Arts of VLSI circuit design
Subtitle: symmetry approaches toward zero PVT sensitivity
By: Hongjiang Song
Publisher: Xlibris Corporation
Published: 2011
Place of publication: [U.S.]
Language: eng
Number of pages: 466
ISBN-13: 9781456874674; 9781456874667
Subjects: Integrated circuits; Very large scale integration; Circuits intégrés à très grande échelle
Other titles: Symmetry approaches toward zero PVT sensitivity
Description: "This text is based on the class notes of a VLSI signal processing circuit course series (EEE598) the author developed for the EE department at Arizona State University. The materials are organized into nineteen special topics covering various state-of-the-arts symmetry based VLSI circuit design techniques for basic VLSI circuit elements, circuit modules and systems, where the symmetry principle and methods with inherently low PVT sensitivity are used to design VLSI circuits with superior scalability and performance for various VLSI SOC applications."--Cover
Notes: Includes bibliographical references and index.
Table of contents: title: ch. 1. Introduction to VLSI symmetry; title: ch. 2. VLSI reflection symmetry circuit elements; title: ch. 3. VLSI translation symmetry circuit elements; title: ch. 4. VLSI rotational symmetry circuit elements; title: ch. 5. VLSI electrical symmetry; title: ch. 6. VLSI symmetry scaling and transformations; title: ch. 7. VLSI symmetry computing; title: ch. 8. Low PVT sensitivity VLSI circuit design; title: ch. 9. Symmetry method in VLSI physical design; title: ch. 10. VLSI spatial signal processing; title: ch. 11. Symmetry approaches in VLSI design and manufacture; title: ch. 12. Symmetry methods in VLSI opamp circuit design; title: ch. 13. Symmetry methods in VLSI bandgap circuit; title: ch. 14. Symmetry methods in VLSI PLL circuit design; title: ch. 15. Symmetry methods in VLSI filter circuit design; title: ch. 16. VLSI parameter tuning circuit structures; title: ch. 17. Symmetry methods in VLSI data converter circuits; title: ch. 18. Symmetry in VLSI fuzzy logic and neural network circuits.