Discoveries and Breakthroughs in Cognitive Informatics and Natural Intelligence

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Wang, Yingxu
IGI Global, Nov 30, 2009 - Education - 606 pages
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Cognitive informatics is a multidisciplinary field that acts as the bridge between natural science and information science. Specifically, it investigates the potential applications of information processing and natural intelligence to science and engineering disciplines.

This collection, entitled Discoveries and Breakthroughs in Cognitive Informatics and Natural Intelligence, provides emerging research topics in cognitive informatics research with a focus on such topics as reducing cognitive overload, real-time process algebra, and neural networks for iris recognition, emotion recognition in speech, and the classification of musical chords.


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A Computational CognitiveModel of the Brain
A Cognitive Approach to theMechanism of Intelligence1
Reducing Cognitive Overloadby MetaLearning AssistedAlgorithm Selection
Analyzing Learning Methodsin a Functional Environment
Nature of Learning and Learning of Nature
On Cognitive Properties ofHuman Factors and ErrorModels in Engineering andSocialization
UserCentered InteractiveData Mining
A Denotational Mathematical Structure forKnowledge and Software Modeling
Unifying Rough Set Analysisand Formal Concept AnalysisBased on a Logic Approachto Granular Computing
On Foundations andApplications of the Paradigm ofGranular Rough Computing
Robust IndependentComponent Analysis forCognitive Informatics
A Relative FractalDimension Spectrum for aPerceptual Complexity Measure
3D Object Classification Basedon Volumetric Parts
Modeling Underwater Structures
A Novel Plausible Model forVisual Perception
An Efficient and AutomaticIris Recognition SystemUsing ICM Neural Network

A Denotational Mathematical Structure forAbstract System Modeling
A Denotational Mathematics forManipulating Intelligent andComputational Behaviors
A Denotational Semantics ofRealTime Process AlgebraRTPA
An Operational Semantics ofRealTime Process AlgebraRTPA
Formal Modeling andSpecification of Design PatternsUsing RTPA
Deductive Semantics of RTPA
On the BigR Notation forDescribing Iterative andRecursive Behaviors
Formal RTPA Models for a Setof MetaCognitive Processes ofthe Brain
Neural Networks for LanguageIndependent EmotionRecognition in Speech
An Analysis of InternalRepresentations for TwoArtificial Neural Networksthat Classify Musical Chords
Foundation and Classificationof Nonconventional NeuralUnits and Paradigm ofNonsynaptic Neural Interaction
A Randomize Test Follow Up Study
Compilation of References
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About the author (2009)

Yingxu Wang is professor of cognitive informatics and software science, President of International Institute of Cognitive Informatics and Cognitive Computing (ICIC), Director of Laboratory for Cognitive Informatics and Cognitive Computing, and Director of Laboratory for Denotational Mathematics and Software Science at the University of Calgary. He is a Fellow of WIF (UK), Fellow of ICIC, a P.Eng of Canada, a Senior Member of IEEE and ACM. He received a PhD in Software Engineering from the Nottingham Trent University, UK, and a BSc in Electrical Engineering from Shanghai Tiedao University. He has industrial experience since 1972 and has been a full professor since 1994. He was a visiting professor on sabbatical leaves in the Computing Laboratory at Oxford University in 1995, Dept. of Computer Science at Stanford University in 2008, the Berkeley Initiative in Soft Computing (BISC) Lab at University of California, Berkeley in 2008, and MIT (2012), respectively. He is the founder and steering committee chair of the annual IEEE International Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC). He is founding Editor-in-Chief of International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), founding Editor-in-Chief of International Journal of Software Science and Computational Intelligence (IJSSCI), Associate Editor of IEEE Trans on System, Man, and Cybernetics (Part A), and associate Editor-in-Chief of Journal of Advanced Mathematics and Applications.

Dr. Wang is the initiator of a few cutting-edge research fields or subject areas such as Cognitive Informatics (CI, the theoretical framework of CI, neuroinformatics, the logical model of the brain (LMB), the layered reference model of the brain (LRMB), the cognitive model of brain informatics (CMBI), the mathematical model of consciousness, and the cognitive learning engine); Abstract Intelligence ( I); Cognitive Computing (such as cognitive computers, cognitive robots, cognitive agents, and cognitive Internet); Denotational Mathematics (i.e., concept algebra, inference algebra, semantic algebra, real-time process algebra, system algebra, granular algebra, and visual semantic algebra); Software Science (on unified mathematical models and laws of software, cognitive complexity of software, and automatic code generators, the coordinative work organization theory, and built-in tests (BITs)); basic studies in Cognitive Linguistics (such as the cognitive linguistic framework, the deductive semantics of languages, deductive grammar of English, and the cognitive complexity of online text comprehension). He has published over 130 peer reviewed journal papers, 220+ peer reviewed conference papers, and 25 books in cognitive informatics, cognitive computing, software science, denotational mathematics, and computational intelligence. He is the recipient of dozens international awards on academic leadership, outstanding contributions, research achievement, best papers, and teaching in the last three decades. [Editor]

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