Algorithms of Eigensubspace Estimation Based on Discrete Recurrent Neural Networks

Based on the eigensubspace estimation using discrete recurrent neural networks, we propose algorithms to solve the problem of eigensubspace estimation for positive definite symmetric matrix. Neural networks are formulated as discrete time systems, they have advantages for computer simulations over digital simulations of continuous time neural network models. Thus they can be easily implemented in digital hardware. Simulation results are given to show the performance of networks.