this paper first defines the elementary granulation and the granulation, and other concepts, then we could convert decision tables to granular graph, and make visual presentation of them. some relevant knowledge of gr...
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ISBN:
(纸本)9780819490261
this paper first defines the elementary granulation and the granulation, and other concepts, then we could convert decision tables to granular graph, and make visual presentation of them. some relevant knowledge of graph theory is applied to granular graph and its computing. In the paper it is shown that it is feasible and effective that granular graph is applied in describing data reduction. the method has the characteristic of simple and visual form and so on. Compared with other analysis methods, its time complexity is decreased to O(n).
Based on the theory of adaptive modulation, the compressed format is introduced in voice and data transmission, and a novel adaptive dynamic capability allocation algorithm is presented. In the given transmission syst...
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ISBN:
(纸本)9780819490261
Based on the theory of adaptive modulation, the compressed format is introduced in voice and data transmission, and a novel adaptive dynamic capability allocation algorithm is presented. In the given transmission system model, according to the channel state information (CSI) provided by channel estimating, the transmitter can adaptively select the modulation model, and shrink the voice symbol duration to improve the datathroughput of data transmission. Simulation results shows that the novel algorithm can effectively evaluate the percentage occupation of data bit in one fame, and improve the datathroughput.
As for inconsistent decision tables, this paper puts forward a reverse-order of data reduction algorithm. Compared withthe traditional methods, firstly, this algorithm makes attribute value reduction, and then makes ...
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ISBN:
(纸本)9780819490261
As for inconsistent decision tables, this paper puts forward a reverse-order of data reduction algorithm. Compared withthe traditional methods, firstly, this algorithm makes attribute value reduction, and then makes attribute reduction, which could avoid the negative factor of inconsistent individuals set. the result of attribute value reduction could be used in the proceed of attribute reduction. the time complexity of the novel algorithm is O(vertical bar C vertical bar(2)vertical bar U vertical bar(2))
this book constitutes the refereed proceedings of the 7th IFIP TC 12 internationalconference on Intelligent Information Processing, IIP 2012, held in Guilin, China, in October 2012. the 39 revised papers presented to...
ISBN:
(数字)9783642328916
ISBN:
(纸本)9783642328909
this book constitutes the refereed proceedings of the 7th IFIP TC 12 internationalconference on Intelligent Information Processing, IIP 2012, held in Guilin, China, in October 2012. the 39 revised papers presented together with 5 short papers were carefully reviewed and selected from more than 70 submissions. they are organized in topical sections on machinelearning, datamining, automatic reasoning, semantic web, information retrieval, knowledge representation, social networks, trust software, internet of things, image processing, and patternrecognition.
the rapid development of parallel computer systems, making parallel operating environment gradually mature and widely used in scientific computing and research in many fields, thus parallel database of research become...
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ISBN:
(纸本)9780819490261
the rapid development of parallel computer systems, making parallel operating environment gradually mature and widely used in scientific computing and research in many fields, thus parallel database of research becomes more and more attention and research has become an important database field of study. this network-based parallel cluster of characteristics and the current parallel computer system new trends, analyzes the network parallel clusters of workstations, parallel database data skew problem in data distribution characteristics of the environment is proposed withthe ability to adapt to the dynamic data balanced distribution programs.
the report is devoted to improvement of algorithms for separating functions by Bezier curve, which are based on the algorithm design with optimal classifying objects. the developed algorithm performs classification in...
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ISBN:
(纸本)9781467345026;9781467345002
the report is devoted to improvement of algorithms for separating functions by Bezier curve, which are based on the algorithm design with optimal classifying objects. the developed algorithm performs classification in the systems with complex order.
In this paper, an effective method for computing term association from a text corpus is presented. Two machinelearning algorithms are employed to evaluate the effectiveness of the proposed method for text mining. the...
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In order to overcome the limitations of piecewise constant phenomenon and computational burden which exist in Markov Random Field (MRF) with pair wise neighborhood and traditional learning style respectively, this pap...
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the Laplacian based matting methods are attracting a lot of attention due to their elegant and high quality closed-form solution. In this paper, we develop an alternative Laplacian construction for matting task by usi...
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ISBN:
(纸本)9780819490261
the Laplacian based matting methods are attracting a lot of attention due to their elegant and high quality closed-form solution. In this paper, we develop an alternative Laplacian construction for matting task by using local linear learning model, and naturally derive its nonlinear extension by incorporating Kernel Ridge Regression algorithm. Our Laplacian matrix construction approaches are based on the assumption that the alpha matte of each pixel point can be reconstructed from its neighbors' alpha values in each of overlapping windows. In this way the induced Laplacians can better exploit neighborhood intrinsic structure to constrain the propagation of foreground and background labels. Experimental results demonstrate the proposed approaches produce very high accuracy matte values, of which our nonlinear method even outperforms other Laplacian based matting methods on many test images.
We can face withthe patternrecognition problems where the influence of hidden context leads to more or less radical changes in the target concept. this paper proposes the mathematical and algorithmic framework for t...
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