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Alberto Sangiovanni-Vincentelli

Researcher at University of California, Berkeley

Publications -  946
Citations -  47259

Alberto Sangiovanni-Vincentelli is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Logic synthesis & Finite-state machine. The author has an hindex of 99, co-authored 934 publications receiving 45201 citations. Previous affiliations of Alberto Sangiovanni-Vincentelli include National University of Singapore & Lawrence Berkeley National Laboratory.

Papers
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Journal ArticleDOI

Symbolic minimization of multilevel logic and the input encoding problem

TL;DR: Techniques for the optimization of multilevel logic with multiple-valued input variable is presented to tackle the input encoding problem in logic synthesis, where binary codes must be found for the different values that a symbolic input variable can take.
Proceedings ArticleDOI

Valid clocking in wavepipelined circuits

TL;DR: In this paper, the authors present an analysis of valid clock rates in wavepipelined circuits using a technique called Timed Boolean Functions, and demonstrate discontinuity and non-monotonicity of the harmonic number H (r) as a+tion of the clock period r.
Journal Article

Schedulability Analysis of Petri Nets Based on Structural Properties

TL;DR: In this article, an approach for schedulability analysis based solely on Petri net structure is proposed, which shows that unschedulability can be caused by a structural relation among transitions modelling non-deterministic choices.
Proceedings ArticleDOI

A behavioral representation for Nyquist rate A/D converters

TL;DR: A behavioral representation for the class of Nyquist rate A/D (analog-to-digital) converters is presented, made of a variance-covariance matrix, Sigma /sub t/, which is a generalization of the integral nonlinearity vector.
Book ChapterDOI

Decomposition Techniques for Efficient ROBDD Construction

TL;DR: It is shown that for a large number of applications, it is more efficient to construct the ROBDD by a suitable combination of top-down and bottom-up approaches than a purely bottom- up approach.