DocumentCode :
443960
Title :
Quotient space based multi-granular computing
Author :
Zhang, Ling ; Zhang, Bo
Author_Institution :
Artificial Intelligence Inst., Anhui Univ., Hefei, China
Volume :
1
fYear :
2005
fDate :
25-27 July 2005
Abstract :
Summary form only given. One of the basic characteristics in human problem solving is the ability to conceptualize the world at different granularities and translate from one abstraction level to the others easily, i.e., the ability of multi-granular computing. The proposed quotient space theory is intended to provide a multi-granular computing model. In this paper, we address the following four problems. The traditional single-granular computing methodology usually confronts with high computational complexity when dealing with complex problems. The main aim of multi-granular computing is intended to reduce the computational complexity. By using the quotient space model, we show in what conditions the multi-granular computing could reduce the computational complexity. Second, based on the quotient space model, the characteristics of the top-down hierarchical problem solving are discussed. Third, the well-known multi-resolution signal analysis is managed under the framework of the quotient space model. And we show the close relationship between the quotient space based multi-resolution model and the second-generation wavelet transforms. This relationship may provide a new idea for signal analysis. Finally, a quotient space based hierarchical machine-learning model is discussed. And a new hierarchical constructive learning algorithm is presented.
Keywords :
computational complexity; learning (artificial intelligence); problem solving; signal resolution; wavelet transforms; hierarchical constructive learning algorithm; hierarchical machine-learning model; human problem solving; multigranular computing; multiresolution signal analysis; quotient space theory; second-generation wavelet transforms; top-down hierarchical problem solving; Artificial intelligence; Artificial neural networks; Books; Computational complexity; Computer science; Humans; Multiresolution analysis; Problem-solving; Signal analysis; Space technology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Granular Computing, 2005 IEEE International Conference on
Print_ISBN :
0-7803-9017-2
Type :
conf
DOI :
10.1109/GRC.2005.1547242
Filename :
1547242
Link To Document :
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