Name
Title | ||
|---|---|---|
Discontinuous Neural Networks for Finite-Time Solution of Time-Dependent Linear Equations. |
Abstract | ||
|---|---|---|
This paper considers a class of nonsmooth neural networks with discontinuous hard-limiter (signum) neuron activations for solving time-dependent (TD) systems of algebraic linear equations (ALEs). The networks are defined by the subdifferential with respect to the state variables of an energy function given by the L1 norm of the error between the state and the TD-ALE solution. It is shown that when... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TCYB.2015.2479118 | IEEE Transactions on Cybernetics |
Keywords | Field | DocType |
Biological neural networks,Mathematical model,Lyapunov methods,Neurons,Convergence,Convex functions | Convergence (routing),Linear equation,Mathematical optimization,Matrix (mathematics),Subderivative,Dynamical systems theory,Convex function,Artificial intelligence,State variable,Artificial neural network,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
46 | 11 | 2168-2267 |
Citations | PageRank | References |
18 | 0.59 | 31 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mauro Di Marco | 1 | 205 | 18.38 |
| Mauro Forti | 2 | 398 | 36.80 |
| Paolo Nistri | 3 | 212 | 33.80 |
| Luca Pancioni | 4 | 207 | 17.58 |