Matrix analysis
Three-Dimensional Structured Networks for Matrix Equation Solving
IEEE Transactions on Computers - Special issue on artificial neural networks
Introduction to artificial neural systems
Introduction to artificial neural systems
A deterministic annealing neural network for convex programming
Neural Networks
Neural Networks for Optimization and Signal Processing
Neural Networks for Optimization and Signal Processing
A Simplified Neural Network for Linear Matrix Inequality Problems
Neural Processing Letters
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Linear matrix inequalities (LMIs) play avery important role in postmodern control by providinga framework that unifies many concepts. While numerouspapers have appeared cataloging applications of LMIsto control system analysis and design, there have beenfew publications in the literature describing thenumerical solution of these problems. Specially, neural network processing has rarely been used to solve those problems.This paper attempts topropose a new approach to solving a class of LMIsusing recurrent neural networks. The nature ofparallel and distributed processing renders thesenetworks, which possess the computational advantages overthe traditional sequential algorithms in real-timeapplications. The proposed networks are proven to be largelyasymptotical and capable of solving LMIs.Some illustrative examples are provided todemonstrate the proposed results.