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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yunong Zhang Xiaojiao Guo Weimu Ma Ke Chen Binghuang Cai |
| Copyright Year | 2008 |
| Description | Author affiliation: Sun Yat-Sen Univ., Guangzhou (Yunong Zhang) |
| Abstract | Recently, a special kind of recurrent neural networks (RNN) with implicit dynamics has been proposed by Zhang et al for online time-varying problems solving (such as time-varying matrix inversion). Such a neural-dynamic system is elegantly designed by defining a matrix-valued error function rather than the usual scalar-valued norm-based error function. Its computational error can be made decrease to zero globally and exponentially. For the final purpose of field programmable gate array (FPGA) and application-specific integrated circuit (ASIC) realization, we investigate in this paper the MATLAB Simulink modeling and simulative verification of such a Zhang neural network (ZNN). By using click-and-drag mouse operations, it is easier to model and simulate in comparison with MATLAB coding. Both convergence and robustness properties of such a ZNN model are analyzed, which substantiate the effectiveness of Zhang neural network on inverting the time-varying matrices. |
| Starting Page | 1480 |
| Ending Page | 1485 |
| File Size | 415970 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424416851 |
| DOI | 10.1109/ICNSC.2008.4525454 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-04-06 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | MATLAB Mathematical model Neural networks Recurrent neural networks Field programmable gate arrays Application specific integrated circuits Circuit simulation Problem-solving Integrated circuit modeling Computational modeling |
| Content Type | Text |
| Resource Type | Article |
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