Brainware: Bio-inspired Architecture and Its Hardware Implementation
The human brain, the ultimate intelligent processor, can handle ambiguous and uncertain information adequately. The implementation of such a human-brain architecture and function is called OC brainwareOCO. Brainware is a candidate for the new tool that will realize a human-friendly computer society. As one of the LSI implementations of brainware, a OC bio-inspiredOCO hardware system is discussed in this book. Consisting of eight enriched versions of papers selected from IIZUKA ''98, this volume provides wide coverage, from neuronal function devices to vision systems, chaotic systems, and also an effective design methodology of hierarchical large-scale neural systems inspired by neuroscience. It can serve as a reference for graduate students and researchers working in the field of brainware. It is also a source of inspiration for research towards the realization of a silicon brain. Contents: Neuron MOS Transistor: The Concept and Its Application (T Shibata); Adaptive Learning Neuron Integrated Circuits Using Ferroelectric-Gate FETs (S-M Yoon et al.); An AnalogOCoDigital Merged Circuit Architecture Using PWM Techniques for Bio-Inspired Nonlinear Dynamical Systems (T Morie et al.); Application-Driven Design of Bio-Inspired Low-Power Vision Circuits and Systems (A KAnig et al.); Motion Detection with Bio-Inspired Analog MOS Circuits (H Yonezu et al.); cents MOS Cellular-Automaton Circuit for Picture Processing (M Ikebe & Y Amemiya); Semiconductor Chaos-Generating Elements of Simple Structure and Their Integration (K Hoh et al.); Computation in Single Neuron with Dendritic Trees (N Katayama et al.). Readership: Graduate students, researchers and industrialists in artificial intelligence, neural networks, machine perception, computer vision, pattern/handwriting recognition, image analysis and biocomputing."
What people are saying - Write a review
We haven't found any reviews in the usual places.
The Concept and Its Application
Chapter 2 Adaptive Learning Neuron Integrated Circuits Using FerroelectricGate FETs
Chapter 3 An Analogdigital Merged Circuit Architecture Using PWM Techniques for BioInspired Nonlinear Dynamical Systems ...
Chapter 4 ApplicationDriven Design of BioInspired LowPower Vision Circuits Systems
Chapter 5 Motion Detection with BioInspired Analog MOS Circuits
Chapter 6 vMOS CellularAutomaton Circuit for Picture Processing
Other editions - View all
Brainware: Bio-Inspired Architecture and Its Hardware Implementation
Limited preview - 2001
1/MOS circuit active dendrites adaptive-learning algorithm applications architecture artiﬁcial association processor binary bio-inspired capacitance capacitor cell circuit cellular automaton chaos chaotic characteristics classiﬁer clock CMOS CMOS Schmitt-trigger compartmental neuron model conﬁguration CUJT Dendritic Spines dendritic tree drain current dynamics edge detection EEPROM Electrical Engineering Electron Devices fabricated ﬁeld ﬁgure ﬁrst ﬁxed ﬂoating gate ﬂow function gate voltage hardware IEEE image sensor information processing inhibitory Integrated Circuits Japan E-mail Koichiro Hoh logic gate MFSFET MOS FETs neural network neuron circuit Neuron MOS Ohmi operation oscillation output pulse frequency parallel parameters pixel pixel cell potential power dissipation PWM signals QuickCog SBT ﬁlm semiconductor Shibata shown in Fig simulation Soft Computing spine structure synaptic inputs synaptic integration synaptic interactions template circuit template vectors thinning threshold voltage Tohoku University transistor University of Technology University of Tokyo vision chip visual VLSI implementation vMOS waveforms