Conferences related to Fuzzy Logic

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2014 IEEE 23rd International Symposium on Industrial Electronics (ISIE)

Control Systems & ApplicationsPower ElectronicsSignal Processing & Computational IntelligenceRobotics & MechatronicsSensors, Actuators & System IntegrationElectrical Machines & DrivesFactory Automation & Industrial InformaticsEmerging Technologies

  • 2012 IEEE 21st International Symposium on Industrial Electronics (ISIE)

    IEEE-ISIE is the largest summer conference of the IEEE Industrial Electronics Society, which is an international forum for presentation and discussion of the state of art in Industrial Electronics and related areas.

  • 2011 IEEE 20th International Symposium on Industrial Electronics (ISIE)

    Industrial electronics, power electronics, power converters, electrical machines and drives, signal processing, computational intelligence, mechatronics, robotics, telecommuniction, power systems, renewable energy, factory automation, industrial informatics.

  • 2010 IEEE International Symposium on Industrial Electronics (ISIE 2010)

    Application of electronics and electrical sciences for the enhancement of industrial and manufacturing processes. Latest developments in intelligent and computer control systems, robotics, factory communications and automation, flexible manufacturing, data acquisition and signal processing, vision systems, and power electronics.

  • 2009 IEEE International Symposium on Industrial Electronics (ISIE 2009)

    The purpose of the IEEE international conference is to provide a forum for presentation and discussion of the state-of art of Industrial Electronics and related areas.


2014 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)

CIBCB 2014 will bring together top researchers, practitioners, and students from around the world to discuss the latest advances in the field of Computational Intelligence and its application to real world problems in biology, bioinformatics, computational biology, chemical informatics, bioengineering, and related fields. Computational Intelligence approaches include artificial neural networks and learning systems, fuzzy logic, evolutionary algorithms, hybrid algorithms, and other emerging techniques.

  • 2013 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)

    The CIBCB 2013 symposium will bring together top researchers, practitioners, and students from around the world to discuss the latest advances in the field of Computational Intelligence and its application to real-world problems in theoretical and applied biology, bioinformatics, computational biology, chemical informatics, bioengineering and related fields. Computational Intelligence (CI) approaches include artificial neural networks, fuzzy logic, evolutionary computation, hybrid approaches and other emerging techniques including but not limited to ant colony optimization, particle swarm optimization, and support vector machines.The use of computational intelligence must play a substantial role in submitted papers.

  • 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)

    The scope of this symposium covers the application of computational Intelligence techniques, such as evolutionary computation, neural networks and fuzzy systemsand, to real world problems in biology, including bioinformatics, computational biology, chemical informatics, bioengineering and related fields.

  • 2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)

    This symposium will bring together top researchers, practitioners, and students from around the world to discuss the latest advances in the field of Computational Intelligence and its application to real world problems in biology, bioinformatics, computational biology, chemical informatics, bioengineering and related fields.


2014 IEEE International Conference on Systems, Man and Cybernetics - SMC

SMC2014 targets advances in Systems Science and Engineering, Human-Machine Systems, and Cybernetics involving state-of-art technologies interacting with humans to provide an enriching experience and thereby improving the quality of lives including theories, methodologies, and emerging applications.

  • 2013 IEEE International Conference on Systems, Man and Cybernetics - SMC

    SMC 2013 targets advances in Systems Science and Engineering Human-machine Systems and Cybernetics involving state-of-the-art technologies interacting with humans to provide an enriching experience and thereby improving the quality of lives including theories, methodologies and emerging applications.

  • 2012 IEEE International Conference on Systems, Man and Cybernetics - SMC

    Theory, research and technology advances including applications in all aspects of systems science and engineering, human machine systems, and emerging cybernetics.

  • 2011 IEEE International Conference on Systems, Man and Cybernetics - SMC

    Theory, research, and technology advances including applications in all aspects of systems science and engineering, human machine systems, and emerging cybernetics.

