‎In this paper‎, ‎an accelerated gradient based iterative algorithm for solving systems of coupled generalized Sylvester-transpose matrix equations is proposed‎. ‎The convergence analysis of the algorithm is investigated‎. ‎We show that the proposed algorithm converges to the exact solution for any initial value under certain assumptions‎. ‎Finally‎, ‎some numerical examples are given to demons...

in this paper, an iterative method is proposed for solving the matrix inverse problem $ax=b$ for hermitian-generalized hamiltonian matrices with a submatrix constraint. by this iterative method, for any initial matrix $a_0$, a solution $a^*$ can be obtained in finite iteration steps in the absence of roundoff errors, and the solution with least norm can be obtained by choosing a special kind of...

we study the problem of reconstructing binary images from four projections data in a fuzzy environment. given the uncertainly projections,w e want to find a binary image that respects as best as possible these projections. we provide an iterative algorithm based on fuzzy integer programming and linear membership functions.

‎Our contribution in this paper is to propose an iterative algorithm which does not require prior knowledge of operator norm and prove a strong convergence theorem for approximating a solution of split equality fixed point problem for quasi-nonexpansive mappings in a real Hilbert space‎. ‎So many have used algorithms involving the operator norm for solving split equality fixed point problem‎, ‎...

This paper addresses the possibility of capacity withholding by energy producers, who seek to increase the market price and their own profits. The energy market is simulated as an iterative game, where each state game corresponds to an hourly energy auction with uniform pricing mechanism. The producers are modeled as agents that interact with their environment through reinforcement learning (RL...

Abstract: This paper proposes a novel scheme for multi-static passive radar processing, based on soft-input soft-output processing and Bayesian sparse estimation. In this scheme, each receiver estimates the probability of target presence based on its received signal and the prior information received from a central processor. The resulting posterior target probabilities are transmitted to the c...