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Your search keyword '"Wang, Yingxu"' showing total 11 results
Start Over Author "Wang, Yingxu" Topic denotational mathematics
11 results on '"Wang, Yingxu"'

2. A Knowledge Representation Tool for Autonomous Machine Learning Based on Concept Algebra

Author

Tian, Yousheng, Wang, Yingxu, Hu, Kai, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Gavrilova, Marina L., editor, Tan, C. J. Kenneth, editor, Wang, Yingxu, editor, and Chan, Keith C. C., editor

Published
2009
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3. On Contemporary Denotational Mathematics for Computational Intelligence

Author

Wang, Yingxu, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Gavrilova, Marina L., editor, Tan, C. J. Kenneth, editor, Wang, Yingxu, editor, Yao, Yiyu, editor, and Wang, Guoyin, editor

Published
2008
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4. On Mathematical Laws of Software

Author

Wang, Yingxu, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Gavrilova, Marina L., editor, Tan, C. J. Kenneth, editor, Wang, Yingxu, editor, Yao, Yiyu, editor, and Wang, Guoyin, editor

Published
2008
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5. Perspectives on Denotational Mathematics: New Means of Thought

Author

Wang, Yingxu, Yao, Yiyu, Wang, Guoyin, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Gavrilova, Marina L., editor, Tan, C. J. Kenneth, editor, Wang, Yingxu, editor, Yao, Yiyu, editor, and Wang, Guoyin, editor

Published
2008
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6. Cognitive Informatics and Denotational Mathematical Means for Brain Informatics

Author

Wang, Yingxu, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Yao, Yiyu, editor, Sun, Ron, editor, Poggio, Tomaso, editor, Liu, Jiming, editor, Zhong, Ning, editor, and Huang, Jimmy, editor

Published
2010
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8. Abstract intelligence and cognitive robots

Author

Wang Yingxu

Subjects
cognitive informatics, cognitive computing, abstract intelligence, cognitive robots, computational intelligence, denotational mathematics, cognitive models, cognitive behaviors, behavioral modeling, Technology
Abstract

Abstract intelligence is the human enquiry of both natural and artificial intelligence at the neural, cognitive, functional, and logical levels reductively from the bottom up. According to the abstract intelligence theory, a cognitive robot is an autonomous robot that is capable of thought, perception, and learning based on the three-level computational intelligence known as the imperative, autonomic, and cognitive intelligence. This paper presents the theoretical foundations of cognitive robots based on the latest advances in abstract intelligence, cognitive informatics, and denotational mathematics. A formal model of intelligence known as the Generic Abstract Intelligence Mode (GAIM) is developed, which provides a foundation to explain the mechanisms of advanced natural intelligence such as thinking, learning, and inference. A set of denotational mathematics is introduced for rigorously modeling and manipulating the behaviors of cognitive robots. A case study on applications of a denotational mathematics, visual semantic algebra (VSA), is presented in architectural and behavioral modeling of cognitive robots based on the theory of abstract intelligence.

Published
2010
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9. On the Cognitive and Theoretical Foundations of Big Data Science and Engineering.

Author

Wang, Yingxu

Subjects
*BIG data, *COGNITIVE analysis, *ENGINEERING, *DATA, *DATA mining
Abstract

Big data play an indispensable role not only in the cognitive mechanisms of human sensation, quantification, qualification, estimation, memory, and reasoning, but also in a wide range of engineering applications. A basic study on the theoretical foundations of big data science is presented with a coherent set of general principles and analytic methodologies for big data systems. Cognitive foundations of big data are explored in order to formally explain the origination and nature of big data. A set of mathematical models of big data are created that rigorously elicit the general essences and patterns of big data across pervasive domains in sciences, engineering, and societies. A significant finding towards big data science is that big data systems in nature are a recursive -dimensional-typed hyperstructure (RNTHS) rather than pure numbers. The fundamental topological property of big data reveals a set of denotational mathematical solutions for dealing with inherited complexities and unprecedented challenges in big data engineering. [ABSTRACT FROM AUTHOR]

Published
2017
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10. A formal measurement of the cognitive complexity of texts in cognitive linguistics.

Author

Wang, Yingxu, Berwick, Robert C., Luo, Xiangfeng, and Lei, Jingsheng

Abstract

The cognitive complexity of texts in natural languages is a fundamental measure of the properties of syntax and semantics in textual comprehension, processing, and search. This paper presents a formal metrics of text comprehension complexity in cognitive linguistics. Both objective and subjective aspects of text comprehension and their complexity are formally modeled. A formal language model is established that characterizes the discourse of natural languages. The mathematical models of cognitive complexity of texts and their comprehension are rigorously described. On the basis of the cognitive and mathematical models of cognitive linguistics, the measurement of cognitive complexity of texts is quantitatively established and tested by a set of case studies. A wide range of applications of the measurement of textual complexity are identified in cognitive linguistics and contemporary web technologies such as search engines, online document retrieval, natural language processing, cognitive linguistics, cognitive computing, cognitive machine learning, and computing with words. [ABSTRACT FROM PUBLISHER]

Published
2012
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11. On abstract intelligence and brain informatics: Mapping the cognitive functions onto the neural architectures.

Author

Wang, Yingxu

Abstract

A fundamental challenge for almost all scientific disciplines is to explain how natural intelligence is generated by physiological organs and what the logical model of the brain is beyond its neural architectures. According to cognitive informatics and abstract intelligence, the exploration of the brain is a complicated recursive problem where contemporary denotational mathematics is needed to efficiently deal with it. Cognitive psychology and medical science are used to explain that the brain works in a certain way based on empirical observations of corresponding activities in usually overlapped brain areas. However, the lack of precise models and rigorous causality in brain studies has dissatisfied the formal expectations of researchers in computational science and mathematics, because a computer, the logical counterpart of the brain, might not be explained in such a vigor and empirical approach without the support of a formal model and a rigorous means. [ABSTRACT FROM PUBLISHER]

Published
2012
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