2000 Fiscal Year Final Research Report Summary
Fundamental Study on Real-Time Brain Computer
| Project/Area Number |
11650382
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Single-year Grants |
|---|
| Section | 一般 |
|---|
| Research Field |
情報通信工学
|
|---|
| Research Institution | HIROSHIMA UNIVERSITY |
|---|
Principal Investigator |
AE Tadashi Faculty of Engineering, HIROSHIMA UNIVERSITY, Professor, 工学部, 教授 (50005386)
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
SAKAI Keiichi Faculty of Engineering, HIROSHIMA UNIVERSITY, Research Associate, 工学部, 助手 (90274117)
ARAKI Hiroyuki Faculty of Engineering, HIROSHIMA UNIVERSITY, Research Associate, 工学部, 助手 (00304402)
KAKUGAWA Hirotsugu Faculty of Engineering, HIROSHIMA UNIVERSITY, Associate Professor, 工学部, 助教授 (80253110)
|
|---|
| Project Period (FY) |
1999 – 2000
|
| Keywords | Brainware / Brain-like Information Processing / Real-Time Processing / Inductive Learning / Automata Learning |
|---|
| Research Abstract |
The model for real-time brain-like information processing is not established yet. The neural network is a typical model for human brain and has been discussed by a lot of researchers. The recurrent network plays an important role of system model for human brain, but its learning includes too difficult problems. We have proposed a two-level model, i.e., a hybrid system model mixed with the neural network and the automaton. The model is practically utilized for a kind of applications. We also introduced an extended vector addition system, i.e., a structured vector addition system.
The vector addition system (in short, VAS) is originally proposed by R.Karp et al. and a parallel processing model. The VAS seems to be far from the neural network, but it is an excellent "macro" model for the brain behavior, The original VAS, however, is weak to represent the control mechanism, and therefore, we propose a structured VAS, where the control mechanism plays a role of simulating the dynamical behavior of human emotion, together with the state transition of vectors. A VLIW architecture is used for hardware mechanism.
As a result we could achieve a fundamental research for real-time brain- like computer.
|
