stochastic matrix
Low-Rank Doubly Stochastic Matrix Decomposition for Cluster Analysis
... Although a preliminary version of our method has been presented earlier (Yang and Oja, 2012a), the current paper introduces several significant improvements. First, we show that the proposed clustering objective can be ...
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Left Eigenvector of a Stochastic Matrix
... In the noncommutative case, we must involve inverses of elements of the skew field and as these may be undefined, we take a generic noncommutative stochastic matrix: this is the matrix of ...
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GROUP CONCEPTS, RING CONCEPTS AND GROUP HOMOMORPHISM OF DOUBLY STOCHASTIC MATRIX
... A collection of non-empty and non-singular doubly stochastic matrix R together with two binary operations denoted by “+” and “.” are addition and multiplication which satisfy the following axioms is called ...
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The Diagonal Equivalence of A Non-Negative Quaternion Matrix to A Doubly Stochastic Matrix
... quaternion matrix to a doubly stochastic matrix ...quaternion matrix to a row doubly stochastic ...non-negative matrix A with atleast one positive element in each row it is clear ...
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Similarity-based Clustering by Left-Stochastic Matrix Factorization
... similarity matrix as the inner products of the unknown cluster ...similarity matrix, we introduce a left-stochastic non-negative matrix factorization ...the matrix factorization. ...
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MoL 2015 04: Learning in Games through Social Networks
... stochastic matrix with degrees of belief bij degree of belief that agent i has for alternative j stochastic matrix B at round t j-th column of matrix B i-th row of matrix B k-ary row vec[r] ...
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Convergence analysis of an improved pagerank algorithm
... Thus Google faces the problem of having to compute the stationary probability of a large stochastic matrix (the dimension of the matrix G is several billion [12],[9, §3.1]). Direct methods [15, §2] ...
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Ranking Theory with Application to Popular Sports.
... irreducible stochastic matrix produced using the “endorsement” ...adjacency matrix also corresponding to the “endorsement” interpretation of ...
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K hermitian doubly stochastic, s hermitian doubly stochastic and s k hermitian doubly stochastic matrices
... doubly stochastic matrix if ̅ = V A* V and = V B* V ...doubly stochastic matrices then A* = V ̅ V and B* = V V To prove A B is s-Hermitian doubly stochastic matrix we will show that AB ...
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An Algorithm for Computing the Perron Root of a Nonnegative Irreducible Matrix
... generalized stochastic matrix that is similar to a positive matrix A, by the Frobenius theorem in section ...positive matrix A has a tight gap between the first and the second largest ...
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The Sinkhorn-Knopp algorithm : convergence and applications
... nonnegative matrix and it converges to the doubly stochastic matrix P then the rate of convergence is asymptotically equal to the square of the second sin- gular value of ...Hessenberg matrix ...
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Some problems in the theory and applications of Markov chains
... XV doubly stochastic matrix, and another derived from it, The chapter ends with a review of the case of the Markov chain with three states, for which these results prove to be exhaustive[r] ...
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A New Parametric Estimation Method for Graph based Clustering
... corresponding stochastic matrix of an affinity matrix has the same eigenvectors as the normalized Laplacian matrix of the graph, thus spectral clustering can be interpreted as trying to find a ...
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Resource Demand Forecasting Model Based on Dynamic Cloud Workload
... right stochastic matrix defines the dependencies between the service ...The stochastic matrix specifies the probabilities of users moving from service unit i to service unit ...a ...
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Quantum stochastic flows on universal partial isometry matrix C* algebras
... Chapter 1 will discuss classical Markov processes and integration kernels. We begin with discrete Markov chains which introduce the most familiar form of ker- nels, stochastic matrices. A stochastic ...
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Assessment of sub-Nyquist deterministic and random data sampling techniques for operational modal analysis
... 3.2 Multi-coset and random sub-Nyquist sampling and power spectral estimation The linear noisy and noiseless response acceleration response signals generated as detailed in the previous sub-section are compressively ...
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Parameter sensitivity analysis for biochemical reaction networks
... long-time stochastic simulations for ...covariance matrix that have similar expressions to the standard LNA and therefore computation of the KL divergence and the Fisher Information Matrix, which ...
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A Efficient Computational Method for Solving Stochastic Itô-Volterra Integral Equations
... an stochastic operational matrix for Legendre wavelets is ...operational matrix in solving stochastic Itˆ o-Voltera integral equation is ...
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AUTOMATIC SPOKEN LANGUAGE RECOGNITION FOR MULTILINGUAL SPEECH RESOURCES
... [27], Stochastic User Equilibrium SUE aims to combine stochastic assignment with Wardrop Equilibrium to rise above the limitation of homogeneous user assumption in Wardrop equilibrium and to take into ...
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AN OVERVIEW OF COMPENSATION SCHEMES OF TIME DELAY IN NETWORK CONTROLLED SYSTEMSSaurav Bajpai1 and Chirag Gupta2
... the stochastic network delay, potentially enough to be used in critical real-time ...optimal stochastic method approaches the problem as a linear–quadratic–Gaussian (LQG) problem, where the LQG gain ...
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