  • 2010 IEEE International Conference on Systems, Man and Cybernetics - SMC

    The 2010 IEEE International Conference on Systems, Man, and Cybernetics (SMC2010) provides an international forum that brings together those actively involved in areas of interest to the IEEE Systems, Man, and Cybernetics Society, to report on up-to-the-minute innovations and developments, to summarize the state-of-the-art, and to exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics.

  • 2009 IEEE International Conference on Systems, Man and Cybernetics - SMC

    The 2009 IEEE International Conference on Systems, Man, and Cybernetics (SMC2009) provides an international forum that brings together those actively involved in areas of interest to the IEEE Systems, Man, and Cybernetics Society, to report on up-to-the-minute innovations and developments, to summarize the state-of-the-art, and to exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics.


IECON 2014 - 40th Annual Conference of the IEEE Industrial Electronics Society

Applications of power electronics, artificial intelligence, robotics, and nanotechnology in electrification of automotive, military, biomedical, and utility industries.

  • IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society

    Industrial and manufacturing theory and applications of electronics, controls, communications, instrumentation and computational intelligence.

  • IECON 2012 - 38th Annual Conference of IEEE Industrial Electronics

    The conference will be focusing on industrial and manufacturing theory and applications of electronics,power, sustainable development, controls, communications, instrumentation and computational intelligence.

  • IECON 2011 - 37th Annual Conference of IEEE Industrial Electronics

    industrial applications of electronics, control, robotics, signal processing, computational and artificial intelligence, sensors and actuators, instrumentation electronics, computer networks, internet and multimedia technologies.

  • IECON 2010 - 36th Annual Conference of IEEE Industrial Electronics

    IECON is an international conference on industrial applications of electronics, control, robotics, signal processing, computational and artificial intelligence, sensors and actuators, instrumentation electronics, computer networks, internet and multimedia technologies. The objectives of the conference are to provide high quality research and professional interactions for the advancement of science, technology, and fellowship.

  • IECON 2009 - 35th Annual Conference of IEEE Industrial Electronics

    Applications of electronics, instrumentation, control and computational intelligence to industrial and manufacturing systems and process. Major themes include power electronics, drives, sensors, actuators, signal processing, motion control, robotics, mechatronics, factory and building automation, and informatics. Emerging technologies and applications such as renewable energy, electronics reuse, and education.


2013 12th IEEE International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

Cognitive Informatics (CI) is a cutting-edge and multidisciplinary research field that tackles the fundamental problems shared by modern informatics, computing, AI, cybernetics, computational intelligence, cognitive science, intelligence science, neuropsychology, brain science, systems science, software engineering, knowledge engineering, cognitive robots, scientific philosophy, cognitive linguistics, life sciences, and cognitive computing.

  • 2012 11th IEEE International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

    Cognitive informatics and Cognitive Computing are a transdisciplinary enquiry on the internal information processing mechanisms and processes of the brain and their engineering applications in cognitive computers, computational intelligence, cognitive robots, cognitive systems, and in the AI, IT, and software industries. The 11th IEEE Int l Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC 12) focuses on the theme of e-Brain and Cognitive Computers.

  • 2011 10th IEEE International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

    Cognitive Informatics and Cognitive Computing are a transdisciplinary enquiry on the internal information processing mechanisms and processes of the brain and their engineering applications in cognitive computers, computational intelligence, cognitive robots, cognitive systems, and in the AI, IT, and software industries. The 10th IEEE Int l Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC 11) focuses on the theme of Cognitive Computers and the e-Brain.

  • 2010 9th IEEE International Conference on Cognitive Informatics (ICCI)

    Cognitive Informatics (CI) is a cutting-edge and transdisciplinary research area that tackles the fundamental problems shared by modern informatics, computing, AI, cybernetics, computational intelligence, cognitive science, neuropsychology, medical science, systems science, software engineering, telecommunications, knowledge engineering, philosophy, linguistics, economics, management science, and life sciences.

