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Getting good statistical models of traffic on network links is a well-known, often-studied problem. A lot of attention has been given to correlation patterns and flow duration. The distribution of the amount of traffic per unit time is an…

Networking and Internet Architecture · Computer Science 2021-02-26 Mohammed Alasmar , Richard Clegg , Nickolay Zakhleniuk , George Parisis

We experimentally investigate mutual information and generalized mutual information for coherent optical transmission systems. The impact of the assumed channel distribution on the achievable rate is investigated for distributions in up to…

Information Theory · Computer Science 2024-01-25 Tobias A. Eriksson , Tobias Fehenberger , Peter A. Andrekson , Magnus Karlsson , Norbert Hanik , Erik Agrell

Getting good statistical models of traffic on network links is a well-known, often-studied problem. A lot of attention has been given to correlation patterns and flow duration. The distribution of the amount of traffic per unit time is an…

Networking and Internet Architecture · Computer Science 2019-02-12 Mohammed Alasmar , George Parisis , Richard G. Clegg , Nickolay Zakhleniuk

Obtaining a reduced description with particle and momentum flux densities outgoing from the microscopic equations of motion of the particles requires approximations. The usual method, we refer to as truncation method, is to zero Fourier…

Statistical Mechanics · Physics 2017-01-04 Hamid Seyed-Allaei , Lutz Schimansky-Geier , Mohammad Reza Ejtehadi

This letter develops a one-dimensional (1D) diffusion-based molecular communication system to analyze channel responses between a single transmitter (TX) and two fully-absorbing receivers (RXs). Incorporating molecular degradation in the…

Emerging Technologies · Computer Science 2020-03-24 Xinyu Huang , Yuting Fang , Adam Noel , Nan Yang

The results of a series of theoretical studies are reported, examining the convergence rate for different approximate representations of $\alpha$-stable distributions. Although they play a key role in modelling random processes with jumps…

Probability · Mathematics 2020-01-03 Marina Riabiz , Tohid Ardeshiri , Ioannis Kontoyiannis , Simon Godsill

Let $X_1,X_2,...$ be a sequence of random variables satisfying the distributional recursion $X_1=0$ and $X_n= X_{n-I_n}+1$ for $n=2,3,...$, where $I_n$ is a random variable with values in $\{1,...,n-1\}$ which is independent of…

Probability · Mathematics 2007-11-01 Alex Iksanov , Martin Möhle

In biochemical reaction networks, the first passage time (FPT) of a reaction quantifies the time it takes for the reaction to first occur, from the initial state. While the mean FPT historically served as a summary metric, a far more…

Molecular Networks · Quantitative Biology 2025-03-07 Changqian Rao , David Waxman , Wei Lin , Zhuoyi Song

We obtain an exact formula for the first-passage time probability distribution for random walks on complex networks using inverse Laplace transform. We write the formula as the summation of finitely many terms with different frequencies…

Statistical Mechanics · Physics 2018-12-17 Mucong Ding , Kwok Yip Szeto

In this study, we introduce a novel method for generating new synthetic samples that are independent and identically distributed (i.i.d.) from high-dimensional real-valued probability distributions, as defined implicitly by a set of Ground…

Machine Learning · Statistics 2024-07-09 Hamidreza Behjoo , Michael Chertkov

Understanding how information can efficiently spread in distributed systems under noisy communications is a fundamental question in both biological research and artificial system design. When agents are able to control whom they interact…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-11-11 Niccolò D'Archivio , Amos Korman , Emanuele Natale , Robin Vacus

We consider a collection of independent standard Brownian particles (or random walks), starting from a configuration where at least one particle is positive, and study the first time they all become negative. This is clearly equivalent to…

Probability · Mathematics 2024-11-27 Emmanuel Humbert , Kilian Raschel

In this paper, we consider the diffusive molecular communication channel between a transmitter nano-machine and a receiver nano-machine in a fluid environment. The information molecules released by the transmitter nano-machine into the…

Emerging Technologies · Computer Science 2016-11-17 Arman Ahmadzadeh , Hamidreza Arjmanidi , Andreas Burkovski , Robert Schober

We study the problem of randomized information dissemination in networks. We compare the now standard PUSH-PULL protocol, with agent-based alternatives where information is disseminated by a collection of agents performing independent…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-06-04 George Giakkoupis , Frederik Mallmann-Trenn , Hayk Saribekyan

We consider three kinds of discrete-time arrival processes: transient, intermediate and recurrent, characterized by a finite, possibly finite and infinite number of events, respectively. In this context, we study renewal processes which are…

In this article, normal inverse Gaussian (NIG) autoregressive model is introduced. The parameters of the model are estimated using Expectation Maximization (EM) algorithm. The efficacy of the EM algorithm is shown using simulated and real…

Methodology · Statistics 2021-07-16 Monika Singh Dhull , Arun Kumar

The problem of the time required for a diffusing molecule, within a large bounded domain, to first locate a small target is prevalent in biological modeling. Here we study this problem for a small spherical target. We develop uniform in…

Biological Physics · Physics 2013-08-06 Samuel A. Isaacson , Jay Newby

We consider nanonodes randomly distributed in a circular area and characterize the received signal strength when a pair of these nodes employ molecular communication. Two communication methods are investigated, namely free diffusion and…

Emerging Technologies · Computer Science 2018-01-29 Rafay Iqbal Ansari , Chrysostomos Chrysostomou , Taqwa Saeed , Marios Lestas , Andreas Pitsillides

The generalized inverse Gaussian, denoted $\mathrm{GIG}(p, a, b)$, is a flexible family of distributions that includes the gamma, inverse gamma, and inverse Gaussian distributions as special cases. In addition to its applications in…

Computation · Statistics 2025-01-28 Victor Peña , Michael Jauch

We consider the estimation of an i.i.d.\ random vector observed through a linear transform followed by a componentwise, probabilistic (possibly nonlinear) measurement channel. A novel algorithm, called generalized approximate message…

Information Theory · Computer Science 2012-08-15 Sundeep Rangan