of detectors’ pulses with respect to the shape of a unit step pulse. The method is described in detail, and the results of the test experiments with different types of radiation detectors, including a boron tetrafluoride (BF3) proportional counter, a liquid scintillation detector, and high purity germanium (HPGe) detector are shown. The performance of the algorithm is also compared to that of the common rise time discrimination method. [ABSTRACT FROM AUTHOR]

Abstract In this paper, a specific reduced-channel Acoustic Vector Sensor (AVS) is proposed comprising one omni-directional microphone and only one particle velocity transducer, such that it can have an arbitrary orientation. Such a reduced transducer configuration is referred to as a Uniaxial AVS (U-AVS). The DOA performance of an array of U-AVSs is analyzed through its beampattern and compared to conventional configurations. It is shown that the U-AVS array beampattern results in an asymptotically biased estimate of the source location and it can be varied by choosing the orientation angles of the particle velocity transducers. Analytical expressions for the asymptotic bias of classical beamforming are proposed and verified both numerically as well as experimentally for Uniform Linear Arrays (ULAs). Furthermore, the Cramér-Rao Bound (CRB) and Mean Square Error (MSE) expressions are derived for a U-AVS array under a single source scenario and they are numerically evaluated for ULA. The implications of changing the orientations of the U-AVSs in the array on the MSE are discussed as well. [ABSTRACT FROM AUTHOR]

The problem of reconstructing a sparse signal vector from magnitude-only measurements (a.k.a. compressive phase retrieval) emerges in diverse applications, but it is NP-hard in general. Building on recent advances in nonconvex optimization, this paper puts forth a new algorithm that is termed compressive reweighted amplitude flow (CRAF) and abbreviated as CRAF, for compressive phase retrieval. Specifically, CRAF operates in two stages. The first stage seeks a sparse initial guess via a new spectral procedure. In the second stage, CRAF implements a few hard thresholding based iterations using reweighted gradients. When there are sufficient measurements, CRAF provably recovers the underlying signal vector exactly with high probability under suitable conditions. Moreover, its sample complexity coincides with that of state-of-the-art procedures. Finally, numerical tests showcase improved performance of the new spectral initialization, as well as improved exact recovery relative to competing alternatives. Empirically, the number of measurements required for exact recovery by CRAF is about 40% less than those of competing alternatives in our experiments using real images. [ABSTRACT FROM AUTHOR]

We consider the minimax detection problem for a Gaussian random signal vector in white Gaussian additive noise. It is assumed that an unknown vector σ of signal vector intensities belongs to a given set ε. We investigate when it is possible to replace the set ε with a smaller set ε without loss of quality (and, in particular, replace it with a single point σ ). [ABSTRACT FROM AUTHOR]

Algorithms for locomotion mode recognition (LMR) based on surface electromyography and mechanical sensors have recently been developed and could be used for the neural control of powered prosthetic legs. However, the variations in input signals, caused by physical changes at the sensor interface and human physiological changes, may threaten the reliability of these algorithms. This study aimed to investigate the effectiveness of applying adaptive pattern classifiers for LMR. Three adaptive classifiers, i.e., entropy-based adaptation (EBA), LearnIng From Testing data (LIFT), and Transductive Support Vector Machine (TSVM), were compared and offline evaluated using data collected from two able-bodied subjects and one transfemoral amputee. The offline analysis indicated that the adaptive classifier could effectively maintain or restore the performance of the LMR algorithm when gradual signal variations occurred. EBA and LIFT were recommended because of their better performance and higher computational efficiency. Finally, the EBA was implemented for real-time human-in-the-loop prosthesis control. The online evaluation showed that the applied EBA effectively adapted to changes in input signals across sessions and yielded more reliable prosthesis control over time, compared with the LMR without adaptation. The developed novel adaptive strategy may further enhance the reliability of neurally-controlled prosthetic legs. [ABSTRACT FROM AUTHOR]

A framework is presented in this paper for the control of a multisensor robot under several constraints. In this approach, the features coming from several sensors are treated as a single feature vector. The core of our approach is a weighting matrix that balances the contribution of each feature, allowing the taking of constraints into account. The constraints are considered as additional features that are smoothly injected in the control law. Multisensor modeling is introduced for the design of the control law, drawing similarities with linear quadratic control. The main properties are exposed and we propose several strategies to cope with the main drawbacks. The framework is validated in a complex experiment, illustrating various aspects of the approach. The goal is the positioning of a six-DOF robot arm with 3-D visual servoing. The considered constraints are both eye-in-hand and eye-to-hand visibility, together with joint limit avoidance. The system is thus highly overdetermined, yet the task can be performed while ensuring several combinations of constraints. [ABSTRACT FROM PUBLISHER]

