The large deviation (LD) statistics of dynamical observables is encoded in the spectral properties deformed Markov generators. Recent works have shown that tensor network methods are well suited to compute relevant leading eigenvalues and eigenvectors accurately. However, efficient generation corresponding rare trajectories a harder task. Here we show how exploit MPS approximation dominant eige...

the purpose of this paper is to develop a methodology for solving a new type of matrix games in which payoffs are expressed with triangular intuitionistic fuzzy numbers (tifns). in this methodology, the concept of solutions for matrix games with payoffs of tifns is introduced. a pair of auxiliary intuitionistic fuzzy programming models for players are established to determine optimal strategies...

this paper presents a method for identification of linear system physical parameters (structural mass, damping and stiffness matrices) using the inverse solution of equation of motion in the frequency domain, by focus on the reducing the illconditioning effect. the method utilizes the measured responses from the forced vibration test of structure in order to identify the system properties and d...

In a network, a distributed consensus algorithm is fully characterized by its weighting matrix. Although there exist numerical methods for obtaining the optimal weighting matrix, we have not found an in-network implementation of any of these methods that works for all network topologies. In this paper, we propose an in-network algorithm for finding such an optimal weighting matrix.

This paper presents some e cient and scalable parallel and distributed implementations of a matrix multiplication operation, ADA0, where A is a very \fat" matrix, D a diagonal matrix and A0 is the transpose of A, a very \thin" matrix, and their application to a maximum entropy problem. Theoretical performance results of a time-optimal implementation and a space-optimal implementation are given ...