  • 2009 8th IEEE International Conference on Cognitive Informatics (ICCI)

    The 8th IEEE International Conference on Cognitive Informatics (ICCI 09) focuses on the theme of Cognitive Computing and Semantic Mining. The objectives of ICCI'09 are to draw attention of researchers, practitioners, and graduate students to the investigation of cognitive mechanisms and processes of human information processing, and to stimulate the international effort on cognitive informatics research and engineering applications.


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Periodicals related to Fuzzy Logic

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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 ...


Computational Biology and Bioinformatics, IEEE/ACM Transactions on

Specific topics of interest include, but are not limited to, sequence analysis, comparison and alignment methods; motif, gene and signal recognition; molecular evolution; phylogenetics and phylogenomics; determination or prediction of the structure of RNA and Protein in two and three dimensions; DNA twisting and folding; gene expression and gene regulatory networks; deduction of metabolic pathways; micro-array design and analysis; proteomics; ...


Computational Intelligence Magazine, IEEE

The IEEE Computational Intelligence Magazine (CIM) publishes peer-reviewed articles that present emerging novel discoveries, important insights, or tutorial surveys in all areas of computational intelligence design and applications.


Evolutionary Computation, IEEE Transactions on

Papers on application, design, and theory of evolutionary computation, with emphasis given to engineering systems and scientific applications. Evolutionary optimization, machine learning, intelligent systems design, image processing and machine vision, pattern recognition, evolutionary neurocomputing, evolutionary fuzzy systems, applications in biomedicine and biochemistry, robotics and control, mathematical modelling, civil, chemical, aeronautical, and industrial engineering applications.


Fuzzy Systems, IEEE Transactions on

Theory and application of fuzzy systems with emphasis on engineering systems and scientific applications. (6) (IEEE Guide for Authors) Representative applications areas include:fuzzy estimation, prediction and control; approximate reasoning; intelligent systems design; machine learning; image processing and machine vision;pattern recognition, fuzzy neurocomputing; electronic and photonic implementation; medical computing applications; robotics and motion control; constraint propagation and optimization; civil, chemical and ...


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Xplore Articles related to Fuzzy Logic

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An optimized fuzzy logic-based control of static VAr compensator in a power system with wind generation

M. F. Kandlawala; T. T. Nguyen 2009 Transmission & Distribution Conference & Exposition: Asia and Pacific, 2009

An optimal controller for a shunt-connected static VAr compensator (SVC) has been developed for improving the dynamic performance of a power system with wind-turbine generators. The fuzzy-logic control complements the voltage control function, and provides damping in the system. A constrained- optimization design procedure for determining the optimal values of the linguistic variables for forming the crisp output of the ...


KUPS: Knowledge-based Ubiquitous and Persistent Sensor networks for Threat Assessment

Qilian Liang MILCOM 2006 - 2006 IEEE Military Communications conference, 2006

In this paper, we propose a knowledge-based ubiquitous and persistent sensor networks (KUPS) for threat assessment, of which "sensor" is a broad characterization concept. It means diverse data or information from ubiquitous and persistent sensor sources such as organic sensors and human intelligence sensors. Our KUPS for threat assessment consists of two major steps: threat detection using fuzzy logic systems ...


Real-time channel evaluation combined with decoding and synchronisation

F. Arani; P. Coulton; B. Honary Global Telecommunications Conference, 1995. GLOBECOM '95., IEEE, 1995

This paper describes a novel digital receiver which uses soft maximum likelihood trellis decoding (SMLD) of the received signal to provide symbol timing and channel estimation from the decoder metrics. Results of simulation of the system over an (AWGN) channel are presented


Fuzzy Eco-Design Product Development by Using Quality Function Deployment

Tsai-Chi Kuo; Wu Hsin-Hung 2005 4th International Symposium on Environmentally Conscious Design and Inverse Manufacturing, 2005

Recently, resource optimization (energy and material) and environmental issues in life-cycle context are taken very seriously by both the general public and government agencies. Also, some governments have set up official eco-labeling schemes, which are used to inform consumers of Eco (ecology and economic) design products. In the past, several environmental impact analyses and evaluation tools are significantly developed to ...


