dnus nonlinear models and dynamics
Shrinkage estimation of nonlinear models and covariance matrix
... ESTIMATION OF NONLINEAR MODELS AND COVARIANCE MATRIX JIANG QIAN (B.Sc and M.Sc Nanjing University) A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF STATISTICS AND APPLIED ... appreciate all the time and effort he has spent on me I also want to thank other faculty members and support staffs of the Department of Statistics and Applied Probability for teaching me and helping me ... and the non-negative λ is a tuning parameter The ridge penalty function, introduced by Hoerl and Kennard (1970), is pλ (|βj |) = λ|βj |2 and the bridge penalty function, introduced by Frank and...
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Existence theorems in nonlinear analysis and applications to optimization related models
... recent years (e.g., Anh and Khanh [1-7], Khanh and Luc [53], Xiang, Liu and Zhou [94], Yang and Yu [96], Preface VI Yu and Xiang [98], Yu, Yang and Xiang [99], Zhou, Xiang and Yang [101]) Based ... were studied in many papers (e.g., Fort [37], Jones and Gowda [49], Khanh and Luc [53], Papageorgiou and Shahzad [78], Rapcsak [86], Zhong, Huang and Wong [105]) The properties of solution maps, ... (Horvath [46-47]), Gconvex spaces (Park and Kim [79-85]), and FC-spaces (Ding [24-32]) These spaces have been used in studying existence theorems and nonlinear problems In the third approach,...
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Thermally activated dynamics stochastic models and their applications
... the two stochastic models 1.2 Motivation and Objective 1.2.1 Langevin dynamics and Monte Carlo method The two stochastic dynamical models, the Langevin dynamical equation and the Monte Carlo ... Monte Carlo model and the Langevin dynamics, if established, could benefit researchers on both sides in reaching a fuller 1.2 Motivation and Objective understanding of stochastic dynamics Furthermore, ... hidden analytical links and prove the equivalence between the two stochastic models; • Develop systematic approaches to map the Monte Carlo models into Langevin dynamics and analytically derive...
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Existence theorems in nonlinear analysis and applications to optimization related models
... recent years (e.g., Anh and Khanh [1-7], Khanh and Luc [53], Xiang, Liu and Zhou [94], Yang and Yu [96], Preface VI Yu and Xiang [98], Yu, Yang and Xiang [99], Zhou, Xiang and Yang [101]) Based ... were studied in many papers (e.g., Fort [37], Jones and Gowda [49], Khanh and Luc [53], Papageorgiou and Shahzad [78], Rapcsak [86], Zhong, Huang and Wong [105]) The properties of solution maps, ... (Horvath [46-47]), Gconvex spaces (Park and Kim [79-85]), and FC-spaces (Ding [24-32]) These spaces have been used in studying existence theorems and nonlinear problems In the third approach,...
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SAP2000® Linear and Nonlinear Static and Dynamic Analysis and Design of Three-Dimensional Structures
... the grids and spacing in the X, Y and Z direction Set the number of grid spaces to 10 for the X direction, and to for the Y and Z directions Type ft into the X direction spacing edit box and press ... loads only, and the deck will be loaded with a Dead Load = 10 pounds per square foot (psf) and a Live Load = 100 psf The Interface The top menu line contains all of the commands and options available ... Assign, Analyze, Display and Design These listed menus contain the commands that will be needed most often when using SAP2000, and many of the most frequently used commands are accessible as a...
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Data Streams Models and Algorithms- P1
... students and researchers It is hoped that this book will provide a reference to students, researchers and practitioners in both introducing the topic of data streams and understanding the practical and ... Dimensionality Reduction and Forecasting on Streams Spiros Papadimitriou, Jimeng Sun, and Christos Faloutsos Related work Principal component analysis (PCA) Auto-regressive models and recursive least ... researchers, the topics and content will be organized in such a way so as to present the most important models, algorithms, and applications in the data mining field in a structured and concise way In...
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Data Streams Models and Algorithms- P2
... environments with limited bandwidth such as sensor networks and handheld devices Thus knowledge structure representation is an important issue After extracting models and patterns locally from ... STREAMS: MODELS AND ALGORITHMS rn Tradeoff between Accuracy and Efficiency: The main tradeoff in data stream mining algorithms is between the accuracy of the output with regard to the application and ... remove this watermark 36 DATA STREAMS: MODELS AND ALGORITHMS Discussion In this paper, we have discussed effective and efficient methods for clustering and classification of data streams The...
