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The Delay-Multiply-And-Sum (DMAS) beamformer has recently been presented in the context of medical ultrasound image formation. Images obtained with the DMAS beamformer present improved contrast resolution and noise rejection when compared to images obtained with the standard Delay-And-Sum (DAS) beamformer. We study here the signal statistics for a homogeneous medium using both the DAS and DMAS beamformers...
This paper describes the results of a Monte Carlo simulation to quantify the statistical uncertainty of emission measurements in the scope of electromagnetic compatibility in a reverberation chamber. Such a measurement can be performed based on the average or maximum received power at the reference antenna. Depending on whether value is measured, different parameters as the chamber validation factor...
Modelling is a crucial step for analyzing the data. Graph is an important modelling technique for some areas especially if the data has some kind of relation between each other like complex networks. There are plenty of study in complex network area which uses graphs as a modelling tool. Collaboration networks are a kind of complex evolving networks. Also community detection and evaluation is an important...
Measuring PDIV with 50 Hz sinusoidal waveforms to find what happens using wide bandgap devices having slew rates of x 100 V/ns can give misleading results. Since PDIV tests using wide bandgap devices offers contradicting results, a probabilistic model is proposed to figure the probability density function of PDIV results. This is an intermediate step developing a statistical procedure enabling a more...
This paper deals with a modeling of data by several mixtures of different distributions within a task of clustering. This issue can be required from a practical point of view, e.g., for a multi-modal system, which generates measurements described by different distributions. The approach is based on the partition of the data on several parts, the factorization of the joint probability density function...
In this paper, for a given Schrödinger equation in quantum mechanics, an interpretation of it is investigated from the stochastic control-theoretic point of view.
In statistical approaches such as statistical static timing analysis, the distribution of the maximum (or the minimum) of plural distributions is needed, and is computed by repeating a statistical maximum operation of two distributions (2Max operation). Since each distribution is represented by a linear combination of several explanatory random variables (RVs) so as to handle correlations efficiently,...
Rain attenuation is a major problem on millimeter wave propagation especially around subtropical, tropical and equatorial regions in Africa. Previous research has determined that rainfall characteristics over sub-tropical and equatorial regions in Africa are essentially a queue process following an M/Ek/s/∞/FCFS queue discipline. Rainfall measurements consisting of 2000 observable rain spikes were...
In this paper, an empirical Rice K factor, distribution is accomplished. The results show that the distribution obtained by measurements well-fitted with the Nakagami-m one. Data have been gathered within the reverberating chamber (RC) of the Università degli Studi di Napoli Parthenope, formerly Istituto Universitario Navale (IUN).
This paper proposes a novel approach to global localization using high-level features. The new probabilistic framework enables to incorporate uncertain localization cues into a probability distribution that describes the likelihood of the current robot pose. We use multiple triplets of planes segmented from RGB-D data to generate this probability distribution and to find the robot pose with respect...
This paper presents a probabilistic model for optimal economic load dispatch problem to address integration of renewable energy resources into conventional power system network grid. The power generated from the solar photovoltaic (PV) array unit and load demand are recognised as random variables with given probability distribution functions. The economic load dispatch objective function is converted...
In the design process of Earth-space link telecommunication systems at higher frequencies, the precise estimation of attenuation due to rain which depends on rain height is important. This study examines two statistical distribution models for freezing height level over Durban, South Africa, using 5 years data and then studied the monthly, seasonal and annual variations using the parameters estimated...
The Evolutionary algorithm (EA) for researching parameters of nonlinear system is a rapidly growing field of identification. This can owe to the importance of EA for both the theoretical field and the engineering community. However, the identification of the nonlinear system is still a knotty problem, especially when heavy-tailed noises exists. Compared to classical identification methods, EA has...
In this contribution, an opto-acoustic system for distance measurement between a transmitter and a receiver is presented. This distance measurement is part of an indoor localization system which uses multilateration to obtain the position and orientation of rigid bodies. The novelty of the presented distance measurement is the efficiency in the sense that high accuracy is obtained with the use of...
The problems of the synthesis and analysis of discriminators under the influence non-Gaussian noise with a band-limited are considered. It is shown that in the above case, the discriminator is dual channel. Therefore the characteristics of the nonlinear transformation unit of the discriminator are determined by the Fisher information relative to the density of probability distribution of the amplitude...
In this paper, we propose a parameter estimation method for nonlinear state-space models based on the variational Bayes. We show that the variational posterior distribution of the hidden states corresponds to a posterior distribution of the states of an augmented nonlinear state-space model. From this, we can obtain the variational posterior distribution of the hidden states by implementing a variety...
A promising direction in deep learning research is to learn representations and simultaneously discover cluster structure in unlabeled data by optimizing a discriminative loss function. Contrary to supervised deep learning, this line of research is in its infancy and the design and optimization of a suitable loss function with the aim of training deep neural networks for clustering is still an open...
In the satellite formation task, due to a satellite failure or formation task change, it is necessary to reconstruct the formation. In the process of reconfiguration of satellites, satellites anti-collision research is one of the most important links. In this paper, by collapsing the initial covariance matrix of the satellite, the collision probability density function is integrated in the region...
This paper considers the problem of range-based decentralized localization in wireless sensor networks when the impulsive measurement noise is present. We develop a robust localization estimator requiring no a priori knowledge of the noise distribution. The approach to robust localization presented here follows the concept of M-estimation and is implemented in a decentralized manner thus suiting the...
In this paper, the cellular mobile communication system with microdiversity and macrodiversity reception operating over Gamma shadowed Weibull multipath fading environment is analyzed. Macrodiversity selection combining (SC) receiver reduces Gamma long term fading effects and three microdiversity SC receivers mitigate Weibull short term fading effects on the system performance. The useful closed form...
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