Boolean Reasoning

Concise text begins with overview of elementary mathematical concepts and outlines theory of Boolean algebras; defines operators for elimination, division, and expansion; covers syllogistic reasoning, solution of Boolean equations, functional deduction. 1990 edition.

Reasoning in Boolean Networks provides a detailed treatment of recent research advances in algorithmic techniques for logic synthesis, test generation and formal verification of digital circuits. The book presents the central idea of approaching design automation problems for logic-level circuits by specific Boolean reasoning techniques. While Boolean reasoning techniques have been a central element of two-level circuit theory for many decades Reasoning in Boolean Networks describes a basic reasoning methodology for multi-level circuits. This leads to a unified view on two-level and multi-level logic synthesis. The presented reasoning techniques are applied to various CAD-problems to demonstrate their usefulness for today's industrially relevant problems. Reasoning in Boolean Networks provides lucid descriptions of basic algorithmic concepts in automatic test pattern generation, logic synthesis and verification and elaborates their intimate relationship to provide further intuition and insight into the subject. Numerous examples are provide for ease in understanding the material. Reasoning in Boolean Networks is intended for researchers in logic synthesis, VLSI testing and formal verification as well as for integrated circuit designers who want to enhance their understanding of basic CAD methodologies.

The consideration of symbolic machine learning algorithms as an entire class will make it possible, in the future, to generate algorithms, with the aid of some parameters, depending on the initial users' requirements and the quality of solving targeted problems in domain applications. Diagnostic Test Approaches to Machine Learning and Commonsense Reasoning Systems surveys, analyzes, and compares the most effective algorithms for mining all kinds of logical rules. Global academics and professionals in related fields have come together to create this unique knowledge-sharing resources which will serve as a forum for future collaborations.

This book constitutes the refereed proceedings of the 10th International Symposium on Methodologies for Intelligent Systems, ISMIS'97, held in Charlotte, NC, USA, in October 1997. The 57 revised full papers were selected from a total of 117 submissions. Also included are four invited papers. Among the topics covered are intelligent information systems, approximate reasoning, evolutionary computation, knowledge representation and integration, learning and knowledge discovery, AI-Logics, discovery systems, data mining, query processing, etc.

The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence.This fifth volume of the Transactions on Rough Sets is dedicated to the monumental life, work and creative genius of Zdzis{l}aw Pawlak, the originator of rough sets, who passed away in April 2006. It opens with a commemorative article that gives a brief coverage of Pawlak's works in rough set theory, molecular computing, philosophy, painting and poetry. Fifteen papers explore the theory of rough sets in various domains as well as new applications of rough sets. In addition, this volume of the TRS includes a complete monograph on rough sets and approximate Boolean reasoning systems that includes both the foundations as well as applications of data mining.

This volume contains the papers selected for presentation at the 10th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2005, organized at the University of Regina, August 31st–September 3rd, 2005.

This volume, containing contributions by experts from all over the world, is a collection of 21 articles which present review and research material describing the evolution and recent developments of various pattern recognition methodologies, ranging from statistical, syntactic/linguistic, fuzzy-set-theoretic, neural, genetic-algorithmic and rough-set-theoretic to hybrid soft computing, with significant real-life applications. In addition, the book describes efficient soft machine learning algorithms for data mining and knowledge discovery. With a balanced mixture of theory, algorithms and applications, as well as up-to-date information and an extensive bibliography, Pattern Recognition: From Classical to Modern Approaches is a very useful resource. Contents: Pattern Recognition: Evolution of Methodologies and Data Mining (A Pal & S K Pal); Adaptive Stochastic Algorithms for Pattern Classification (M A L Thathachar & P S Sastry); Shape in Images (K V Mardia); Decision Trees for Classification: A Review and Some New Results (R Kothari & M Dong); Syntactic Pattern Recognition (A K Majumder & A K Ray); Fuzzy Sets as a Logic Canvas for Pattern Recognition (W Pedrycz & N Pizzi); Neural Network Based Pattern Recognition (V David Sanchez A); Networks of Spiking Neurons in Data Mining (K Cios & D M Sala); Genetic Algorithms, Pattern Classification and Neural Networks Design (S Bandyopadhyay et al.); Rough Sets in Pattern Recognition (A Skowron & R Swiniarski); Automated Generation of Qualitative Representations of Complex Objects by Hybrid Soft-Computing Methods (E H Ruspini & I S Zwir); Writing Speed and Writing Sequence Invariant On-line Handwriting Recognition (S-H Cha & S N Srihari); Tongue Diagnosis Based on Biometric Pattern Recognition Technology (K Wang et al.); and other papers. Readership: Graduate students, researchers and academics in pattern recognition.

This book constitutes the thoroughly refereed conference proceedings of the 14th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, RSFDGrC 2013, held in Halifax, Canada in October 2013 as one of the co-located conference of the 2013 Joint Rough Set Symposium, JRS 2013. The 69 papers (including 44 regular and 25 short papers) included in the JRS proceedings (LNCS 8170 and LNCS 8171) were carefully reviewed and selected from 106 submissions. The papers in this volume cover topics such as inconsistency, incompleteness, non-determinism; fuzzy and rough hybridization; granular computing and covering-based rough sets; soft clustering; image and medical data analysis.