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Data Streams Models and Algorithms- P3
... STREAMS: MODELS AND ALGORITHMS On Demand Classification Aggarwal et al have adopted the idea of micro-clusters introduced in CluStream [2] in On-Demand classification in [3] The on-demand classification ... Demand Classification of Data Streams, Proc 2004 Int Con$ on Knowledge Discovery and Data Mining (KDD '04), Seattle, WA [4] Babcock B., Babu S., Datar M., Motwani R., and Widom J (2002) Models and ... Holder and Diane Cook, Springer Verlag, to appear lease purchase PDF Split-Merge on www.verypdf.com to remove this watermark 58 DATA STREAMS: MODELS AND ALGORITHMS [15] Gama J., Rocha R and Medas...
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Tài liệu Data Streams Models and Algorithms- P4 doc
... and whose counts are less than An item whose counts exceeds is called Hierarchy Heavy Hitter (HHH), and we want to find all HHHs in a data stream They have presented both deterministic and randomized ... Shinji Kawasoe, and Setsuo Arikawa Online algorithms for mining semi-structured data stream In ICDM, pages 27-34,2002 [4] B Babcock, S Babu, M Datar, R Motwani, and J Widom Models and f Issues in ... time was reversed and the data stream arrived in reverse order, starting at t ht and ending at t Examples of the forward and reverse density profiles are illustrated in Figures 5.1 and 5.2 respectively...
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Tài liệu Data Streams Models and Algorithms- P5 docx
... response, and both space and time are critical in processing, we examine both time and space consumption In our study, besides presenting the total time and memory taken to compute and store ... ,XN be N random variables, such that 1.1 each random variable X j takes the value vj/P with probability P and the value zero otherwise Let & be the sum of these random variables and let A~ = ... logarithmic and progressive logarithmic models discussed above, we have assumed that the base is Similar rules can be applied to any base a , where a is an integer and a > The tilted time models shown...
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Tài liệu Data Streams Models and Algorithms- P6 pdf
... data elements at a given time instant and window size refers to N 0.1 Motivation and Road Map Our aim is to develop algorithms for maintaining statistics and models that use space sublinear in ... studied by Das, Gehrke and Riedwald [6] and Kang, Naughton and Viglas [16] This further motivates the need to maintain various statistics over sliding windows, using small space and update time This ... makes On the other hand, a Monte Carlo algorithm is a randomized algorithm >A lease purchase PDF Split-Merge on www.verypdf.com to remove this watermark 158 DATA STREAMS: MODELS AND ALGORITHMS that...
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Tài liệu Data Streams Models and Algorithms- P7 ppt
... watermark 174 DATA STREAMS: MODELS AND ALGORITHMS The Chernoff bound [14] applies when X is the sum of several independent and identical Bernoulli random variables, and has a lower tail bound ... to remove this watermark DATA STREAMS: MODELS AND ALGORITHMS the wavelet coefficient definition i.e half the difference between the left hand and right hand side of the time series While this ... point with each of these random vectors Each component of the k random vectors is drawn from the normal distribution with zero mean and unit variance In addition, the random vector is normalized...
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Tài liệu Data Streams Models and Algorithms- P8 doc
... watermark 212 DATA STREAMS: MODELS AND ALGORITHMS duration w, we simply regard the stream join between S 1and S2as a relational join view over append-only bags S 1and S2with an extra "window join ... sensors, which is slower and less reliable The resulting distribution has a higher variance and looser bounds, and lags slightly behind that of S1 To correlate measurements from S1 and S2by time, we ... tuples sl and s2, SI'S ECB dominates S ~ ' SECB if and only if b(sl) b(s2) Therefore, + lease purchase PDF Split-Merge on www.verypdf.com to remove this watermark DATA STREAMS: MODELS AND ALGORITHMS...
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Tài liệu Data Streams Models and Algorithms- P9 doc
... STREAMS :MODELS AND ALGORITHMS Introduction Raw stream data, such as faults and alarms generatedby network traffic monitors and log records generated by web servers, are almost always at low level and ... Keogh and T Folias Time Series Data Mining Archive In http://www.cs.ucr:edu/"eamonn/TSDMA, 2002 [I 91 Y Law, H Wang, and C Zaniolo Query languages and data models for database sequences and data ... models such as stochastic models and multivariate regression enable capturing intra-sensor and inter-sensor dependencies in order to model sensor network data accurately Such models can be used in...