This paper addresses the problem of fault estimation and fault-tolerant control for a class of Takagi–Sugeno (T–S) fuzzy Itô stochastic systems subject to simultaneously sensor and actuator faults. The main difficulty in this study is that sensor faults, actuator faults, and stochastic noise that are governed by Brownian motion are taken into simultaneous consideration in a unified framework, and traditional fault-tolerant approaches are not effective to solve this research issue. A new descriptor fuzzy sliding-mode observer approach is presented in this paper to obtain the simultaneous estimates of system state, sensor fault, and actuator fault vectors. Based on the state estimates, an observer-based fault-tolerant control (FTC) scheme is developed to stabilize the resulting closed-loop system. Finally, a simulation example is provided to show the effectiveness of the proposed fault-tolerant approach. [ABSTRACT FROM AUTHOR]

An important task in sensor networks is to sense locally to detect global properties that hold at some instant in physical time, namely, Instantaneously. We propose software logical clocks, called strobe clocks, that can be implemented by the middleware when synchronized physical clocks are not available or are too expensive in resource-constrained environments. Strobe clocks come in two flavors--scalar and vector. Let $(n)$ be the number of sensors and $(p)$ be the upper bound on the number of relevant events sensed at a sensor. We propose an algorithm using vector strobes that can detect all occurrences of a conjunctive predicate in time $(O(n^3p))$. The algorithm has some false negatives but this is the best achievable accuracy in the face of race conditions. We also present a variant algorithm using scalar strobes; it needs time $(O(n^2p))$ but may also suffer from some false positives. We provide a characterization of the errors. Both algorithms can also detect relational predicates but with a greater chance of error. The message complexity of strobe clocks (scalar and vector) and both algorithms is $(O(np))$, which is the same as that of reporting each sensed event for detection of the predicate even with synchronized physical clocks. We formalize the physical time modality, Instantaneously, and show its relationship to the logical time modalities Definitely and Possibly. [ABSTRACT FROM AUTHOR]

A new code aperture design framework for multiframe code aperture snapshot spectral imaging (CASSI) system is presented. It aims at the optimization of code aperture sets such that a group of compressive spectral measurements is constructed, each with information from a specific subset of bands. A matrix representation of CASSI is introduced that permits the optimization of spectrally selective code aperture sets. Furthermore, each code aperture set forms a matrix such that rank minimization is used to reduce the number of CASSI shots needed. Conditions for the code apertures are identified such that a restricted isometry property in the CASSI compressive measurements is satisfied with higher probability. Simulations show higher quality of spectral image reconstruction than that attained by systems using Hadamard or random code aperture sets. [ABSTRACT FROM AUTHOR]

This paper concerns a classification problem of 3D shapes being in motion. The goal is to develop the system with real-time capabilities to distinguish basic shapes (corners, planes, cones, spheres etc.) that are moving in front of RGB-D sensor. It is introduced an improvement of 'SoA al-gorithms (normal vector computation using PC A Principal Component Analysis and SVD Singular Value Decomposi-tion, PFH - Point Feature Histogram) based on GPGPU (General Purpose Graphic Processor Unit) computation. This approach guarantee on-line computation of normal vectors, unfortunately computation time of the PFH for each normal vector is still a challenge to obtain on-line ca-pabilities, therefore in this paper it is shown how to find a region of movement and to perform the classification process assuming the decreased amount of data. Proposed approach can be a starting point for further developments of the systems able to recognize the objects in the dynamic environments. [ABSTRACT FROM AUTHOR]

Transient dynamic behavior of Magneto-electro-elastic (MEE) sensors bonded to a mild steel plate using 3D magnetic vector potential approach is presented. The electric field induced by time varying magnetic field is non-conservative and can be described by electric scalar potential and magnetic vector potentials. The aim of the study is to find how different volume fractions of the MEE composite behave in sensor applications at various locations on the plate subjected to different boundary conditions. The 3D plate and the sensor are modeled using eight nodded brick element with sufficient numbers of elements across the thickness direction to capture the bending behavior of the plate correctly. The four boundary conditions chosen are one symmetric boundary condition (CCCC), one free edge (CCFC), two adjacent free edges (CFFC) and two opposite free edges (FCFC). It is seen that the electric response is maximum when volume fraction vf=0.2 for all sensor locations with different boundary conditions. The boundary conditions significantly influence the magnetic response; volume fraction vf=0.4 gives noticeably higher values of magnetic potential in almost all the cases except for CFFC boundary condition with sensor near the edge and FCFC boundary condition with sensor at an off set distance from the edge. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editors discuss various reports within the issue on topics including Euclidean vectors, algorithms, and time difference of arrival (TDOA) sensors.