Non-negative matrix factorization(NMF) has been widely used in mixture analysis for hyperspectral remote sensing. When used for spectral unmixing analysis, however, it has two main shortcomings:(1) since the dimension...
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Non-negative matrix factorization(NMF) has been widely used in mixture analysis for hyperspectral remote sensing. When used for spectral unmixing analysis, however, it has two main shortcomings:(1) since the dimensionality of hyperspectral data is usually very large, NMF tends to suffer from large computational complexity for the popular multiplicative iteration rule;(2) NMF is sensitive to noise(outliers), and thus the corrupted data will make the results of NMF meaningless. Although principal component analysis(PCA) can be used to mitigate these two problems, the transformed data will contain negative numbers, hindering the direct use of the multiplicative iteration rule of NMF. In this paper, we analyze the impact of PCA on NMF, and find that multiplicative NMF can also be applicable to data after principal component transformation. Based on this conclusion, we present a method to perform NMF in the principal component space, named ‘principal component NMF'(PCNMF). Experimental results show that PCNMF is both accurate and time-saving.
With the rapid development of Internet technology, crowdsourcing, as a flexible, effective and low-cost problem-solving method, has begun to receive more and more attention. The use of crowdsourcing to evaluate the qu...
With the rapid development of Internet technology, crowdsourcing, as a flexible, effective and low-cost problem-solving method, has begun to receive more and more attention. The use of crowdsourcing to evaluate the quality of linked data has also become a research hotspot. This paper proposes the concept of Domain Specialization Test (DST), which uses domain professional testing tasks DSTs to evaluate the professionalism of workers, and combines the idea of Mini-batch Gradient Descent (MBGD) to improve the EM algorithm, and the MBEM algorithm is proposed to achieve efficient and accurate evaluation of task results. The experimental results show that the proposed method can screen out the appropriate workers for the linked data crowdsourcing task and improve the accuracy and iteration efficiency of the results.
Research on software quality has a very important strategic and practical significance to improve software quality,and promote the healthy and orderly development of software *** paper study and realize the visualizat...
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Research on software quality has a very important strategic and practical significance to improve software quality,and promote the healthy and orderly development of software *** paper study and realize the visualization of software quality,combined the change and complexity of program,based on existing research.
With the extensive application of the knowledge base (KB), how to complete it is a hot topic on Semantic Web. However, many problems go with the big data, and the event matching is one of these problems, which is find...
With the extensive application of the knowledge base (KB), how to complete it is a hot topic on Semantic Web. However, many problems go with the big data, and the event matching is one of these problems, which is finding out the entities referring to the same things in the real world and also the key point in the extending process. To enrich the emergency knowledge base (E-SKB) we constructed before, we need to filter out the news from several web pages and find the same news to avoid data redundancy. In this paper, we proposed a hierarchy blocking method to reduce the times of comparisons and narrow down the scope by extracting the news properties as the blocking keys. The method transforms the event matching problem into a clustering problem. Experimental results show that the proposed method is superior to the existing text clustering algorithm with high precision and less comparison times.
Support vector machine (SVM) is good at classifying high dimensional data. Parameter setting in the SVM training procedure, along with the feature selection, significantly influences the classification accuracy. An im...
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ISBN:
(纸本)9781450353489
Support vector machine (SVM) is good at classifying high dimensional data. Parameter setting in the SVM training procedure, along with the feature selection, significantly influences the classification accuracy. An improved algorithm based on particle swarm optimization (PSO) for feature selection and parameters optimization of SVM (GPSO-SVM) is proposed to improve the classification accuracy and select the number of features as little as possible. This method introduces crossover and mutation operator from genetic algorithm (GA), which allows the particle to carry out crossover and mutation operations after iteration and update to avoid the problem of falling into local optimum and premature maturation in
Research on software quality has a very important strategic and practical significance to improve software quality, and promote the healthy and orderly development of software industry. This paper study and realize th...
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Research on software quality has a very important strategic and practical significance to improve software quality, and promote the healthy and orderly development of software industry. This paper study and realize the visualization of software quality, combined the change and complexity of program, based on existing research.
With the rapid development of RFID technologies,RFID has been introduced into applications such as supply chain management,inventory control,sampling inspection,3-D positioning and object ***,the reader accesses all t...
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ISBN:
(纸本)9781509009107
With the rapid development of RFID technologies,RFID has been introduced into applications such as supply chain management,inventory control,sampling inspection,3-D positioning and object ***,the reader accesses all the tags in its interrogation region while some applications may only need to identify the tags in a specified area which is smaller than the reader's interrogation *** paper concerns the essential problem of estimating cardinality of tags in the specified *** key novelty of our solution builds on an estimation synopsis that can capture key counting information by moving the reader as well as a simple *** the help of this data structure,a BS can be obtained which only contains the target *** computing the number of 1 in the BS,we can easily get cardinality |E| of the tags in the specified *** conduct extensive experiments to examine this design and the results shows that our solution achieves high *** it not requires any modification of tags and can be implemented with only one reader and some passive RFID tags,the proposed method is easy to deploy in a practical system.
This paper investigates a kind of switched discrete-time neural network. Such neural network is composed of multiple sub-networks and switched different sub-networks according to the states of neural network. There is...
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This paper investigates a kind of switched discrete-time neural network. Such neural network is composed of multiple sub-networks and switched different sub-networks according to the states of neural network. There is no common equilibrium for all of sub-networks, i.e., multiple equilibria coexist. Firstly, a bounded condition is presented for the switched discrete-time neural network. And then sufficient conditions are derived to ensure region stability of the equilibrium points of such neural network by mathematical analysis and nonsingular M-matrix theory. Four examples are presented to verify the validity of our results.
Networked systems often relies on distributed algorithms to achieve a global computation goal with iterative local information exchanges between neighbor nodes. To preserve data privacy, a node may add a random noise ...
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Path planning system is one of the key component for the unmanned aerial vehicles(UAVs) and mobile robots in modern operational systems used in all sorts of ***,genetic algorithm(GA) plays a big role in dealing with o...
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ISBN:
(纸本)9781467397155
Path planning system is one of the key component for the unmanned aerial vehicles(UAVs) and mobile robots in modern operational systems used in all sorts of ***,genetic algorithm(GA) plays a big role in dealing with optimization ***,compared to GA,genetic programming(GP) displays better modeling and optimizing ability in path planning *** is capable of dealing with UAV and mobile robot path planning *** improves performance by utilizing generalized hierarchical computer programs and optimizing *** paper presents an optimized GP method which applies to path planning *** special designed function and symbol operators are proposed and appended to the binary tree structure,as well as the redesigned decoding *** the combination of selection and reproduction operation,the optimized GP accomplishes the design of path *** using the optimized GP method,experiment results display better fitness paths against GA method.
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