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Tài liệu Data Streams Models and Algorithms- P10 docx
... most streams exhibit a slow dip and then ascent (e.g., see 2, and and, to a lesser extent, 3, and 8) However, a number of them start fluctuating more quickly and violently when the second hidden ... a succinct summary to the user, they can help to fast forecasting and detect outliers, and they facilitate interpolations and handling of missing values, as we discuss later The rest of the chapter ... related work, on data streams and stream mining Section and overview some of the background Section describes our method and Section shows how its output can be interpreted and immediately utilized,...
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Tài liệu Data Streams Models and Algorithms- P11 doc
... watermark 306 DATA STREAMS: MODELS AND ALGORITHMS [25] H Kargupta, R Bhargava, K Liu, M Powers, P Blair, S Bushra, J Dull, K Sarkar, M Klein, M Vasa, and D Handy Vedas: A mobile and distributed data ... Pi and Pj (calculated from Xij and Xj,i) Xi\ : the kept knowledge of Pi and Pj (calculated from Xi and Xirli) Initially Xi is initialized to Sit.The first time a data is exchanged between Pi and ... remove this watermark 304 DATA STREAMS: MODELS AND ALGORITHMS that can be efficiently maintained in a distributed and incremental setting should be designed and then specific solutions that use...
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Tài liệu Data Streams Models and Algorithms- P12 ppt
... 5, 10, 15, 16,22,23,24,30, and 31 are in site A Nodes 2,6,7, 11, 17,18,25,26, and 32 are in site B Nodes 3,8, 12, 19,20, and 27 are in site C Nodes 4,9, 13, 14,21, 28, and 29 are in site D A dataset ... Babcock, S Babu, M Datar, R Motwani, and J Widom Models and issues in data stream systems In I n Principles o Database Systems f (PODS '02), 2002 [5] B Babcock and C Olston Distributed top-k monitoring ... watermark 330 DATA STREAMS: MODELS AND RCGORITHMS [lo] P Gibbons and S Tirthapura Estimating simple functions on the union of data streams In ACM Symposium on Parallel Algorithms and Architectures, 200...
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Tài liệu Data Streams Models and Algorithms- P13 docx
... 196 lease purchase PDF Split-Merge on www.verypdf.com to remove this watermark DATA STREAMS: MODELS AND ALGORITHMS Hoeffding Inequality, 46, 174 Hoeffding Trees, 46 HPSTREAM 22 Iceberg Cubing ... Stream clustering, 22 Pseudo-random number generation for sketches, 186 Punctuations for Stream Joins, 214 Pyramidal Time F m e , 12 Quantile Estimation, 198 Quantiles and Equi-depth Histograms, ... in Sensor Networks, 337 Query Processing with Wavelets, 181 Querying Data Streams, 238 Random Projection and Sketches, 184 Relational Join View, 11 Relative Error Histogram Construction, 198 Reservoir...
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Tài liệu Bài 12: ICA by Nonlinear Decorrelation and Nonlinear PCA doc
... 240 ICA BY NONLINEAR DECORRELATION AND NONLINEAR PCA is a stochastic gradient algorithm and the other one a recursive least mean-square algorithm 12.1 NONLINEAR CORRELATIONS AND INDEPENDENCE ... correlation, we here define the nonlinear correlation of the random variables y1 and y2 as Eff (y1 )g (y2 )g Here, f (y1 ) and g (y2 ) are two functions, of which at least one is nonlinear Typical examples ... Cichocki e 244 ICA BY NONLINEAR DECORRELATION AND NONLINEAR PCA B B and Unbehauen proposed a feedforward network with weight matrix , with the mixture vector for input and with output = Now...
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08 TAYLOR MODELS AND OTHER VALIDATED FUNCTIONAL INCLUDING METHOD MAKINO & m BERZ
... ) and (Pg,h , Ig,h ) be n-th order Taylor models for f and g around xh on xh + [h, h]v D Let the remainder bounds If,h and Ig,h satisfy If,h = O(hn+1 ) and Ig,h = O(hn+1 ) Then the Taylor models ... models (Pf +g , If +g,h ) and (Pf ãg , If ãg,h ) for the sum and products of f and g obtained via addition and multiplication of Taylor models satisfy If +g,h = O(hn+1 ), and If ãg,h = O(hn+1 ) ... arithmetic Addition Addition of two Taylor models T (1) and T (2) with coef(1) (2) (1) (1) (2) (2) cients and aj , coding integers (ni,1 , ni,2 ) and (nj,1 , nj,2 ), and remainder bounds I1 , I2 , respectively,...
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