A New Transitive Closure Algorithm with Application to Redundancy Identi cation

نویسندگان

  • Vivek Gaur
  • Vishwani D. Agrawal
  • Michael L. Bushnell
چکیده

A new transitive closur ealgorithm is presented for implication graphs that c ontainpartial implications. In the presence of partial implications, a vertex can assume the true state when all vertices that p artially imply it become true. Such graphs provide a more complete representation of a logic cir cuit than is possible with the conventional pair-wise implications. A napplic ation of the new transitive closur e algorithm to redundancy identi cation shows signi cantly improved results. Empiric ally, we nd the computational complexity of transitive closure to be linear for the implication graphs of the ISCAS benchmark circuits.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Theorems on Redundancy Identi cation

There is a class of implication-based methods that identify logic redundancy from circuit topology and without any primary input assignment. These methods are less complex than automatic test pattern generation (ATPG) but identify only a subset of all redundancies. This paper provides new results to enlarge this subset. Contributions are a xed-value theorem and two theorems on fanout stem unobs...

متن کامل

SECURING INTERPRETABILITY OF FUZZY MODELS FOR MODELING NONLINEAR MIMO SYSTEMS USING A HYBRID OF EVOLUTIONARY ALGORITHMS

In this study, a Multi-Objective Genetic Algorithm (MOGA) is utilized to extract interpretable and compact fuzzy rule bases for modeling nonlinear Multi-input Multi-output (MIMO) systems. In the process of non- linear system identi cation, structure selection, parameter estimation, model performance and model validation are important objectives. Furthermore, se- curing low-level and high-level ...

متن کامل

Eecient Transitive Closure Computation

We present two new transitive closure algorithms that are based on strong component detection. The algorithms scan the input graph only once without generating partial successor sets for each node. The new algorithms eliminate the redundancy caused by strong components more e ciently than previous transitive closure algorithms. We present statistically sound simulation experiments showing that ...

متن کامل

Genetic Algorithm and Simulated Annealing for Redundancy Allocation Problem with Cold-standby Strategy

This paper presents a new mathematical model for a redundancyallocation problem (RAP) withcold-standby redundancy strategy and multiple component choices.The applications of the proposed model arecommon in electrical power, transformation,telecommunication systems,etc.Manystudies have concentrated onone type of time-to-failure, butin thispaper, two components of time-to-failures which follow hy...

متن کامل

The Effect of Transitive Closure on the Calibration of Logistic Regression for Entity Resolution

This paper describes a series of experiments in using logistic regression machine learning as a method for entity resolution. From these experiments the authors concluded that when a supervised ML algorithm is trained to classify a pair of entity references as linked or not linked pair, the evaluation of the model’s performance should take into account the transitive closure of its pairwise lin...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2001