2009 Fiscal Year Final Research Report
Hardware Implementation of Neural Networks with Learning Capability Using Simultaneous Perturbation
| Project/Area Number |
19500198
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Single-year Grants |
|---|
| Section | 一般 |
|---|
| Research Field |
Sensitivity informatics/Soft computing
|
|---|
| Research Institution | Kansai University |
|---|
Principal Investigator |
MAEDA Yutaka Kansai University, システム理工学部, 教授 (60209393)
|
|---|
| Project Period (FY) |
2007 – 2009
|
| Keywords | ニューラルネットワーク |
|---|
| Research Abstract |
In this research, we demonstrated feasibility of a learning rule using the simultaneous perturbation optimization method for artificial neural networks. First, we showed that combination of pulse density expression and the simultaneous perturbation method is useful for hardware implementation of neural networks. Second, we fabricated support vector machine with learning mechanism using the simultaneous perturbation method based on FPGA. Finally, a pulse coupled oscillator with learning capability is realized as an analog circuit system using FPAA and the simultaneous perturbation method.
|
Research Products
(26 results)
