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Commercial shipping vessels are a common source of underwater noise in the ocean. This article details a stochastic model for generating frequency-rough emission spectra for different classes of commercial shipping vessels. The model incorporates discrete probability density functions (PDFs) for different ship classes as well as class-dependent conditional PDFs of ship speed and length. Realistic...
This article develops a geometric framework for detecting targets, in the form of regions of interest, from certain sonar imagery. The main idea is to extract level sets from voxel images and compute local geometric features of the resulting surfaces. Examples include Gaussian and principal curvatures, radial distances, patch areas etc. These features are then compressed into histograms, or estimated...
Modern advanced driver assistance systems (ADAS) and automated driving functions for automobiles rely on an accurate model of the environment. To this end, the exploitation of complementary advantages of the measurement principles used by radar, lidar and camera sensors is an important prerequisite. We develop a framework for sensor data fusion that incorporates heterogeneous sensor data from multiple...
Pattern classification in electroencephalography (EEG) signals is an important problem in biomedical engineering since it enables the detection of brain activity, in particular the early detection of epileptic seizures. In this paper we propose a k-nearest neighbors classification for epileptic EEG signals based on an t-location-scale statistical representation to detect spike-and-waves. The proposed...
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,...
Future self-driving cars and current ones with advanced driver assistance systems are expected to interact with other traffic participants, which often are multiple other vehicles. To facilitate the motion planning of the autonomously controlled vehicle in collision avoidance, individual object vehicles with closeness in positions and velocities can be grouped as a single extended moving object. However,...
In this paper, we describe a set of robust algorithms for group-wise registration using both rigid and non-rigid transformations of multiple unlabelled point-sets with no bias toward a given set. These methods mitigate the need to establish a correspondence among the point-sets by representing them as probability density functions where the registration is treated as a multiple distribution alignment...
Non-Gaussian statistical models fit SAR data better than Gaussian-based statistics, in most cases, but are complicated and time-consuming to use for unsupervised image segmentation via probabilistic clustering. The more advanced the model, the more complicated and slow the clustering. The U-distribution has been demonstrated to be one of the most flexible models, capturing the Gaussian/Wishart, the...
This paper proposes several probability distribution models for wind- and net-load-power forecast error, i.e., a generalized normal model (GN) and extended skew-generalized-normal models (ESGN, SGN and SN). They are all compared to different models known from the literature (beta, Weibull and gamma). The evaluation of the discussed probability distribution models shows that the ESGN model presents...
We verify the validity of the recently suggested universal superstatistical model for the modeling of the aggregated local network traffic. The empirical data set consists of 14 complete daily traffic logs obtained at the link between the Internet Service Provider (ISP) and the local subnet comprising part of the campus network of Ivanovo State University. We show explicitly that the superstatistical...
In this paper, we propose a compact image steganalysis method for the LSB-matching steganography, in which a feature vector composed by only 12 elements is extracted from the image. We analyze the statistical artifact occurred in images when a secret data is embedded in it by the LSB-matching steganography. We selected 12 most relevant features based on the probability density function (PDF) of difference...
This paper proposes a practical implementation for the generation of real-time K-Distributed correlated sea-clutter in firmware. The method uses a dual cumulative distribution function (CDF) based look-up method to transpose a complex uniformly distributed random variable (RV) to the required RV. The clutter is correlated by means of a filter process before translation, and it is shown that this technique...
The Levy Walk (or Levy flight) is a concept fromBiomathematics to describe the hunting–behaviour of manypredatory species. It is a very efficient way to find prey in avery short time frame. We now want to use this concept ina clustering–context to – if you so will – "hunt" for clusters. We describe how we convert this concept into an efficient wayto find cluster centres by linking the data...
For analyzing the effects of the uncertainties of the fuzzy failure criterion and the input variables on fuzzy failure probability, the moment-independence importance measure (MIIM) model on the fuzzy failure probability for the fuzzy state structural system is proposed. Firstly, according to the fuzzy random theory, the fuzzy failure criterion is transformed into the equivalent additional random...
A quantitative diagnostic method for liver fibrosis using ultrasound echo signals is highly required. A probability density function (PDF) of echo envelope from a normal liver can be approximated by a Rayleigh distribution; however, the PDF of echo envelope from liver fibrosis deviates from the Rayleigh distribution. To evaluate tissue characteristics in the ultrasound B-mode image, several amplitude...
This paper deals with clustering non-gaussian data with fixed bounds. It considers the problem using recursive mixture estimation algorithms under the Bayesian methodology. Such a solution is often desired in areas, where the assumption of normality of modeled data is rather questionable and brings a series of limitations (e.g., non-negative, bounded data, etc.). Here for modeling the data a mixture...
Images with weak contrast, overlapped noise and texture of the object and background make many PDE based methods disabled. To address these problems, this paper presents a novel combined multi-scale variational framework level set segmentation model. Its level set formulation consists edge-based term, region-based term and shape constraint term. The edge-based term is constructed using a newly defined...
In this paper, the electromagnetic (EM) environment inside four kinds of enclosure are analyzed by statistical method. The external electromagnetic energy is coupled into enclosure through nine kinds of aperture array with equivalent areas respectively. The computational results are given in the form of probability density function (PDF) to show the interior EM characteristics. Statistics can effectively...
The complex multivariate generalized Gaussian distribution (CMGGD) is a flexible parametrized distribution suitable for a variety of applications. Previous work in this area is either limited to the univariate case or, in the multivariate case, restricts the complex vectors, unjustifiably, to be circular. In both cases, algorithms for parameter estimation also suffer from convergence or accuracy limitations...
Wind energy is a prime sector of the composite renewable energy sector which is supposed to be the prime energy producing force in years to come [1]. The ever increasing demand of wind energy and its renewable nature has led to an emphatic push in development of this sector. Wind speed has been one of those important parameters which form the basic element for design of any wind energy system. Thus,...
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