Title :
Momentum algorithms in neural networks and the applications in numerical algebra
Author_Institution :
Sch. of Math. & Inf. Sci., Wenzhou Univ., Wenzhou, China
Abstract :
Momentum algorithms in neural networks and the applications for solving linear systems are discussed. The sufficient and necessary conditions for the convergence of the stationary iteration with momentum acceleration are obtained. Furthermore, the optimal momentum factor which minimizes the spectral radius of the associated momentum acceleration iteration matrix is also obtained. Some numerical results have demonstrated the effectiveness of the stationary iterations with momentum acceleration.
Keywords :
convergence of numerical methods; iterative methods; linear systems; mathematics computing; matrix algebra; neural nets; associated momentum acceleration iteration matrix; linear system solving; momentum algorithm; neural network; numerical algebra; optimal momentum factor; spectral radius; stationary iteration; Acceleration; Convergence; Eigenvalues and eigenfunctions; Gradient methods; Jacobian matrices; Linear systems; Neural networks; Neural networks; convergence; momentum; numerical algebra;
Conference_Titel :
Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on
Conference_Location :
Deng Leng
Print_ISBN :
978-1-4577-0535-9
DOI :
10.1109/AIMSEC.2011.6011205
