Convergence of a Finite-Time Zhang Neural Network for Moore–Penrose Matrix Inversion

Author:

Sowmya G.,Thangavel P.

Publisher

Springer Singapore

Reference12 articles.

1. Sharina Huang, M.C., Zhao, G.: Tensor extreme learning design via generalized Moore–Penrose inverse and triangular type-2 fuzzy sets. Neural Comput. Appl. 31, 5641–5651 (2019)

2. Sheng, X.: Computation of weighted Moore–Penrose inverse through Gauss-Jordan elimination on bordered matrices. Appl. Math. Comput. 323, 64–74 (2018)

3. Sturges, R.H.: Analog matrix inversion (robot kinematics). IEEE J. Robotics Autom. 4(2), 157–162 (1988)

4. Hunter, J.J.: Generalized inverses of Markovian kernels in terms of properties of the Markov chain. Linear Algebra Appl. 447, 38–55 (2014) (special Issue - Memorial Issue for Michael Neumann and Uriel Rothblum)

5. Lv, X., Xiao, L., Tan, Z., Yang, Z., Yuan, J.: Improved gradient neural networks for solving Moore–Penrose inverse of full-rank matrix. Neural Process. Lett. 50 (2019)

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