To meet the increasing capacity and mobility as well as decrease the costs in next-generation optical access networks, RoF technology is a promising technique in the emerging optical and wireless convergence network, ...
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ISBN:
(纸本)9781849195058
To meet the increasing capacity and mobility as well as decrease the costs in next-generation optical access networks, RoF technology is a promising technique in the emerging optical and wireless convergence network, mm-wave generation is a key technique to realize the convergence network. In this paper, existing optical mm-wave generation technologies are introduced, including direct modulation, optical heterodyning and external modulation. Associated with Shanghai University, a scheme based on Optical Frequency Multiplication employing a dual drive Mach-Zehnder Modulator (DD-MZM) is presented. The novel efficient technique does not require expensive high-frequency electrical equipment. Moreover, no optical filtering is used, which significantly reduces the cost.
Based on analysis of basic cubic spline interpolation, the clamped cubic spline interpolation is generalized in this paper. The methods are presented on the condition that the first derivative and second derivative of...
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As an important component of data mining, Cluster Analysis (CA) has being attached importance to artificial intelligence, machine learning and other fields. Traditional clustering methods have been studied for a relat...
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As an important component of data mining, Cluster Analysis (CA) has being attached importance to artificial intelligence, machine learning and other fields. Traditional clustering methods have been studied for a relatively long time;their technologies are mature and consequently they are well-applied. However, they are insufficient in clustering accuracy, noise sensitivity, along with effect on mass of data and non-convex clustering. Granular computing, which is regarded as a label of theories, methodologies, techniques, and tools, is an emerging conceptual and computing par informationprocessing. It plays an important role informationprocessing for fuzzy, uncertainty, partial truth and soft computing and is one of the main study stream in A.I. This paper introduces some new clustering methods, such as Fuzzy clustering, Clustering Algorithm Based on Rough Set, and clustering algorithm based on quotient space theory, emphatically expounds the basic thought and typical algorithms of these methods, and comparative analysis is carried out among these methods. Finally, new clustering algorithms are prospected and we put forward the value of research direction.
Based on analysis of cubic spline interpolation, the differentiation formulas of the cubic spline interpolation on the three boundary conditions are put up forward in this paper. At last, this calculation method is il...
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The rough neural networks (RNNs) are the neural networks based on rough set and one kind of hot research in the artificial intelligence in recent years, which synthesize the advantage of rough set to process uncertain...
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The grey system forecasting model, neural network forecasting model and support vector machine forecasting model are proposed in this paper. Taking the road goods traffic volume from year of 1996 to 2003 in the whole ...
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In image/video processing software and hardware products, low complexity interpolation algorithms, such as cubic and splines methods, are commonly used. However, these methods tend to blur textures and produce jaggy e...
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In image/video processing software and hardware products, low complexity interpolation algorithms, such as cubic and splines methods, are commonly used. However, these methods tend to blur textures and produce jaggy effect compared with other adaptive methods such as NEDI, SAI. Tanner graph based image interpolation algorithm has better effect in dealing with edge and texture, but with high computation complexity. Thanks to the high performance parallel processing capability of today's GPU, use of complex algorithms for real time application is becoming possible. In this paper, we present a fast algorithm for tanner graph based image interpolation and it's implementation on GPU. In our algorithm, the image model training process of tanner graph based image interpolation is greatly simplified. Experimental results show that the GPU implementation can be more than 47 times as fast as the CPU implementation.
The bottleneck problem has emerged in feature selection when processing high-dimension and large-scale data, so in the past decade, the researches on feature selection have not adhere to the traditional algorithms and...
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The bottleneck problem has emerged in feature selection when processing high-dimension and large-scale data, so in the past decade, the researches on feature selection have not adhere to the traditional algorithms and ideas, showing a new trend of combining many new mathematical tools, which opens new space for feature selection applied in pattern recognition and makes further development in knowledge discovery and data mining. Granular computing has begun to take shape and show effect as a new idea of intelligentinformationprocessing, which creates the conditions for feature selection applied in data. The paper describes a new feature selection algorithm, basing on granular computing and making rough set approximation as background, the algorithm generates the granules, using a tolerance function, distinguishes noise data and inconsistent data, to achieve feature selection in the information table, and be effective for large-scale data sets.
China is the largest food consumption country in the world. With the social and economic development, China's food security has become a global attention. Grain security research involves many uncertain factors: a...
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China is the largest food consumption country in the world. With the social and economic development, China's food security has become a global attention. Grain security research involves many uncertain factors: as well as quantitative and qualitative information. In order to get the grain security status comprehensively, we proposed a method to evaluate risk in grain security based on multifactor information fusion. In the method, the quantitative and qualitative information were used to construct the basic probability assignment, and the attribute weights was got based on the Analytic Hierarchy Process method. After that, the multifactor fusion results were got based on the Dempster combination rule. The effectiveness of the method was verified with a numeric example that the data comes from the yearbook of China in 2007. The Results show that the method is effective and can correctly reflect the grain safety warning degrees.
Discriminant analysis, especially Fisherface and its numerous variants, have achieved great success in face recognition. However, these methods fail to work for face recognition from Single Sample per Person (SSPP), s...
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