Modern methodology of the safety risk assessment in Mobile Communication Networks

B. Yu. Shomaksudov; R. H. Djurayev 2008 4th IEEE/IFIP International Conference on Central Asia on Internet, 2008

In this work the methods of safety risk assessments in Mobile Communication Networks are considered. Also the modern risk assessment methods and the most important fuzzy logic mechanism are shown.


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Educational Resources on Fuzzy Logic

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eLearning

An optimized fuzzy logic-based control of static VAr compensator in a power system with wind generation

M. F. Kandlawala; T. T. Nguyen 2009 Transmission & Distribution Conference & Exposition: Asia and Pacific, 2009

An optimal controller for a shunt-connected static VAr compensator (SVC) has been developed for improving the dynamic performance of a power system with wind-turbine generators. The fuzzy-logic control complements the voltage control function, and provides damping in the system. A constrained- optimization design procedure for determining the optimal values of the linguistic variables for forming the crisp output of the ...


KUPS: Knowledge-based Ubiquitous and Persistent Sensor networks for Threat Assessment

Qilian Liang MILCOM 2006 - 2006 IEEE Military Communications conference, 2006

In this paper, we propose a knowledge-based ubiquitous and persistent sensor networks (KUPS) for threat assessment, of which "sensor" is a broad characterization concept. It means diverse data or information from ubiquitous and persistent sensor sources such as organic sensors and human intelligence sensors. Our KUPS for threat assessment consists of two major steps: threat detection using fuzzy logic systems ...


Real-time channel evaluation combined with decoding and synchronisation

F. Arani; P. Coulton; B. Honary Global Telecommunications Conference, 1995. GLOBECOM '95., IEEE, 1995

This paper describes a novel digital receiver which uses soft maximum likelihood trellis decoding (SMLD) of the received signal to provide symbol timing and channel estimation from the decoder metrics. Results of simulation of the system over an (AWGN) channel are presented


Fuzzy Eco-Design Product Development by Using Quality Function Deployment

Tsai-Chi Kuo; Wu Hsin-Hung 2005 4th International Symposium on Environmentally Conscious Design and Inverse Manufacturing, 2005

Recently, resource optimization (energy and material) and environmental issues in life-cycle context are taken very seriously by both the general public and government agencies. Also, some governments have set up official eco-labeling schemes, which are used to inform consumers of Eco (ecology and economic) design products. In the past, several environmental impact analyses and evaluation tools are significantly developed to ...


Modern methodology of the safety risk assessment in Mobile Communication Networks

B. Yu. Shomaksudov; R. H. Djurayev 2008 4th IEEE/IFIP International Conference on Central Asia on Internet, 2008

In this work the methods of safety risk assessments in Mobile Communication Networks are considered. Also the modern risk assessment methods and the most important fuzzy logic mechanism are shown.


