Abstract
Optimal message scheduling is one of the key issues in the field of controller area network (CAN) bus system. There are numerous approaches related to this issue. Most of them are essentially based on priority-based strategies. In 1, we utilized Radial Basic Function (RBF) network 2 as a message scheduling controller to dynamically schedule messages. Furthermore, an online Backward-Through-Time (BTT) algorithm is presented for parameter optimization under a priori fixed network structure. Intuitively, an inappropriate RBF network structure leads to performance degradation. In the worst case, the CAN system diverges. In this paper, we extend our previous works by including Minimal Resource Allocation (MRA) algorithm for structure determination, In this way, both problems of parameter optimization and structure determination can be resolved at the same time. Simulation results demonstrated that the proposed BTT with MRA methods outperform our previous results in terms of convergence time, stability, and the number of required hidden neurons (or radial basis functions).
| Original language | English |
|---|---|
| Title of host publication | Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings |
| Pages | 998-1005 |
| Number of pages | 8 |
| Edition | PART 3 |
| Publication status | Published - 2007 Dec 1 |
| Event | 4th International Symposium on Neural Networks, ISNN 2007 - Nanjing, China Duration: 2007 Jun 3 → 2007 Jun 7 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Number | PART 3 |
| Volume | 4493 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 4th International Symposium on Neural Networks, ISNN 2007 |
|---|---|
| Country | China |
| City | Nanjing |
| Period | 07-06-03 → 07-06-07 |
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All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)
Cite this
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Minimal resource allocation on CAN bus using radial basis function networks. / Wei, Yan Hao; Chen, Mu Song; Lin, Chuan Ku; Hwang, Chi Pan.
Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 3. ed. 2007. p. 998-1005 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4493 LNCS, No. PART 3).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Minimal resource allocation on CAN bus using radial basis function networks
AU - Wei, Yan Hao
AU - Chen, Mu Song
AU - Lin, Chuan Ku
AU - Hwang, Chi Pan
PY - 2007/12/1
Y1 - 2007/12/1
N2 - Optimal message scheduling is one of the key issues in the field of controller area network (CAN) bus system. There are numerous approaches related to this issue. Most of them are essentially based on priority-based strategies. In 1, we utilized Radial Basic Function (RBF) network 2 as a message scheduling controller to dynamically schedule messages. Furthermore, an online Backward-Through-Time (BTT) algorithm is presented for parameter optimization under a priori fixed network structure. Intuitively, an inappropriate RBF network structure leads to performance degradation. In the worst case, the CAN system diverges. In this paper, we extend our previous works by including Minimal Resource Allocation (MRA) algorithm for structure determination, In this way, both problems of parameter optimization and structure determination can be resolved at the same time. Simulation results demonstrated that the proposed BTT with MRA methods outperform our previous results in terms of convergence time, stability, and the number of required hidden neurons (or radial basis functions).
AB - Optimal message scheduling is one of the key issues in the field of controller area network (CAN) bus system. There are numerous approaches related to this issue. Most of them are essentially based on priority-based strategies. In 1, we utilized Radial Basic Function (RBF) network 2 as a message scheduling controller to dynamically schedule messages. Furthermore, an online Backward-Through-Time (BTT) algorithm is presented for parameter optimization under a priori fixed network structure. Intuitively, an inappropriate RBF network structure leads to performance degradation. In the worst case, the CAN system diverges. In this paper, we extend our previous works by including Minimal Resource Allocation (MRA) algorithm for structure determination, In this way, both problems of parameter optimization and structure determination can be resolved at the same time. Simulation results demonstrated that the proposed BTT with MRA methods outperform our previous results in terms of convergence time, stability, and the number of required hidden neurons (or radial basis functions).
UR - http://www.scopus.com/inward/record.url?scp=38049174247&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=38049174247&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:38049174247
SN - 9783540723943
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 998
EP - 1005
BT - Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings
ER -