Showing 1-25 of 5,898 resultsfor "Index Terms":Central Limit Theorem
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In this paper we discuss some recent limit laws for empirical optimal transport distances from a simulation perspective. On discrete spaces, this requires to solve another optimal transport problem in each simulation step, which reveals simulations of such limit laws computational demanding. We discuss several strategies, e.g., resampling, to overcome this burden. In particular, we examine empiric...Show More
On the Convergence of Multipath Fading Channel Gains to the Rayleigh Distribution
The gain of a multipath propagation scenario is addressed by this work and it is shown that the convergence to the Rayleigh distribution depends on some conditions on the path gains, which are not always satisfied. These conditions confirm the convergence to the Rayleigh distribution for some well known scenarios. However, counter-examples are also exhibited where this convergence does not hold. F...Show More
Large System Analysis of the Energy Consumption Distribution in Multi-User MIMO Systems With Mobility
Luca Sanguinetti;Aris L. Moustakas;Emil Björnson;Merouane Debbah
In this work, we consider the downlink of a single-cell multi-user MIMO system in which the base station (BS) makes use of N antennas to communicate with K single-antenna user equipments (UEs). The UEs move around in the cell according to a random walk mobility model. We aim at determining the energy consumption distribution when different linear precoding techniques are used at the BS to guarante...Show More
Phase-Shift-Free $M$-Phase Spreading Sequences of Markov Chains
We consider the optimum spreading sequences of Markov chains in terms of the mean value of the limit of variance of the normalized multiple-access interference for asynchronous spread-spectrum multiple access communication systems. We first define a novel class of spreading sequences, namely the phase-shift-free M(ges 3)-phase spreading sequences. Then we theoretically and experimentally show that...Show More
Asymptotic analysis for hidden Markovian process with quantum hidden system
2017 IEEE Information Theory Workshop (ITW)
Year: 2017 | Conference Paper |
We focus on a hidden Markovian process whose internal hidden system is given as a quantum system, and we address a sequence of data obtained from this process. Using a quantum version of Perron-Frobenius theorem, we derive novel upper and lower bounds for the cumulant generating function of the sample mean of the data. Using these bound, we derive the central limit theorem and large and moderate d...Show More
Estimation of total power output fluctuation of high penetration photovoltaic power generation system
2011 IEEE Power and Energy Society General Meeting
Year: 2011 | Conference Paper |
Cited by: Papers (10)
This study proposes a method to estimate the standard deviation (STD) of total power output fluctuation of high penetration photovoltaic power generation system (HP-PVS) dispersed in large area, so that the impact of HP-PVS on the load frequency control is discussed. First, by using the data of horizontal global insolation observed at 5 points in 25 km × 25 km area, the practical usefulness of STD...Show More
Eigenvalue Estimation of Parameterized Covariance Matrices of Large Dimensional Data
This article deals with the problem of estimating the covariance matrix of a series of independent multivariate observations, in the case where the dimension of each observation is of the same order as the number of observations. Although such a regime is of interest for many current statistical signal processing and wireless communication issues, traditional methods fail to produce consistent est...Show More
Entropic Central Limit Theorem for Rényi Entropy
2019 IEEE International Symposium on Information Theory (ISIT)
Year: 2019 | Conference Paper |
Cited by: Papers (1)
We establish a central limit theorem for Rényi entropies when the Rényi parameters belong to (0, 1) for a large class of random vectors. This complements a celebrated result of Barron (1986). As an application, we show that a general Rényi entropy power inequality fails when the Rényi parameter is in (0, 1).Show More
Asymptotic analysis of a consistent subspace estimator for observations of increasing dimension
2011 IEEE Statistical Signal Processing Workshop (SSP)
Year: 2011 | Conference Paper |
Cited by: Papers (3)
Traditional estimators of the eigen-subspaces of sample co-variance matrices are known to be consistent only when the sample volume increases for a fixed observation dimension. Due to this fact, their accuracy tends to be rather poor in practical settings where the number of samples and the observation dimension are comparable in magnitude. To overcome this effect, an estimator was recently propos...Show More
Analysis of data-based methods for approximating fisher information in the scalar case
2015 49th Annual Conference on Information Sciences and Systems (CISS)
Year: 2015 | Conference Paper |
Cited by: Papers (2)
The Fisher information matrix (FIM) has long been of interest in applied mathematics and statistics for its various uses. Its scalar case, the Fisher information number (FIN), is also widely used. However, in many cases it is challenging to obtain the true value for the Fisher information so we need to use approximations. In this paper, we compare the accuracy of two major approximation methods fo...Show More
Lattice parameter estimation from sparse, noisy measurements
2016 50th Asilomar Conference on Signals, Systems and Computers
Year: 2016 | Conference Paper |
Cited by: Papers (1)
We consider a problem in which noisy measurements are made of the positions of points in a lattice. Some parameters of the lattice are known but others need to be estimated. In particular, it is not known a priori from which lattice point each measurement arises. In previous work [1-5], the authors have considered estimating the parameters of a one-dimensional lattice from measurements on the real...Show More
The limit distributions of growth rate fluctuation of complex systems: An application to business firms
2011 21st International Conference on Noise and Fluctuations
Year: 2011 | Conference Paper |
We consider statistical properties of aggregated systems consisting of randomly growing subunits which are governed by random multiplicative growth. The system exhibits typical features of complex systems such as power law system size distributions, fat-tailed growth rate distributions and nontrivial slow shrink of variance of growth rates as a function of the number of subunits. There are extraor...Show More
Optimization of State-Estimator-Based Operation Framework Including Measurement Placement for Medium Voltage Distribution Grid
IEEE Transactions on Smart Grid
Cited by: Papers (28)