More eLearning Resources

IEEE.tv Videos

Hamid R Tizhoosh - Fuzzy Image Processing
The Sorites Paradox: Introduction to Fuzzy Logic
The Hertzsprung-Russell Diagram: Introduction to Fuzzy Logic
A perspective shift from Fuzzy logic to Neutrosophic Logic - Swati Aggarwal
Single Frame Super Resolution: Fuzzy Rule-Based and Gaussian Mixture Regression Approaches
Norbert Wiener in the 21st Century Conference Concept
Dynamic Logic Example
Evolving Fuzzy Systems: A Granular Computing Design Framework
Type-2 Fuzzy Sets and Systems: Some Questions and Answers (edited)
Towards Logic-in-Memory circuits using 3D-integrated Nanomagnetic Logic - Fabrizio Riente: 2016 International Conference on Rebooting Computing
Computing with Words: Towards an Ultimately Human Centric Computing Paradigm
Valerie Cross - Similarity from Fuzzy Sets to Semantic Similarity and Their Role on the Semantic Web
Fuzzy and Soft Methods for Multi-Criteria Decision Making - Ronald R Yager - WCCI 2016
Sparse Fuzzy Modeling - Nikhil R Pal - WCCI 2016
FinSAL: A Novel FinFET Based Secure Adiabatic Logic for Energy-Efficient and DPA Resistant IoT Devices - Himanshu Thapliyal: 2016 International Conference on Rebooting Computing
2013 IEEE Robert N. Noyce Medal
Provably-Correct Robot Control with LTLMoP, OMPL and ROS
Erasing Logic-Memory Boundaries in Superconductor Electronics - Vasili Semenov: 2016 International Conference on Rebooting Computing
Fuzzy Sets and Social Research - Charles C. Ragin - WCCI 2016
Low-energy High-performance Computing based on Superconducting Technology

IEEE-USA E-Books

  • Intelligent Control: An Overview of Techniques

    In many established fields, the label ?>intelligent?> heralds new developments that take issue with some traditional assumptions in research. In the case of intelligent control, an explicit attempt is made to draw inspiration from nature, biology, and artificial intelligence, and a methodology is promoted that is more accepting of heuristics and approximationsï¿¿-ï¿¿and is less insistent on theoretical rigor and completenessï¿¿-ï¿¿than is the case with most research in control science. Beyond such general and abstract features, succinct characterizations of intelligent control are difficult. Extensional treatments are an easier matter. Fuzzy logic, neural networks, genetic algorithms, and expert systems constitute the main areas of the field, with applications to nonlinear identification, nonlinear control design, controller tuning, system optimization, and encapsulation of human operator expertise. Intelligent control is thus no narrow specialization; it furnishes a diverse body of techniques that potentially addresses most of the technical challenges in control systems. It is also important to emphasize that intelligent control is by no means methodologically opposed to theory and analysis. Chapter 6 of this book, for example, discusses some theoretical results for neural networks and fuzzy models as nonlinear approximators Introductory tutorials to the key topics in intelligent control are provided in this chapter. No prior background in these topics is assumed. Examples from ship maneuvering, robotics, and automotive diagnostics help motivate the discussion. (Other chapters in this volume, notably Chapter 16, also outline applications of intelligent control.) General observations on autonomy and adaptationï¿ ¿-ï¿¿two characteristics that are often considered essential to any definition of intelligenceï¿¿-ï¿¿are also included.

  • Neural, Fuzzy, and ApproximationBased Control

    The assumption of linearity must be given due credit for the tremendous practical impact that control systems have had over the last several decades. However, as the original challenges have been encountered and overcome, and as the control and automation of complex, large-scale problems are being sought, effective methods for dealing with nonlinear systems have become essential. One key component of nonlinear controls technology is representations or models of nonlinear systems that are derived from operational data. Such models, referred to as _approximators_, are the focus of this chapter. Specific attention is paid to neural networks and fuzzy models. These topics are discussed within a general formulation that emphasizes their close relationships with other approximator structures. In this chapter, several associated properties are noted and defined, including universal approximation, linear and nonlinear parameterizations, generalization, and approximator transparency. Compared to most other chapters in this volume, this one is relatively theoretical. Less formal introductions to neural networks and fuzzy logic can be found in Chapter 5; some applications are discussed therein and in Chapter 16. An important problem in approximator development is the estimation of the approximator parameters. This chapter discusses some algorithms - specifically steepest descent, least-squares, and Lyapunov-based algorithms - that can be used for this purpose. Some degree of modeling error is inescapable, and this realization has motivated the development of extensions to parameter estimation algorithms. Readers interested in additional nonlinear control methods may also find Chapter 8 of interest, which provides a readable technical introduction to a popular nonlinear control design technique, slidingmode control.

