This book isn't designed to be just another theoretical text on statistics or data mining. Instead, it's aimed at database administrators who want to buttress their understanding of statistics to support data ...
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ISBN:
(纸本)9781893115545
This book isn't designed to be just another theoretical text on statistics or data mining. Instead, it's aimed at database administrators who want to buttress their understanding of statistics to support data mining and customer relationship management, and analytics, and who want to use Structured Query Language. Each chapter is independent and self-contained with examples that are tailored to business applications. Each analysis technique will be expressed in a mathematical format that lends itself to coding either as a database query or as a Visual Basic procedure using SQL.
This paper proposes a DC-link voltage control method for the permanent magnet synchronous generator (PMSG) wind power system with a full-rated back-to-back converter, to improve the dc-link voltage dynamic response un...
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ISBN:
(纸本)9781467343558;9781467343541
This paper proposes a DC-link voltage control method for the permanent magnet synchronous generator (PMSG) wind power system with a full-rated back-to-back converter, to improve the dc-link voltage dynamic response under normal operation and grid faults conditions. The dc-link voltage is controlled by the motor-side converter, while the grid-side converter is responsible for the maximum power point tracking. Considering the system nonlinear characteristic, a dc-link voltage controller is designed based on the feedback linearization theory. With this control scheme, the dc-link voltage responses much faster than other control structures. It can suppress the dc-link voltage fluctuation with the wind speed varying and prevent the voltage from rising too high under grid faults. The validity of the control algorithm has been verified by simulation with Matlab/Simulink, and the results show a better dc-link dynamic response with the proposed control scheme.
As the network technique is fast developing, the microblog has been a significant carrier representing the social public opinions. Therefore, it is important to investigate the propagation characteristics of the topic...
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As the network technique is fast developing, the microblog has been a significant carrier representing the social public opinions. Therefore, it is important to investigate the propagation characteristics of the topics and to unearth the opinion leaders in Micro-blog network. The propagation status of the hot topics in the Micro-blog is influenced by the authority of the participating individuals. We build a time-varying model with the variational external field strength to simulate the topic propagation process. This model also fits for the multimodal events. The opinion leaders are important individuals who remarkably influence the topic discussions in its propagation process. They can help to guide the healthy development of public opinion. We build an AHP model based on the influence, the support, and the activity of a node, as well as a microblog-rank algorithm based on the weighted undirected network, to unearth and analyze the opinion leaders' characteristics. The experiments in the data, collected from the Sina Micro-blog from October 2012 to November 2012 and from January 2013 to February 2013, show that our models predict the trend of hot topic efficiently and the opinion leaders we found are reasonable.
We address the challenging problem of the joint estimation of transmitted symbols and phase distortions in standardized multicarrier systems, including pilot or virtual subcarriers. These subcarriers create time corre...
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We address the challenging problem of the joint estimation of transmitted symbols and phase distortions in standardized multicarrier systems, including pilot or virtual subcarriers. These subcarriers create time correlation on the useful transmitted OFDM signal that we propose to take into account by an autoregressive model. Because the phase distortions are nonlinear, we set the joint estimation algorithm on the framework of the Sequential Monte Carlo methods. Simulation results are provided in terms of bit error rate (BER) and mean square error (MSE);they highlight the efficiency and the robustness of the estimator.
An efficient algorithm is described for generating subsets of a set S which satisfy constraints of the form: 'If sj is a member of the subset, then sj must also be a member of the subset.' The algorithm has be...
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An efficient algorithm is described for generating subsets of a set S which satisfy constraints of the form: 'If sj is a member of the subset, then sj must also be a member of the subset.' The algorithm has been programmed in the WISP language and successfully run on the IBM 7094 in connection with a routine to detect feedback in multidimensional iterative networks. [ABSTRACT FROM AUTHOR]
Spatial cluster analysis is an important data mining task. Typical techniques include CLARANS, density- and gravity-based clustering, and other algorithms based on traditional von Neumann's computing architecture....
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Spatial cluster analysis is an important data mining task. Typical techniques include CLARANS, density- and gravity-based clustering, and other algorithms based on traditional von Neumann's computing architecture. The purpose of this paper is to propose a technique for spatial cluster analysis based on sticker systems of DNA computing. We will adopt the Bin-Packing Problem idea and then design algorithms of sticker programming. The proposed technique has a better time complexity. In the case when only the intracluster dissimilarity is taken into account, this time complexity is polynomial in the amount of data points, which reduces the NP-completeness nature of spatial cluster analysis. The new technique provides an alternative method for traditional cluster analysis.
In the past few years, several encryption algorithms based on chaotic systems have been proposed as means to protect digital images against cryptographic attacks. These encryption algorithms typically use relatively s...
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In the past few years, several encryption algorithms based on chaotic systems have been proposed as means to protect digital images against cryptographic attacks. These encryption algorithms typically use relatively small key spaces and thus offer limited security, especially if they are one-dimensional. In this paper, we proposed a novel image encryption algorithm based on Rubik's cube principle. The original image is scrambled using the principle of Rubik's cube. Then, XOR operator is applied to rows and columns of the scrambled image using two secret keys. Finally, the experimental results and security analysis show that the proposed image encryption scheme not only can achieve good encryption and perfect hiding ability but also can resist exhaustive attack, statistical attack, and differential attack.
We describe new methods for denoising and detection of gravitational waves embedded in additive Gaussian noise. The methods are based on total variation denoising algorithms. These algorithms, which do not need any a ...
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We describe new methods for denoising and detection of gravitational waves embedded in additive Gaussian noise. The methods are based on total variation denoising algorithms. These algorithms, which do not need any a priori information about the signals, have been originally developed and fully tested in the context of image processing. To illustrate the capabilities of our methods we apply them to two different types of numerically-simulated gravitational wave signals, namely bursts produced from the core collapse of rotating stars and waveforms from binary black hole mergers. We explore the parameter space of the methods to find the set of values best suited for denoising gravitational wave signals under different conditions such as waveform type and signal-to-noise ratio. Our results show that noise from gravitational wave signals can be successfully removed with our techniques, irrespective of the signal morphology or astrophysical origin. We also combine our methods with spectrograms and show how those can be used simultaneously with other common techniques in gravitational wave data analysis to improve the chances of detection.
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