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We study the problem of decomposing a measured signal as a sum of decaying exponentials. There is a direct connection to sums of these types and positive semi-definite (PSD) Hankel matrices, where the rank of these matrices equals the number of exponentials. We propose to solve the identification problem by forming an optimization problem with a misfit function combined with a rank penalty function...
Bistatic MIMO radar has become an active research area in recent years. In this paper, linear prediction combining with eigenvalue decomposition is applied to DOD and DOA estimation of bistatic MIMO radar. Firstly, according to signal model, the output signals of receivers are depicted by transceiver combing steering vector which is the kronecker product of receiving steering vector and transmitting...
A Method of source number detection and estimation direction of arrival (DOA) is applied to detect the passive target of under water in low signal-to-noise ratio (SNR) condition. Firstly, the combined covariance matrix of the pressure and particle velocity with uniform circular acoustic vector sensor array is constructed. Then, diagonal loading is used to make a robust estimation. Finally, the information...
In this paper, we mainly address the problem of Joint EigenValue Decomposition (JEVD) subject to nonnegative constraints on the eigenvalues of the matrices to be diagonalized. An efficient method based on the Alternating Direction Method of Multipliers (ADMM) is designed. ADMM provides an elegant approach for handling nonnegativity constraints, while taking advantage of the structure of the objective...
This paper studies how to sample load more realistically and efficiently for security constraint unit commitment (SCUC) problems in order to achieve a high degree of robustness of the unit commitment (UC) solution. For example, given the UC solution, 95% of load profiles can be supplied. Principal component analysis (PCA) is introduced to find a clear feature of the historical load in two-dimensional...
A robust stability assessment approach is presented to efficiently estimate eigenvalues in microgrids in the presence of bounded uncertainties. Through this method, all possible locations of eigenvalues can be directly obtained, which makes repeatedly eigenvalue calculation unnecessary when dealing with uncertainties. More importantly, a quasi-diagonalization technique is established to reduce the...
In this paper,we propose a sparse Baysesian learning (SBL) based approach for the DOA estimation in the presence of coherent sources. First, the difference technique is used to enhance the input SNR. Then, we construct a virtual array manifold to eliminate the cross-term effect between each coherent group, after eigenvalue decomposition (EVD) of the difference covariance matrix, reduce the dimension...
Harmonic resonance, which is a main concern in power quality, may cause damage of equipments in power system, and consequently affect stable operation of power grid. In addition, with the continued growth of distributed generators and controllable FACTS devices,for example SVCs, in power grid, harmonic resonance becomes more complicated as frequent changes of their equivalent harmonic impedance parameters...
This manuscript focuses on velocity estimation for synthetic aperture radar (SAR) in high-resolution wide-swath mode. HRWS mode is proposed to overcome the system-inherent limitation, which allows for collecting additional samples under relatively low PRF. Unlike the previous work of SAR ground moving target indication (GMTI) in single channel and multiple channels, the velocity estimation in HRWS...
Spectrum sensing is a fundamental technique of cognitive radio (CR) system to detect the presence of primary user (PU) transmissions in the licensed spectrum. This paper investigates secondary user (SU) selection based cooperative spectrum sensing under exponentially embedded family (EEF) criterion. With an aim to estimate the optimal number of cooperative users who are better fitting for participating...
In this paper we present a new approach for the automatic reconstruction of seismic horizons and the generation of a pseudo-geological time cube. Our method can accomodate user constraints and relies on the computation of a local Riemannian metric on the seismic image, whose geodesic lines correspond to seismic horizons. The parameterization chosen in our method eases some of the restrictions imposed...
In this paper we develop an algorithm that can detect the identity of false data-injection attackers in distributed optimization loops for estimating oscillation modes in large power system models. The fundamental set-up for this distributed optimization is based on Alternating Direction Multiplier Method (ADMM). The power system is divided into multiple non-overlapping areas, each equipped with a...
Unification of spatial brain dynamics in multiclass brain computer interface (BCI) paradigm reduces computational latencies by using lesser number of electrodes from the sensorimotor regions of the brain. We employ reduced number of channels without compromising performance notably. We apply three spatial filtering methods, i.e., Common Spatial Pattern (CSP), Regularized Common Spatial Pattern (RCSP)...
Two estimation algorithms for the spreading sequence in DSSS signals are proposed. Some of previously proposed algorithms have some drawbacks such as large computational complexity, low estimation accuracy and poor accuracy by increasing the length of spreading sequence period. In this paper by using an initial estimate of chips, we can improve recursively the final decision with low computational...
Common Spatial Pattern (CSP) is one of the popular and effective methods for discriminating two class electroencephalogram (EEG) measurements. Its probabilistic counterpart by resolving the problem of overfitting as the main limitation of CSP attracted much attention, especially in the motor imaginary based brain computer interface (BCI) applications. Since the computational efficiency is a paramount...
Two algorithms for the problem of joint angles and delays of arrival (JADE) of multiple paths are presented. The algorithms are based on a generalisation of the Matrix Pencil algorithm to the two dimensional case, i.e. 2D Matrix Pencils. Matrix pencil algorithms offer estimation of signal parameters, i.e. angles of arrival (AoA) or times of arrival (ToA), of multiple sources using a single snapshot...
In this paper we consider a passive radar system with widely separated receivers where the propagation path between the target and some of the receiver elements may be blocked. We assume a system with no surveillance channel to the reference transmitted signal and consider the problem of joint detection of target and active receivers. We pose this as a composite detection problem with unknown signal...
This paper presents a data-driven method to estimate a high quality depth map of a hand from a stereoscopic camera input by introducing a novel regression framework. The method first computes disparity using a robust stereo matching technique. Then, it applies Random Forest (RF) to learn the mapping between the estimated, noisy disparity and actual depth given ground truth data. We introduce Eigen...
Morphological closing is a powerful tool for recovering and smoothing altered structures. Classic morphological closing uses constant and predefined structuring element that is well-adapted to regular shapes. However, the use of such structuring elements may deteriorate the information held by more complex and heterogeneous objects. In this paper, we present a new method for adaptive morphological...
Electroencephalography (EEG) based motor imagery Brain-Computer Interface (MI-BCI) paradigm is used to communicate with external device by people who lost peripheral nerve control, or perform neuro-rehabilitation for stroke patients. BCI systems based on motor imagery often employ feature extraction algorithms based on Common Spatial Patterns (CSP). CSP is capable of discriminating two classes, but...
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