  • Prospects for Low???Energy Device Technology and Applications

    This chapter considers three types of integrated circuits (ICs): ultra???high???speed ICs (artificial intelligence or AI), ordinary high???speed ICs (motor control) and low???power ICs (data acquisition from various sensors). High???level AI architecture needs hardware with a self???control function based on a highspeed CPU and huge???scale memory. DC???DC converters are frequently used for robot motor control. Analog???to???digital converters are generally used to implement sensor functions and require more devices than DC???DC converters. It is known that the human brain does not offer high???speed signal processing, but its comprehensive decision function (so???called ???intelligence???) reveals very high performance with low???energy dissipation for its physical volume. Although scientists and engineers are still investigating how the human brain works, studies of circuits to simulate some brain functions have been performed widely, as well as research on advanced control technologies and fuzzy logic circuits.

  • References

    A comprehensive introduction to the exploding field of data mining We are surrounded by data, numerical and otherwise, which must be analyzed and processed to convert it into information that informs, instructs, answers, or otherwise aids understanding and decision-making. Due to the ever-increasing complexity and size of today's data sets, a new term, data mining, was created to describe the indirect, automatic data analysis techniques that utilize more complex and sophisticated tools than those which analysts used in the past to do mere data analysis. Data Mining: Concepts, Models, Methods, and Algorithms discusses data mining principles and then describes representative state-of- the-art methods and algorithms originating from different disciplines such as statistics, machine learning, neural networks, fuzzy logic, and evolutionary computation. Detailed algorithms are provided with necessary explanations and illustrative examples. This text offers guidance: how and when to use a particular software tool (with their companion data sets) from among the hundreds offered when faced with a data set to mine. This allows analysts to create and perform their own data mining experiments using their knowledge of the methodologies and techniques provided. This book emphasizes the selection of appropriate methodologies and data analysis software, as well as parameter tuning. These critically important, qualitative decisions can only be made with the deeper understanding of parameter meaning and its role in the technique that is offered here. Data mining is an exploding field and this book offers much-needed guidance to selecting among the numerous analysis programs that are available.

  • Cue Integration for Manipulation

    Robustness of vision is a notorious problem in vision, and it is one of the major bottlenecks for industrial exploitation of vision. One hypothesis is that fusion of multiple natural features facilitates robust detection and tracking of objects in scenes of realistic complexity. Use of dedicated models of objects of interest is another approach to the robustness problem. To provide some generality the use of natural features for estimation of the end- effector position is pursued in this work. The research investigates two different approaches to cues integration, one based on voting and another based on fuzzy logic. The two approaches have been tested in association with scenes of varying complexity. Experimental results clearly demonstrate that fusion of cues results in added robustness and increased estimation performance. The robustness is in particular evident for scenes with multiple moving objects and partial occlusion of the object of the interest.

  • Armchair Missions to Mars

    This chapter contains sections titled: Modeling a Team of Astronauts, Modeling the Mission Process, Using Case-Based Reasoning, The Case-Retrieval Mechanism, The Adaptation Algorithm, Rules and Fuzzy Logic, Conclusions and Future Work

  • Basic Fuzzy Set Theory

    Fuzzy set theory and fuzzy logic provide a different way to view the problem of modeling uncertainty and offer a wide range of computational tools to aid decision making. The mathematical basis for formal fuzzy logic can be found in infinite-valued logics, first studied by the Polish logician Jan Lukasiewicz in the 1920s. While the big economic impact of fuzzy set theory and fuzzy logic centers on control, particularly in consumer electronics, there has been, and continues to be, much research and application of these technologies in pattern recognition, information fusion, data mining, and automated decision making. All fuzzy set theory is based on the concept of a membership function. In many cases, the membership functions take on specific functional forms such as triangular, trapezoidal, S-functions, pi-functions, sigmoids, and even Gaussians for convenience in representation and computation. A neural network also acts as a membership function.

