一、課程說明(Course Description)
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<br>The nervous systems of even simple animals contain computing paradigms far more 
<br>effective than any found in currently available computers. These nervous systems 
<br>can be realized in silicon integrated circuits. This is the motivation of 
<br>neuromorphic engineering.
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<br>This course is to introduce students to neuromorphic engineering with various 
<br>analog VLSI circuits. The course will start from the basic transistor physics. MOS 
<br>transistor in the subthreshold region and various circuit building blocks will be 
<br>introduced. Some system-level integration examples will be discussed at the end if 
<br>time permits. 
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<br>Junior and senior undergraduate students are also welcome!
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<br>二、指定用書(Text Books)
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<br>Liu, Kramer, Indiveri, Delbruck, and Douglas, "Analog VLSI: Circuits and 
<br>Principles"
<br>The MIT Press, 2002, ISBN：0262122553
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<br>三、參考書籍(References)
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<br>C. A. Mead, "Analog VLSI and Neural Systems"
<br>Mead and Ismail, "Analog VLSI implementation of Neural Systems"
<br>Ismail and Fiez, "Analog VLSI Signal and Information Processing"
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<br>四、教學方式(Teaching Method)
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<br>The course is lectured in English with power-point handouts.
<br>Related materials will be distributed in class
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<br>五、教學進度(Syllabus)
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<br>1. Introduction to Neuromorphic Engineering
<br>2. Transistor physics and characteristics
<br>3. Basic static circuits
<br>4. Transconductance amplifier
<br>5. Current-mode circuits
<br>6. Basic Arithmetic circuits
<br>7. Translinear Circuits
<br>8. Floating Gate MOSFET
<br>9. Silicon Learning Array
<br>10. Multiple-Input Translinear Element (MITE) Networks
<br>11. Linear Systems
<br>12. Integrators and Differentiators
<br>13. Autozeroing amplifier
<br>14. Silicon Neuron and Axons
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<br>六、成績考核(Evaluation)
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<br>七、可連結之網頁位址
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<br>LMS system