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We consider the k-encoder source coding problem with a quadratic distortion measure. We show that among all source distributions with a given covariance matrix K, the jointly Gaussian source requires the highest rates in order to meet a given set of distortion constraints.
We derive a lower bound on each supporting hyperplane of the rate region of the vector Gaussian multiterminal source coding problem by coupling it with the CEO problem through a limiting argument. The tightness of this lower bound in the high-resolution regime and the weak-dependence regime is proved.
This paper deals with cocoa powder production process which is multivariate in nature. The process is monitored based on individual observations. In order to monitor such process, in general, there are three different statistics available in the literature namely T2 statistic introduced by Hotelling in 1947, Wilks' statistic introduced by Mason, Chou and Young in 2009, and F (Frobenius norm) statistic...
The purpose of this article is to evaluate and compare designs for multivariate generalized linear models using quantile dispersion graphs when the linear predictor is misspeci-fied. The uncertainty in the linear predictor is represented by an unknown function. The comparison of the designs are based on a scalar-valued function of the mean square error of prediction (MSEP) matrix, which incorporates...
This work considers practical implementation of the decode-and-forward relaying protocol for the full-duplex Gaussian relay channel. Unlike previous works which developed coding techniques tailored to this protocol, it is shown that standard codes which are good for the Gaussian scalar channel of fixed signal-to-noise ratio suffice to approach the theoretical performance promised by this protocol...
This work studies distributed compression for the uplink of a cloud radio access network, where multiple multi-antenna base stations (BSs) communicate with a central unit, also referred to as cloud decoder, via capacity-constrained back-haul links. Distributed source coding strategies are potentially beneficial since the signals received at different BSs are correlated. However, they require each...
Adaptive beamformers such as LSMI provide an excellent robustness against various types of mismatches. These beamformers are sometimes too conservative because they are worst-case optimization based beamformers. A rank-one beamformer based on probability-constrained optimization has been proved to have better performance. In this paper, a probability-constrained beamformer for general-rank signal...
Spectral clustering has represented a good alternative in digital signal processing and pattern recognition; however a decision concerning the affinity functions among data is still an issue. In this work it is presented an extended version of a traditional multiclass spectral clustering method which employs prior information about the classified data into the affinity matrixes aiming to maintain...
CATHEGORY 2: The reconstruction of neural activity acquired with MEG/EEG devices (magnetoencephalogram/electroencephalogram) consists on generating three dimensional images indicating the location of the sources of activity. The neural activity is commonly modeled as current dipoles distributed over the cortical surface, for guaranteeing a linear propagation model though the head until the sensors...
In this paper we explore the idea of dimensionality reduction and approximation of OD demand based on principal component analysis (PCA). First, we show how we can apply PCA to linearly transform the high dimensional OD matrices into the lower dimensional space without significant loss of accuracy. Next, we define a new transformed set of variables (demand principal components) that is used to represent...
The pedestrian detection literature has been recently extended by the availability of large-scale multisensory datasets, able to capture complementary aspects of the objects of interest, namely, appearance, motion, and depth. In this paper, we exploit this multimodal scenario to propose a new set of composite descriptors dubbed CO2, CO-variances of visual features and CO-occurrences of depth fields...
This paper suggests the calculation methodology of univariate and multivariate absolute risk aversion based on asymptotic analysis of conditional expectation and future excess return variance. In the paper we provide modification of the multivariate econometric algorithm on the assumption of weakly time-varying correlation matrices for which the conditions of positive definiteness were received. We...
The estimation of carrier frequency offset (CFO) is an important issue for OFDM systems. Many CFO estimation methods have been proposed in the past. In particular, two ESPRIT-based methods were introduced for blind CFO estimations. These ESPRIT-based methods can provide satisfactory performance at a reasonable implementation cost. In this paper, we propose a least-squares (LS) algorithm for improving...
This paper studies the multi-cell cooperative transmission based on interference alignment (IA). A new macro-diversity approach is presented in which each BS not only transmits data to its serving users but also transmits data to the users belonging to the cooperative BSs. By coherently designing the precoding and detection matrices, desired signals from multi-BSs are detected to achieve macro-diversity...
We propose a method that detects mating of shrimps in a tank and records the scene from a surveillance camera onto a PC. Shrimps behave differently at the mating time compared with the non-mating time. This difference of the motion is determined by using cubic higher-order local auto correlation feature in conjunction with a subspace method in this study. Experimental results show the effectiveness...
A filtering technique of neutron flux during the nuclear reactor restarting is presented in this paper. The nuclear reactor model is described by equation of inverse kinetics. The ionization chambers are used for neutron flux measure. To minimize the undesired noise of measurement the extended Kalman filter (EKF) method is used. The filter EKF is designed using the nuclear reactor model.
In this paper, we design a precoding codebook generator with an angular channel model using eigen beamforming. We consider a codebook generator which is constructed by an eigen beamforming with a channel state rotation matrix. The transmission signals are rotated by a real (θ) and a complex (φ) phase angle in the channel. Complex phase rotation (φ) depends on real phase angle (θ) and it has a free...
Video cameras are extensively used in modern surveillance systems to detect, track, and recognize, objects, people, and anomalies. Their use in user authentication, however, has been limited primarily to close-range face recognition systems. In this paper, we explore user authentication based on gestures captured by a video camera. Unlike pure biometrics, such as fingerprints, iris scans, and faces,...
In this paper is presented the design of a tracking and trayectory generation robotic system in a testing environment Robocup (small size category) by the prediction of movements using Kalman filters and the optimal trajectory generation by implementing B-spline curves. In the different results obtained it was found that the Kalman filter facilitates the prediction of robotic agents with small processing...
the problem of adaptive detection of spatially distributed targets or targets embedded in no homogeneous clutter with unknown covariance matrix is studied. At first, assume the clutter is complex circular zero-mean Gaussian clutter with an unknown positive definite covariance matrix, and it is independent of the covariance matrix vector under test, the secondary data are assumed to be random, then...
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