... performance of four alternative track-before-detect algorithms has been investigated for a range of targetSNR values and speeds. For most of the scenarios the differ-ence in detection performance ... of detection for that SNR. The false trackperformance at the SNR values of interest is shown in Tab l e 2.The false track performance of the PDAF-AI is clearly unac-ceptable below 12 dB. For ... history was included.At 3 dB, all of the algorithms showed degraded detec-tion performance and found less than half of the targets.Again, the H-PMHT performed poorly for high speed tar-gets. It...
... information in the probability distributions of words for each class. For example, if the word “pro-fessor” is the most likely word for faculty home pages, itwill have a large probability for ... Bayes-optimal estimates for these parameters from a set of labeled training data.Here, the estimate of the probability of word wtin classcjis:2Many previous formalizations of the multinomial ... of the classification tasks from Reuters.Multinomial event models do an average of 4.8% pointsbetter. This domain tends to require smaller vocabular-ies for best performance. See Figure 6 for...
... based on information that is not immediatelyapparent from the data. For example, in the evaluation of the importance of re-cycling of STAT5 [9–11], a pri-mary argument for the importance of this ... dataalone. After that, we review methods for comparison of the predictive ability of two models, and finally sug-gest a scheme for the general comparisonof two ormore models. In the subsequent ... 23,2747–2753.Supporting informationThe following supplementary material is available:Doc. S1. Simulation files used for the calculations inthe examples.Doc. S2. Summary of standard formulae for model comparison, ...
... gen-eration of basic Stanford dependencies (for constituent parsers) and part -of- speech tagging (for dependency parsers).3 ResultsTable 3 tabulates efficiency and performance for allparsers; ... Proceedings of the fourth SIGHAN bakeoff.Fei Wu and Daniel S. Weld. 2010. Open information extractionusing Wikipedia. In Proceedings of the 48th Annual Meet-ing of the Association for Computational ... Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics, pages 11–16,Jeju, Republic of Korea, 8-14 July 2012.c2012 Association for Computational LinguisticsA Comparison...
... thedocument.From a linguistic point of view, a document ismade up of words, and the semantics of the doc-ument is determined by the meaning of the wordsand the linguistic structure of the document. TheNaive ... respectto the amount of information it captures about the307 3.2 Feature Selection in the Multinomialused feature ranking functions of the form in (10):ModelMutual information as in (9) ... parame-ters of c3 with distribution P(dilc3; 0). The likeli-hood of a document is given by the total probabil-ity0) = E p(eij=1 Of course, the true parameters 0 of the mixturemodel...
... m-component of the I's of / contains two or more m-components of the Ts of T{I) (i.e., no m-component of the I's of / is split by T). FC2. Every m-component of the Ts of / ... n-components of the O's of / (i.e., no two n-components of the O's of / are merged by T). BC4. Every n-component of the O's of T{I) contains an n-component of the O's of / (i.e., ... image transformation of A preserves foreground connectivity for the input image I. Proof. Let T be A's cyclic image transformation. Suppose T does not preserve foreground connectivity...
... coded as 0 for homozygote of themajor allele, 1 for heterozygote, and 2 for homozygote of the minor allele, respectively.Classification algorithms In this study, we used three families of classification ... decisiontree, as a basis for comparisons. These classifiers were per-formed using the Waikato Environment for KnowledgeAnalysis (WEKA) software [19]. First, naive Bayes is thesimplest form of Bayesian ... BioMed CentralPage 1 of 8(page number not for citation purposes)Journal of Translational MedicineOpen AccessResearchA comparisonof classification methods for predicting Chronic Fatigue...
... Department of Laboratory Medicine, University of Washington, Seattle, WA, USA, 2Department of Microbiology, University of Washington, Seattle, WA, USA, 3Department of Pathobiology, University of ... 4Department of Biostatistics, University of Washington, Seattle, WA, USA, 5Department of Medicine, University of Washington, Seattle, WA, USA, 6Department of Pediatrics, University of Washington, ... a trend for increased HMR for Taq amplified HALT-C samples as wellas for HMR and complexity scores for HCV/HIV co-infected samples. Based on the current results, it would Comparison of quasipecies...
... Half of the summation of PCSA values for non-primaryflexors was added to each of the two primary flexorswhile a third of the summation of PCSA values for non-primary extensors ... networksforestimationofthumb-tipforcesunderfourdifferentconfigurations. In another study, performance of a Hill-based physiological muscle model was compared to aneural network for estimation of forearm ... witnessed for forces of up to30% of the maximum isometric force [33]. These non-linear relationships can be associated with exponentialincreases in firing rate of motor units as muscle forcesincrease...
... parameter r oft en plays an important role in the perfor-mance of the reconstruction algorithms. Hence, webelieve it is a fair comparisonof al gorithms only if eachreaches same level of OSR. ... formulation of the reconstruction problem wasproposed by Lazar and co-workers [4] to i ncrease thespeed of the reconstruction algorithm. In both recon-struction algorithms, the inversion of ... tolerancelevel of the other two methods to a low value to boostthe low noise performance, their performance would bemuch worse at high noise level, as shown in F igure 5c (for example the performance of...
... StanfordUniversity, Stanford, Calif. At Stanfor d, hedeveloped image processing algorithms for the Programmable Digital Camera project.He also consulted for industry in the ar-eas ofdigital ... Basedon these basic reconstruction models, researchers have de-veloped algorithms with a joint formulation of reconstruc-tion and registration [19–22], and other algorithmsfor mul-tispectral ... additional information from each LR image.Generally, SR techniques can be divided into two classes of algorithms, namely, f requency domain algorithms and spa-tial domain algorithms. Most of the...
... 10.1155/ASP/2006/87298Use of Genetic Algorithmsfor Contrast and EntropyOptimization in ISAR AutofocusingMarco Martorella, Fabrizio Berizzi, and Silvia BruscoliDepartment of Information Engineering, University of ... image entropy. In this papera solution of this problem is proposed by using genetic algorithms. The performances of the new algorithms that make use of genetic algorithms overcome the problem with ... ineering (EEE) of the University of Adelaide under apostdoctoral contract, and the Department of Information Tech-nology and Electrical Engineering (ITEE) of the University of Queensland as...
... Applicationsexists for each x, y ∈ SE; ii a uniformly Gˆateaux differentiable norm, if for each y in SE,the limit 2.2 is uniformly attained for x ∈ SE; iii aFr´echet differentiable norm,ifforeach ... 2.2 is attained uniformly for y ∈ SE; iv a uniformly Fr´echetdifferentiable norm we also say that E is uniformly smooth, if the limit 2.2 is attaineduniformly for x, y SE ì SE. A ... pagesdoi:10.1155/2009/824374Research ArticleConvergence Comparisonof Several Iteration Algorithms for the Common Fixed Point ProblemsYisheng Song and Xiao LiuCollege of Mathematics and Information Science, Henan Normal...