Graph-Based Algorithms for Boolean Function Manipulation
IEEE Transactions on Computers
A maximum entropy approach to natural language processing
Computational Linguistics
Arithmetic Circuits for Analog Digits
ISMVL '99 Proceedings of the Twenty Ninth IEEE International Symposium on Multiple-Valued Logic
Information Theoretic Approach to Minimization of Polynomial Expressions over GF(4)
ISMVL '00 Proceedings of the 30th IEEE International Symposium on Multiple-Valued Logic
Introduction to Quantum Computation Information
Introduction to Quantum Computation Information
Improving Web Database Access Using Decision Diagrams
AICCSA '01 Proceedings of the ACS/IEEE International Conference on Computer Systems and Applications
An Axiomatization of Generalized Entropy of Partitions
ISMVL '01 Proceedings of the 31st IEEE International Symposium on Multiple-Valued Logic
Improved use of continuous attributes in C4.5
Journal of Artificial Intelligence Research
Information theoretic measures for power analysis [logic design]
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
An improved method for computing a generalized spectral coefficient
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Efficient calculation of spectral coefficients and their applications
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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In modern science, significant advances are typically made at cross-roads of disciplines. Thus, many optimization problems in Multiple-valued Logic Design have been successfully approached using ideas and techniques from Artificial Intelligence. In particular, improvements in multiple-valued logic design have been made by exploiting information/uncertainty measures. In this paper, we review well-known information measures in the multiple-valued domain and consider some methods of finding information measures for completely or incompletely specified functions with multiple-valued and continuous attributes. In this respect, the paper addresses the problem known as discretization and introduces a method of finding an optimal representation of continuous data in the multiple-valued domain. We also propose a technique for efficient calculation of different information measures using Multiple-valued Decision Diagrams. As one application of our technique, we outline an approach to synthesizing digital circuits derived from decision diagrams that can yield to reduction in power dissipation. The paper also shows the impact in several important areas of multiple-valued system design including (i) fuzzy logic, (ii) quantum computing systems, and (iii) data mining.