Neural networks for solving systems of linear equations. II. Minimax and least absolute value problems
From MaRDI portal
Publication:4036511
DOI10.1109/82.193316zbMath0825.94288OpenAlexW2162406405WikidataQ60487042 ScholiaQ60487042MaRDI QIDQ4036511
Andrzej Cichocki, Rolf Unbehauen
Publication date: 16 May 1993
Published in: IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1109/82.193316
Lua error in Module:PublicationMSCList at line 37: attempt to index local 'msc_result' (a nil value).
Related Items (7)
Decentralized proximal splitting algorithms for composite constrained convex optimization ⋮ Real-time computation of the eigenvectors of a class of positive definite matrices ⋮ Real-time computation of singular vectors ⋮ A consensus algorithm based on collective neurodynamic system for distributed optimization with linear and bound constraints ⋮ A Cooperative Recurrent Neural Network for Solving L1 Estimation Problems with General Linear Constraints ⋮ Analog approach for the eigen-decomposition of positive definite matrices ⋮ Recurrent neural networks for LU decomposition and Cholesky factorization
This page was built for publication: Neural networks for solving systems of linear equations. II. Minimax and least absolute value problems