To provide a guideline for grid operators to manage medium voltage distribution grids, this paper presents a probabilistic approach for measurement placement optimization and a state-estimator-based operation framework. The Monte Carlo method is used to optimize the measurement placement with minimum measured points, which support the observability of state estimator and satisfy the requirements f...Show More
Power Allocation for Distributed Antenna Systems in Frequency-Selective Fading Channels
A distributed antenna system (DAS) is very attractive, since it can reduce transmit power by shortening the distance between antenna elements (AEs) and the mobile station. This paper investigates the channel capacity of the DAS over a multi-path frequency-selective fading channel. We first show that the optimal power allocation solution to approaching the channel capacity is unrealistic for the pr...Show More
Revisiting Central Limit Theorem: Accurate Gaussian Random Number Generation in VLSI
Jamshaid Sarwar Malik;Ahmed Hemani;Jameel Nawaz Malik;Ben Silmane;Nasirud Din Gohar
Gaussian random numbers (GRNs) generated by central limit theorem (CLT) suffer from errors due to deviation from ideal Gaussian behavior for any finite number of additions. In this paper, we will show that it is possible to compensate the error in CLT, thereby correcting the resultant probability density function, particularly in the tail regions. We will provide a detailed mathematical analysis t...Show More
Asymptotic Mutual Information Statistics of MIMO Channels and CLT of Sample Covariance Matrices
In this paper, we consider the fluctuation of mutual information statistics of a multiple input multiple output channel communication systems without assuming that the entries of the channel matrix have zero pseudovariance. To this end, we also establish a central limit theorem of the linear spectral statistics for sample covariance matrices under general moment conditions by removing the restrict...Show More
Unscrambling Nonlinear Dynamics in Synthetic Aperture Radar Imagery
Khalid El-Darymli;Eric W. Gill;Peter Mcguire;Desmond Power;Cecilia Moloney
In analyzing single-channel synthetic aperture radar (SAR) imagery, three interrelated questions often arise. First, should one use the detected or the complex-valued image? Second, what is the `best' statistical model? Finally, what constitutes the `best' signal processing methods? This paper addresses these questions from the overarching perspective of the generalized central limit theorem, whic...Show More
Explicit Bounds for Entropy Concentration Under Linear Constraints
Consider the set of all sequences of n outcomes, each taking one of m values, whose frequency vectors satisfy a set of linear constraints. If m is fixed while n increases, most sequences that satisfy the constraints result in frequency vectors whose entropy approaches that of the maximum entropy vector satisfying the constraints. This well-known entropy concentration phenomenon underlies the maxim...Show More
Limit Distribution Theory for f-Divergences
$f$ -divergences, which quantify discrepancy between probability distributions, are ubiquitous in information theory, machine learning, and statistics. While there are numerous methods for estimating $f$ -divergences from data, a limit distribution theory, which quantifies fluctuations of the estimation error, is largely obscure. As limit theorems are pivotal for valid statistical inference, to c...Show More
Kernelized Locality-Sensitive Hashing
Fast retrieval methods are critical for many large-scale and data-driven vision applications. Recent work has explored ways to embed high-dimensional features or complex distance functions into a low-dimensional Hamming space where items can be efficiently searched. However, existing methods do not apply for high-dimensional kernelized data when the underlying feature embedding for the kernel is u...Show More
Joint Entropy Analysis Model for DDoS Attack Detection
2009 Fifth International Conference on Information Assurance and Security
Year: 2009 | Conference Paper |
Cited by: Papers (18)
Distributed Denial of service (DDoS) attack has become one of the most serious threats to the Internet. DDoS attack can be considered a system anomaly or misuse from which abnormal behaviour is imposed on network traffic. Network traffic characterization with behaviour modelling could be a good indication of attack detection witch can be performed via abnormal behaviour identification. Moreover, i...Show More
Approximation to Distribution of Product of Random Variables Using Orthogonal Polynomials for Lognormal Density
IEEE Communications Letters
Cited by: Papers (11)
We derive a closed-form expression for the orthogonal polynomials associated with the general lognormal density. The result can be utilized to construct easily computable approximations for probability density function of a product of random variables, when the considered variates are either independent or correlated. As an example, we have calculated the approximative distribution for the product...Show More
k-nearest neighbor estimation of entropies with confidence
2011 IEEE International Symposium on Information Theory Proceedings
Year: 2011 | Conference Paper |
Cited by: Papers (5)
We analyze a k-nearest neighbor (k-NN) class of plug-in estimators for estimating Shannon entropy and Rényi entropy. Based on the statistical properties of k-NN balls, we derive explicit rates for the bias and variance of these plug-in estimators in terms of the sample size, the dimension of the samples and the underlying probability distribution. In addition, we establish a central limit theorem ...Show More
A semi-blind image watermarking based on Discrete Wavelet Transform and Secret Sharing
2012 International Conference on Communication, Information & Computing Technology (ICCICT)
Year: 2012 | Conference Paper |
Cited by: Papers (4)
In this paper the concepts of frequency domain watermarking and Secret Sharing are combined to protect the copyrights of a digital image. The proposed method employs the concept of XOR-based Visual Secret Sharing (XVSS) to split a watermark into two unexpanded parts, a public watermark and a private watermark. The private watermark is extracted from the features of host image and original watermar...Show More
Efficient analysis of warm standby systems using central limit theorem
2012 Proceedings Annual Reliability and Maintainability Symposium
Year: 2012 | Conference Paper |
Cited by: Papers (4)
In a warm standby sparing system, the standby units have time-dependent failure behavior; they have different failure parameters or in general distributions before and after they are used to replace the on-line faulty units. Such time-dependent behavior makes the reliability analysis of warm standby system a challenging task. Existing approaches to analyzing the reliability of warm standby systems...Show More
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