Cluster Separation using One-Dimensional Projections
Bayesian analysis of multivariate stable distributions using one-dimensional projections
... See seminal work by Nolan (1998), Nolan and Rajput (1995), Abdul-Hamid and Nolan (1998), and also Cambanis and Miller (1981), and Nagaev (2000). Notably the parameters (α, Γ) fully define all centered multivariate stable ...
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Noble gas separation by a MOF with one-dimensional channels
... the separation efficiency and energy input, maximizing the overall Xe/Kr separation ...4 using a hybrid separation process combining membrane with low temperature sys- tem; however, detailed ...
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Scaling properties of one dimensional cluster cluster aggregation with Lévy diffusion
... of cluster-cluster aggregation with a source of monomers in the stationary state when the spatial transport of particles occurs by L´ evy ...in one dimension by vary- ing the characteristic exponent, ...
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ProxiLens: Interactive Exploration of High-Dimensional Data using Projections
... scaling projections can help analyst to discover patterns by identifying outliers and enabling visual ...these projections, artifacts and interpretation issues must be ...to cluster and analyze ...
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Control Synthesis of Large-Dimensional Systems Using Clustering-Based Projections.
... 4.2 Design II: Weight Design We next state a variant of our proposed controller where we solve (RL-2) by fixing the clus- tering set I and varying the projection weights in w instead. This type of a controller may be ...
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High Dimensional Cluster Analysis Using Path Lengths
... new cluster ID starting from one and increasing the cluster ID each time any tech- nique changes its ID, which results in the largest set of clusters ...new cluster ID each time the accu- ...
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High-dimensional one-way quantum processing implemented on d-level cluster states
... the cluster states 5,6 ...Furthermore, cluster states have structural properties that protect the quantum information, ...of cluster states, they have been studied in many different ...achieved ...
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Underdetermined convolutive source separation using two dimensional non-negative factorization techniques
... Figure 4.2 shows the average SDR performance with respects to different values of sparsity. It is clear from Figure 4.2 that the variable sparsity gives the highest SDR performance. This is attributed to the fact that ...
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Principal Component Analysis to Detect Anomaly in High Dimensional Data using Cluster
... of projections from the data ...high dimensional data suggests that each point is a similarly good anomaly from the perspective of closeness based ...
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Projections of temperature-attributable premature deaths in 209 U.S. cities using a cluster-based Poisson approach
... We obtained daily death record data with information on the county and cause of death from 1973 through 2006 from the National Center for Health Statistics. We defined cities as groupings of one or more counties ...
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On low-dimensional projections of high-dimensional distributions
... Abstract: Let P be a probability distribution on q-dimensional space. The so-called Diaconis-Freedman effect means that for a fixed dimension d q, most d-dimensional projections of P look like a ...
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Protecting Surfaces Using One-Dimensional Nanostructures
... (*) Corresponding author: [email protected] (Received:21 Oct. 2013 and Accepted: 12 Jan. 2013) Abstract: Ultraviolet waves, because of their short wavelength, have a high energy and considerable damaging effects on ...
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CiteSeerX — N Degrees of Separation: Multi-Dimensional Separation of Concerns
... Our ability t o achieve the goals of software engineering depends fundamentally on our ability t o keep separate all concerns of importance in software systems, All modern [r] ...
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Abstract In this study, one-dimensional analysis using AVL
... study, one-dimensional analysis using AVL Boost software has been carried out on a series of compression and spark ignition engines utilizing a manufacturer fitted single-entry turbocharger and a ...
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Design study of a regenerative pump using one-dimensional and three-dimensional numerical techniques
... the one-dimensional model is used to match the ...the one-dimensional optimisation into a parameterised CAD model to create a fully three-dimensional ...
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Bayesian kernel projections for classification of high dimensional data
... model. One important di↵erence between the problem of choosing of number of projections and the more general setting of variable selection is that in the latter the number of possible models is 2 n , which, ...
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Bayesian Kernel Projections for Classification of High Dimensional Data
... space, one is hoping that the underlying structure of the feature space can be summarized by a much smaller subset of the principal axes, ...high dimensional NIR spectroscopy and animal image categorization ...
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Theory of Dynamic Projections in High-Dimensional Data Visualization
... principles. One can, however, make informal arguments: Invariance is desirable because the notion of speed should be devised a priori without looking at the structure of particular ...interesting ...
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One Dimensional Consolidation
... in one dimension, using the heat ...three- dimensional heat ...has one spring constant for virgin compression and a different constant for swelling, so we have to model a material with an ...
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One dimensional searching
... Find the node (like in Find operation) with the given key and set the reference to it from its parent to its (single) child... Find the node (like in Find operation) with the given key [r] ...