| Project/Area Number |
13835005
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Institution | Kyushu Institute of Technology (2002)
Hiroshima University (2001) |
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Principal Investigator |
MORIE Takashi Kyushu Institute of Technology, Graduate School of Life Science and Systems Engineering, Professor, 大学院・生命体工学研究科, 教授 (20294530)
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| Co-Investigator(Kenkyū-buntansha) |
IWATA Atsushi Hiroshima University, Graduate School of Advanced Sciences of Matter, Professor, 大学院・先端物質科学研究科, 教授 (30263734)
永田 真 広島大学, 大学院・先端物質科学研究科, 助手 (40274138)
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| Project Period (FY) |
2001 – 2002
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| Project Status |
Completed (Fiscal Year 2002)
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| Budget Amount *help |
¥3,600,000 (Direct Cost: ¥3,600,000)
Fiscal Year 2002: ¥1,800,000 (Direct Cost: ¥1,800,000)
Fiscal Year 2001: ¥1,800,000 (Direct Cost: ¥1,800,000)
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| Keywords | pulse modulation method / spiking neuron / integrate-and-fire-neuron / Hopfield networks / associative memory / nanodot MOSFET / nanotechnology / パルス幅変調方式 |
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| Research Abstract |
1. Development of an image processing LSI using nonlinear dynamics with pulse timing
An oscillator network LSI that performs image region segmentation and extraction using oscillation phase synchronization was designed using analog-digital merged/mixed architecture. In this LSI, the circuit block for nonlinear dynamics consists of pulse modulation circuits, and the weight memory and control part consists of digital circuits.
2. Development of an algorithm for brain-like information processing circuits using pulse timing
By applying a spiking neuron model (integrate-and-fire type) to feedback networks, we can operate the networks faster. The basic concept is that signals inputted earlier are considered more important. To discriminate between feedback signals and late-inputted signals, a global inhibitor neuron with ramped inhibition and a reset mechanism at firing in a neuron are introduced. From the circuit simulation results of associative memory operation in Hopfield networks with 20 neurons, it was confirmed that the proposed circuit converges 20 times faster than the conventional pulse-width modulation circuit.
3. Design of a spiking neuron circuit with multi-nanodot MOSFETs
For a circuit technique in the post-CMOS era, a spiking neuron circuit with multi-nanodot MOSFETs is proposed. The circuit can generate a post-synaptic potential much more efficiently and with ultra-low power dissipation. The nanodot structure will be constructed by using self-assembly processes using nanotechnology.
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