Set theory

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Set theory is the branch of mathematics that studies sets, which are collections of objects. (Wikipedia.org)






Conferences related to Set theory

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2019 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)

Promote the exchange of ideas between academia and industry in the field of computer and networks dependability


2019 IEEE 58th Conference on Decision and Control (CDC)

The CDC is recognized as the premier scientific and engineering conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, systems and control, and related areas.The 58th CDC will feature contributed and invited papers, as well as workshops and may include tutorial sessions.The IEEE CDC is hosted by the IEEE Control Systems Society (CSS) in cooperation with the Society for Industrial and Applied Mathematics (SIAM), the Institute for Operations Research and the Management Sciences (INFORMS), the Japanese Society for Instrument and Control Engineers (SICE), and the European Union Control Association (EUCA).


2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Early Vision and Sensors Color, Illumination and Texture Segmentation and Grouping Motion and TrackingStereo and Structure from Motion Image -Based Modeling Physics -Based Modeling Statistical Methods and Learning in VisionVideo Surveillance and Monitoring Object, Event and Scene Recognition Vision - Based Graphics Image and Video RetrievalPerformance Evaluation Applications


GLOBECOM 2019 - 2019 IEEE Global Communications Conference

Provides a full program of technical and professional activities spanning hot topics in voice, data, image and multimedia communications and networking.


ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

ICASSP is the world’s largest and most comprehensive technical conference focused on signal processing and its applications. The conference will feature world-class presentations by internationally renowned speakers, cutting-edge session topics and provide a fantastic opportunity to network with like-minded professionals from around the world.


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Periodicals related to Set theory

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Antennas and Propagation, IEEE Transactions on

Experimental and theoretical advances in antennas including design and development, and in the propagation of electromagnetic waves including scattering, diffraction and interaction with continuous media; and applications pertinent to antennas and propagation, such as remote sensing, applied optics, and millimeter and submillimeter wave techniques.


Antennas and Wireless Propagation Letters, IEEE

IEEE Antennas and Wireless Propagation Letters (AWP Letters) will be devoted to the rapid electronic publication of short manuscripts in the technical areas of Antennas and Wireless Propagation.


Automatic Control, IEEE Transactions on

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...


Automation Science and Engineering, IEEE Transactions on

The IEEE Transactions on Automation Sciences and Engineering (T-ASE) publishes fundamental papers on Automation, emphasizing scientific results that advance efficiency, quality, productivity, and reliability. T-ASE encourages interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, operations research, and other fields. We welcome results relevant to industries such as agriculture, biotechnology, healthcare, home automation, maintenance, manufacturing, pharmaceuticals, retail, ...


Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


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Most published Xplore authors for Set theory

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Xplore Articles related to Set theory

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A survey of some results in lattice-valued model theory

[1988] Proceedings. The Eighteenth International Symposium on Multiple-Valued Logic, 1988

The author surveys some of his published results on the model theory of lattice-valued logic. Among the results surveyed are: the fundamental theorem of ultraproducts, the compactness theorem, the LST theorem, and the omitting types theorem. A proof of the compactness theorem is appended.<<ETX>>


The Development of Fuzzy Rough Sets with the Use of Structures and Algebras of Axiomatic Fuzzy Sets

IEEE Transactions on Knowledge and Data Engineering, 2009

The notion of a rough set was originally proposed by Pawlak underwent a number of extensions and generalizations. Dubois and Prade (1990) introduced fuzzy rough sets which involve the use of rough sets and fuzzy sets within a single framework. Radzikowska and Kerre (2002) proposed a broad family of fuzzy rough sets, referred to as (phi, t)-fuzzy rough sets which ...


Normal forms of fuzzy middle and fuzzy contradictions

IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 1999

The expressions of "excluded middle" and "crisp contradiction" are reexamined starting with their original linguistic expressions which are first restated in propositional and then predicate forms. It is shown that, in order to generalize the truth tables and hence the normal forms, the membership assignments in predicate expressions must be separated from their truth qualification. In two-valued logic, there is ...


Logical calculi of rough-set granules in problems of approximate synthesis in distributed systems

Proceedings Third International Conference on Computational Intelligence and Multimedia Applications. ICCIMA'99 (Cat. No.PR00300), 1999

A logical calculus of granules is presented. This calculus provides a framework for the approximate synthesis of solutions under uncertainty by distributed systems. The presented calculus is based on rough mereology, a paradigm for approximate reasoning developed by the authors which blends together and relies on the mereology ideas of St. Lesniewski (see L. Polkowski and A. Skowron, Intell. Automation ...


