Name
Abstract | ||
|---|---|---|
Static matrix inverse solving has been studied for many years. In this paper, we aim at solving a dynamic complex-valued matrix inverse. Specifically, based on the artful combination of a conventional gradient neural network and the recently-proposed Zhang neural network, a novel complex-valued neural network model is presented and investigated for computing the dynamic complex-valued matrix inverse in real time. A hardware implementation structure is also offered. Moreover, both theoretical analysis and simulation results substantiate the effectiveness and advantages of the proposed recurrent neural network model for dynamic complex-valued matrix inversion. |
Year | Venue | Keywords |
|---|---|---|
2016 | JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS | complex-valued matrix inverse,gradient neural network,Zhang neural network,dynamic |
Field | DocType | Volume |
Zhang neural network,Feedforward neural network,Pattern recognition,Computer science,Matrix (mathematics),Inversion (meteorology),Stochastic neural network,Recurrent neural network,Probabilistic neural network,Artificial intelligence,Artificial neural network,Machine learning | Journal | 20 |
Issue | ISSN | Citations |
1 | 1343-0130 | 4 |
PageRank | References | Authors |
0.40 | 8 | 5 |