  • Index

    Featuring current contributions by experts in signal processing and biomedical engineering, this book introduces the concepts, recent advances, and implementations of nonlinear dynamic analysis methods. Together with Volume I in this series, this book provides comprehensive coverage of nonlinear signal and image processing techniques. Nonlinear Biomedical Signal Processing: Volume II combines analytical and biological expertise in the original mathematical simulation and modeling of physiological systems. Detailed discussions of the analysis of steady-state and dynamic systems, discrete-time system theory, and discrete modeling of continuous-time systems are provided. Biomedical examples include the analysis of the respiratory control system, the dynamics of cardiac muscle and the cardiorespiratory function, and neural firing patterns in auditory and vision systems. Examples include relevant MATLAB® and Pascal programs. Topics covered include: Nonlinear dynamics Behavior and estimation Modeling of biomedical signals and systems Heart rate variability measures, models, and signal assessments Origin of chaos in cardiovascular and gastric myoelectrical activity Measurement of spatio-temporal dynamics of human epileptic seizures A valuable reference book for medical researchers, medical faculty, and advanced graduate students, it is also essential reading for practicing biomedical engineers. Nonlinear Biomedical Signal Processing, Volume II is an excellent companion to Dr. Akay's Nonlinear Biomedical Signal Processing, Volume I: Fuzzy Logic, Neural Networks, and New Algorithms.

  • No title

    <p>Information retrieval used to mean looking through thousands of strings of texts to find words or symbols that matched a user's query. Today, there are many models that help index and search more effectively so retrieval takes a lot less time. Information retrieval (IR) is often seen as a subfield of computer science and shares some modeling, applications, storage applications and techniques, as do other disciplines like artificial intelligence, database management, and parallel computing. This book introduces the topic of IR and how it differs from other computer science disciplines. A discussion of the history of modern IR is briefly presented, and the notation of IR as used in this book is defined. The complex notation of relevance is discussed. Some applications of IR is noted as well since IR has many practical uses today. Using information retrieval with fuzzy logic to search for software terms can help find software components and ultimately help increase the reuse f software. This is just one practical application of IR that is covered in this book.</p> <p>Some of the classical models of IR is presented as a contrast to extending the Boolean model. This includes a brief mention of the source of weights for the various models. In a typical retrieval environment, answers are either yes or no, i.e., on or off. On the other hand, fuzzy logic can bring in a "degree of" match, vs. a crisp, i.e., strict match. This, too, is looked at and explored in much detail, showing how it can be applied to information retrieval. Fuzzy logic is often times considered a soft computing application and this book explores how IR with fuzzy logic and its membership functions as weights can help indexing, querying, and matching. Since fuzzy set theory and logic is explored in IR systems, the explanation of where the fuzz is ensues.</p> <p>The concept of relevance feedback, including pseudorelevance feedback is explored for the various mod ls of IR. For the extended Boolean model, the use of genetic algorithms for relevance feedback is delved into.</p> <p>The concept of query expansion is explored using rough set theory. Various term relationships is modeled and presented, and the model extended for fuzzy retrieval. An example using the UMLS terms is also presented. The model is also extended for term relationships beyond synonyms.</p> <p>Finally, this book looks at clustering, both crisp and fuzzy, to see how that can improve retrieval performance. An example is presented to illustrate the concepts.</p>

  • Introduction to Pattern Recognition and Data Mining

    This introductory chapter of the book provides a brief review of pattern recognition, data mining, and application of pattern recognition algorithms in data mining problems. The objective of the book is to provide some results of investigations, both theoretical and experimental, addressing the relevance of rough-fuzzy approaches to pattern recognition with real-life applications. The chapter first briefly presents a description of the basic concept, features, and techniques of pattern recognition. It then elaborates the data mining aspect, discussing its components, tasks involved, approaches, and application areas. The chapter next introduces the pattern recognition perspective of data mining and mentions related research challenges. It describes the role of soft computing in pattern recognition and data mining. Finally, the chapter discusses the scope and organization of the book. fuzzy logic



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