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We propose a simpler derivation of the probability density function of Feller Diffusion using the Fourier Transform and solving the resulting equation via the Method of Characteristics. We also discuss simulation algorithms and confirm key…

Probability · Mathematics 2019-06-28 Ranjiva Munasinghe , Leslie Kanthan , Pathum Kossinna

Accurate noise modelling is important for training of deep learning reconstruction algorithms. While noise models are well known for traditional imaging techniques, the noise distribution of a novel sensor may be difficult to determine a…

Machine Learning · Computer Science 2018-07-11 Felix Horger , Tobias Würfl , Vincent Christlein , Andreas Maier

Weak gravitational lensing surveys are rapidly becoming important tools to probe directly the mass density fluctuations in the universe and its background dynamics. Earlier studies have shown that it is possible to model the statistics of…

Astrophysics · Physics 2009-11-07 Patrick Valageas , Andrew J. Barber , Dipak Munshi

We study the Langevin equation with stationary-increment Gaussian noise. We show the strong consistency and the asymptotic normality with Berry--Esseen bound of the so-called alternative estimator of the mean reversion parameter. The…

Probability · Mathematics 2016-03-02 Tommi Sottinen , Lauri Viitasaari

This paper is concerned with the estimation of the period of an unknown periodic function in Gaussian white noise. A class of estimators of the period is constructed by means of a penalized maximum likelihood method. A second-order…

Statistics Theory · Mathematics 2011-11-10 I. Castillo

Gaussian time-series models are often specified through their spectral density. Such models present several computational challenges, in particular because of the non-sparse nature of the covariance matrix. We derive a fast approximation of…

Computation · Statistics 2012-11-20 Nicolas Chopin , Judith Rousseau , Brunero Liseo

The density estimation is one of the core problems in statistics. Despite this, existing techniques like maximum likelihood estimation are computationally inefficient due to the intractability of the normalizing constant. For this reason an…

Machine Learning · Computer Science 2021-01-14 Tsimboy Olga , Yermek Kapushev , Evgeny Burnaev , Ivan Oseledets

The explicit form for the post-Newtonian gravitational time delay of light signals propagating on the equatorial plane of a Kerr-Newman black hole is derived. Based on the null geodesic in Kerr-Newman spacetime, we adopt the iterative…

General Relativity and Quantum Cosmology · Physics 2020-07-22 Guansheng He , Wenbin Lin

The Gaussian mixed-effects model driven by a stationary integrated Ornstein-Uhlenbeck process has been used for analyzing longitudinal data having an explicit and simple serial-correlation structure in each individual. However, the…

Statistics Theory · Mathematics 2023-11-07 Takumi Imamura , Hiroki Masuda , Hayato Tajima

We present exact analytical results for the statistics of nonlinear coupled oscillators under the influence of additive white noise. We suggest a perturbative approach for analysing the statistics of such systems under the action of a…

Chaotic Dynamics · Physics 2007-05-23 J. E. Prilepsky , S. A. Derevyanko

A low-complexity model for signal quality prediction in a nonlinear fiber-optical network is developed. The model, which builds on the Gaussian noise model, takes into account the signal degradation caused by a combination of chromatic…

Optics · Physics 2015-01-07 Pontus Johannisson , Erik Agrell

This paper addresses the detection of a stochastic process in noise from irregular samples. We consider two hypotheses. The \emph{noise only} hypothesis amounts to model the observations as a sample of a i.i.d. Gaussian random variables…

Information Theory · Computer Science 2009-09-25 Walid Hachem , Eric Moulines , Francois Roueff

In fiber-optic distributed sensing, vibration signals are mostly assumed to follow Gaussian distribution for the simplicity of signal processing. However, in real applications, vibration signals often behave as non-Gaussian processes, which…

Signal Processing · Electrical Eng. & Systems 2019-01-18 Qian He , Rong Liu , Chengdan Tan , Lijun Tang , Xiongjun Shang

New problems arise when the standard theory of joint detection and estimation is applied to a set of signals drawn from a continuous family; decision thresholds must be determined as a function of the continuous parameter x characterizing…

Statistics Theory · Mathematics 2014-07-17 D. Michael Milder , Robert G. Lindgren , Morris M. Berman

The diffusion of colloids inside an active system-e.g. within a living cell or the dynamics of active particles itself (e.g. self-propelled particles) can be modeled through overdamped Langevin equation which contains an additional noise…

Statistical Mechanics · Physics 2024-12-06 Koushik Goswami , K. L. Sebastian

The Gaussian function (GF) is widely used to explain the behavior or statistical distribution of many natural phenomena as well as industrial processes in different disciplines of engineering and applied science. For example, the GF can be…

Signal Processing · Electrical Eng. & Systems 2020-01-08 Ibrahim Al-Nahhal , Octavia A. Dobre , Ertugrul Basar , Cecilia Moloney , Salama Ikki

We present an expression for the shot noise power spectral density in quasi-one dimensional conductors electrostatically controlled by a gate electrode, that includes the effects of Coulomb interaction and of Pauli exclusion among charge…

Mesoscale and Nanoscale Physics · Physics 2015-05-13 Alessandro Betti , Gianluca Fiori , Giuseppe Iannaccone

One of the central goals of the newborn field of gravitational wave astronomy is to test gravity in the highly nonlinear, strong field regime characterizing the spacetime of black holes. In particular, "black hole spectroscopy" (the…

General Relativity and Quantum Cosmology · Physics 2017-10-04 Kostas Glampedakis , George Pappas , Hector O. Silva , Emanuele Berti

This is the second part of the two-part paper considering the communications under the bursty mixed noise composed of white Gaussian noise and colored non-Gaussian impulsive noise. In the first part, based on Gaussian distribution and…

Signal Processing · Electrical Eng. & Systems 2024-05-10 Tianfu Qi , Jun Wang , Zexue Zhao

The construction of synthetic complex-valued signals from real-valued observations is an important step in many time series analysis techniques. The most widely used approach is based on the Hilbert transform, which maps the real-valued…

Machine Learning · Statistics 2017-12-08 Luca Ambrogioni , Eric Maris
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