Foundations of robotics: analysis and control
Foundations of robotics: analysis and control
Three-Dimensional Structured Networks for Matrix Equation Solving
IEEE Transactions on Computers - Special issue on artificial neural networks
Parallel structured networks for solving a wide variety of matrix algebra problems
Journal of Parallel and Distributed Computing - Special issue on neural computing on massively parallel processing
Neural network approach to computing matrix inversion
Applied Mathematics and Computation
A recurrent neural network for real-time matrix inversion
Applied Mathematics and Computation
Solving simultaneous linear equations using recurrent neural networks
Information Sciences—Intelligent Systems: An International Journal
Linear System Theory and Design
Linear System Theory and Design
Neural Networks for Optimization and Signal Processing
Neural Networks for Optimization and Signal Processing
Recurrent neural networks for LU decomposition and Cholesky factorization
Mathematical and Computer Modelling: An International Journal
| Hi-index | 0.98 |
A recurrent neural network is presented for computing pseudoinverse matrices. Under the zero initial state condition, the recurrent neural network derived from a reflexive generalized inverse problem which involves two matrix equations can be used to solve the corresponding pseudoinverse problem which involves four matrix equations. The proposed recurrent neural network based on the reflexive generalized inverse problem simplifies network dynamics and makes physical implementation easier. The proposed recurrent neural network is proven and shown to be asymptotically stable and capable of computing pseudoinverse matrices. Three numerical examples are illustrated to show the performance of the proposed recurrent neural network.