Intelligence vague information analysis and decision support system

Proceedings of the 4th World Congress on Intelligent Control and Automation (Cat. No.02EX527), 2002

With a rapid growth of interest in recent years, vague set has become an effective tool to handle inexact data in the fields of fuzzy information processing. In this paper, I use vague set theory on information analysis and decision support system, set up vague information analysis system, and develop fuzzy gray matter element space decision system into vague gray ...


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Educational Resources on Set theory

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IEEE.tv Videos

Fuzzy and Soft Methods for Multi-Criteria Decision Making - Ronald R Yager - WCCI 2016
Applying Control Theory to the Design of Cancer Therapy
IMS MicroApps: Nonlinear Co-Simulation with Real-Time Channel Measurements
IMS MicroApp: Advances in High Frequency Printed Circuit Board (PCB)
IMS Organizer: Ramesh Gupta, Technical Program Chair for IMS 2011
IMS MicroApps: Multi-Chip Module Design Challenges
IMS MicroApps: Analyzing and Understanding the Performance of an LTE System
IMS MicroApp: Causality Considerations for Multi-Gigabit StatEye Analysis
The Josephson Effect: Brian Josephson Debates John Bardeen
IMS MicroApp: Unexpected effects of conductor profile on the propagation constant
IMS MicroApps: Single Chip LNA on 0.25um SOS for SKA Midband Receiver
Bayesian Perception & Decision from Theory to Real World Applications
IMS 2012 Special Sessions: A Retrospective of Field Theory in Microwave Engineering - Magdalena Salazar Palma
IMS 2012 Special Sessions: A Retrospective of Field Theory in Microwave Engineering - David M. Pozar
IMS 2012 Special Sessions: A Retrospective of Field Theory in Microwave Engineering - Constantine A. Balanis
Type-2 Fuzzy Sets and Systems: Some Questions and Answers (edited)
Inspiring Brilliance: The impact of control theory and cybernetics of Maxwell's paper: On governors
Innovative Transmission Line Measurement and Characterization Reduce Time to Repair for Complex Communication Systems: MicroApps 2015 - Keysight Technologies
IMS Organizer: Richard Snyder, President Elect for MTT-S
Big Data Panelist - Joe Weinman: 2016 Technology Time Machine

IEEE-USA E-Books

  • A survey of some results in lattice-valued model theory

    The author surveys some of his published results on the model theory of lattice-valued logic. Among the results surveyed are: the fundamental theorem of ultraproducts, the compactness theorem, the LST theorem, and the omitting types theorem. A proof of the compactness theorem is appended.<<ETX>>

  • The Development of Fuzzy Rough Sets with the Use of Structures and Algebras of Axiomatic Fuzzy Sets

    The notion of a rough set was originally proposed by Pawlak underwent a number of extensions and generalizations. Dubois and Prade (1990) introduced fuzzy rough sets which involve the use of rough sets and fuzzy sets within a single framework. Radzikowska and Kerre (2002) proposed a broad family of fuzzy rough sets, referred to as (phi, t)-fuzzy rough sets which are determined by some implication operator (implicator) phi and a certain t-norm. In order to describe the linguistically represented concepts coming from data available in some information system, the concept of fuzzy rough sets are redefined and further studied in the setting of the axiomatic fuzzy set (AFS) theory. Compared with the (phi, t)-fuzzy rough sets, the advantages of AFS fuzzy rough sets are twofold. They can be directly applied to data analysis present in any information system without resorting to the details concerning the choice of the implication phi, t-norm and a similarity relation S. Furthermore such rough approximations of fuzzy concepts come with a well-defined semantics and therefore offer a sound interpretation. Some examples are included to illustrate the effectiveness of the proposed construct. It is shown that the AFS fuzzy rough sets provide a far higher flexibility and effectiveness in comparison with rough sets and some of their generalizations.

  • Normal forms of fuzzy middle and fuzzy contradictions

    The expressions of "excluded middle" and "crisp contradiction" are reexamined starting with their original linguistic expressions which are first restated in propositional and then predicate forms. It is shown that, in order to generalize the truth tables and hence the normal forms, the membership assignments in predicate expressions must be separated from their truth qualification. In two-valued logic, there is no need to separate them from each other due to reductionist Aristotalean dichotomy. Whereas, in infinite (fuzzy) valued set and logic, the separation of membership assignments from their truth qualification forms the bases of a new reconstruction of the truth tables. The results obtained from these extended truth tables are reducible to their Boolean equivalents under the axioms of Boolean theory. Whereas, in fuzzy set and logic theory, we obtain a richer and more complex interpretations of the "fuzzy middle" and "fuzzy contradiction.".

