In mathematics, the Markov spectrum, devised by Andrey Markov, is a complicated set of real numbers arising in Markov Diophantine equations and also in...

Gauss–Markov theorem Gauss–Markov process Markov blanket Markov boundary Markov chain Markov chain central limit theorem Additive Markov chain Markov additive...

A Markov number or Markoff number is a positive integer x, y or z that is part of a solution to the Markov Diophantine equation x 2 + y 2 + z 2 = 3 x y...

Gauss–Markov stochastic processes (named after Carl Friedrich Gauss and Andrey Markov) are stochastic processes that satisfy the requirements for both...

that the conclusion holds for a set of denominators of density 1. Markov spectrum Rockett, Andrew M.; Szüsz, Peter (1992). Continued Fractions. World...

mathematicians successfully formalizing contemporary mathematics. Markov spectrum Plünnecke–Ruzsa inequality Kneser's theorem (combinatorics) Freiman...

The spectrum of a linear operator T {\displaystyle T} that operates on a Banach space X {\displaystyle X} is a fundamental concept of functional analysis...

paper by Andrew D. Martin and Kevin M. Quinn. The Martin–Quinn score uses Markov chain Monte Carlo (MCMC) methods to fit a Bayesian model of ideal points...

{2d(d-\lambda _{2})}}.} This inequality is closely related to the Cheeger bound for Markov chains and can be seen as a discrete version of Cheeger's inequality in...

In number theory, specifically in Diophantine approximation theory, the Markov constant M ( α ) {\displaystyle M(\alpha )} of an irrational number α {\displaystyle...

matrix of links. A related matrix S corresponding to the transitions in a Markov chain of given network is constructed from A by dividing the elements of...

Academy of Sciences. In 2003, he received the Institute for Nuclear Research Markov Prize for his contributions to neutrino physics. In 2006, he received the...

See also Markov switching multifractal (MSMF) techniques for modeling volatility evolution. A hidden Markov model (HMM) is a statistical Markov model in...

components. This vector corresponds to the stationary distribution of the Markov chain represented by the row-normalized adjacency matrix; however, the adjacency...

and business, such as finite probability spaces, matrix multiplication, Markov processes, finite graphs, or mathematical models. These topics were used...

process Markov information source Markov kernel Markov logic network Markov model Markov network Markov process Markov property Markov random field Markov renewal...

elsewhere. The topic of Markov chains was particularly popular so Kemeny teamed with J. Laurie Snell to publish Finite Markov Chains (1960) to provide...

seeing themselves as a new individual; enter a relationship with Brion Markov; and befriend Harper Row. However, they are kidnapped by Granny Goodness...

the dominant speech processing strategy started to shift away from Hidden Markov Models towards more modern neural networks and deep learning. In 2012, Geoffrey...

theorem has important applications to probability theory (ergodicity of Markov chains); to the theory of dynamical systems (subshifts of finite type);...

appearing in comic books published by DC Comics, related to the emotional spectrum. The group is composed of deceased fictional characters in zombie form...

S1500. PMC 2656336. PMID 19300629. S2CID 8816485. Sheldrick AJ, Krug A, Markov V, Leube D, Michel TM, Zerres K, et al. (September 2008). "Effect of COMT...

doi:10.1109/TMC.2020.2992045. S2CID 218931192. Gu, X.; et al. (2022). "Markov Analysis of C-V2X Resource Reservation for Vehicle Platooning". 2022 IEEE...

mathematicians united around E. B. Dynkin who were developing the theory of Markov processes. His thesis introduced the concept of a strong Feller process...

smoothing in step 3 makes the output image look blurred. These methods, using Markov fields, non-parametric sampling, tree-structured vector quantization and...

Least-squares spectral analysis (LSSA) is a method of estimating a frequency spectrum based on a least-squares fit of sinusoids to data samples, similar to Fourier...

and decorrelating the spectrum using a cosine transform, then taking the first (most significant) coefficients. The hidden Markov model will tend to have...

independent Markov machine. Each time a particular arm is played, the state of that machine advances to a new one, chosen according to the Markov state evolution...

graph is strongly connected.) A detailed definition is given here. Also, a Markov chain is irreducible if there is a non-zero probability of transitioning...

uniqueness conjecture for Markov numbers that every Markov number is the largest number in exactly one normalized solution to the Markov Diophantine equation...