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Analysis and Design of VLSI Analog-Digital Interface Circuits

IC776CA (Berkeley EECS247)

Spring 2004 - 3 units

 

ANNOUNCEMENTS

  • (1/23) The class office hour is changed to Tue. & Wed. 2-3pm PT. During the office hour you'll need to first call in the CalView office and then get it transferred to the consultant's contact.

  • (1/22) Welcome to Spring 2004 IC776CA class. Class web page is up and in construction right now. You may want to check back often for updates and announcements.


Lecturer:

Prof. Bernard E. Boser

Course Consultant:

Huifang Qin    (Email: huifangq@eecs.berkeley.edu)

  • Office Hours: Tue. & Wed. 2-3pm PT

  • You may contact the Cal View Office to make an appointment if those times do not work for you.

  • Class mailing list: n247@cory.eecs.berkeley.edu, when asking questions that may be of a concern of the whole class, e.g., regarding homework, please use this email alias so everyone will receive a copy.


Contact:

  • Course content/prerequisites: Email the course consultant.

  • Registration, pricing, administrative: Contact Cal VIEW.

Cal VIEW Office

205 McLaughlin Hall

University of California

Berkeley, CA 94720

Phone: (510) 642-5776

Fax: (510) 643-5877

Email: ntu@coe.berkeley.edu

Web Page: www.coe.berkeley.edu/calview


Course Description:

This course covers various aspects of the design of integrated analog and analog-digital interface electronics  at the building block and system level. Specific topics include

  • Continuous-time and sampled-data filters

  • Oversampled A/D converters

  • Nyquist rate A/D- and D/A-converters

  • Digital data receivers and equalization

Problem-specific CAD tools such as MATLAB (filter design), HSPICE, and SPECTRE will be used throughout the course.


Prerequisites:

Familiarity with analog circuit analysis (transistor models, small signal circuit analysis, frequency compensation, etc.) and building blocks (amplifiers, references, mirrors, etc.) as taught in EE140 and EE142. Circuit simulation with HSPICE. A basic course in signal processing (Laplace transform, sampled data systems, filter synthesis) is very helpful.


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Last modified: 一月 23, 2004