  • Logical calculi of rough-set granules in problems of approximate synthesis in distributed systems

    A logical calculus of granules is presented. This calculus provides a framework for the approximate synthesis of solutions under uncertainty by distributed systems. The presented calculus is based on rough mereology, a paradigm for approximate reasoning developed by the authors which blends together and relies on the mereology ideas of St. Lesniewski (see L. Polkowski and A. Skowron, Intell. Automation and Soft Comput., vol. 2, no. 2, 1996), rough set theory and fuzzy set theory.

  • Intelligence vague information analysis and decision support system

    With a rapid growth of interest in recent years, vague set has become an effective tool to handle inexact data in the fields of fuzzy information processing. In this paper, I use vague set theory on information analysis and decision support system, set up vague information analysis system, and develop fuzzy gray matter element space decision system into vague gray matter element decision system. Based on vague set theory, I set up an information and task incidence rectangular matrix, and make it as the base of information analysis and decision. The system especially suits for deciding expounding and estimating macroscopic complicated huge system.

  • An automatic classification algorithm for web document in rough set theory and fuzzy sart

    None

  • Heuristic constraints enforcement for training of and knowledge extraction from a fuzzy/neural architecture. I. Foundation

    Using fuzzy/neural architectures to extract heuristic information from systems has received increasing attention. A number of fuzzy/neural architectures and knowledge extraction methods have been proposed. Knowledge extraction from systems where the existing knowledge limited is a difficult task. One of the reasons is that there is no ideal rulebase, which can be used to validate the extracted rules. In most of the cases, using output error measures to validate extracted rules is not sufficient as extracted knowledge may not make heuristic sense, even if the output error may meet the specified criteria. The paper proposes a novel method for enforcing heuristic constraints on membership functions for rule extraction from a fuzzy/neural architecture. The proposed method not only ensures that the final membership functions conform to a priori heuristic knowledge, but also reduces the domain of search of the training and improves convergence speed. Although the method is described on a specific fuzzy/neural architecture, it is applicable to other realizations, including adaptive or static fuzzy inference systems. The foundations of the proposed method are given in Part I. The techniques for implementation and integration into the training are given in Part II, together with applications.

  • Computing with uncertainty

    The role of and interaction between statistical, fuzzy, and neural-like models for certain problems associated with the three main areas of pattern recognition system design are discussed. Some questions concerning fuzzy sets are answered, and the design of fuzzy pattern recognition systems is reviewed. Pattern recognition, statistical pattern recognition and fuzzy pattern recognition systems are described. The use of computational neural-like networks in fuzzy pattern recognition is also discussed.<<ETX>>

  • Fuzzy resolution principle

    The resolution principle based on reduction and absurdum is extended from binary logic to fuzzy logic. The extension is dependent on introducing the concepts of fuzzy contradictory, contradictory degree, fuzzy resolvent, and confidence of resolvent. The concept of fuzzy resolvent is first interpreted, as it is the most important concept and is the basis of fuzzy resolution. Then the fuzzy resolution principle is considered for fuzzy propositional logic and extended to the fuzzy firs-order logic. The completeness of the fuzzy resolution principle is proved. The fuzzy resolution principle has been used as the basis of a powerful fuzzy Prolog system.<<ETX>>

  • On Combining Neuro-Fuzzy Architectures with the Rough Set Theory to Solve Classification Problems with Incomplete Data

    This paper presents a new approach to fuzzy classification in the case of missing features. The rough set theory is incorporated into neuro-fuzzy structures and the rough-neuro-fuzzy classifier is derived. The architecture of the classifier is determined by the modified indexed center of gravity (MICOG) defuzzification method. The structure of the classifier is presented in a general form, which includes both the Mamdani approach and the logical approach-based on the genuine fuzzy implications. A theorem, which allows the determination of the structures of rough-neuro-fuzzy classifiers based on the MICOG defuzzification, is given and proven. Specific rough-neuro-fuzzy structures based on the Larsen rule, the Reichenbach, and the Kleene-Dienes implications are given in details. In the experiments, it is shown that the classifier with the Dubois-Prade fuzzy implication is characterized by the best performance in the case of missing features.



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