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11 results for “Expectation Maximization”
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Research ArticleOpen accessEvery word in the titleA NOVEL TWO STAGE CARRIER FREQUENCY OFFSET ESTIMATION AND COMPENSATION SCHEME IN MULTIPLE INPUT MULTIPLE OUTPUT-ORTHOGONAL FREQUENCY DIVISION MULTIPLEXING SYSTEM USING EXPECTATION AND MAXIMIZATION ITERATIONMalarvezhi Pandy, Kumar RamamoorthyMultiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO-OFDM) is a promising technique to handle impairments of multipath channel. Alternatively, one of its major drawbacks is drift in carrier frequency, called Carrier Frequency Offset (CFO). Due to CFO, Inter Carrier Interference (ICI) occurs and results in a large performance degradation. The study proposes a novel two stage CFO estimation and compensation … …Journal of Computer Science, Vol. 9, Issue 11 · 30 Sep 2013 · 6,549 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAn Accurate Mango Pest Identification Employing the Gaussian Mixture Model and Expectation-Maximization (EM) AlgorithmD. Lita Pansy, M. MuraliMangoes are fruits that originated in South and Southeast Asia. Mango fruits are consumed in high volume worldwide. However, fruit, stem, root, and mango leaves are damaged by pests, and it has a significant negative impact on mango production. Many works were developed for the pest detection of mango; but, none of the works concentrated on the practical applicability and … …Journal of Computer Science, Vol. 21, Issue 1 · 3 Dec 2024 · 5,063 accessesView PDFCite
Research ArticleOpen accessIn the keywordsStock Trading Using PE Ratio Based on Bayesian InferenceHaizhen Wang, Ratthachat Chatpatanasiri, Pairote SattayathamThe Price Earnings (PE) ratio is one of the most widely applied tool for the firm valuation in a security market. Unfortunately, recent academic developments in financial econometrics and machine learning have rarely looked at this tool. In the paper, we propose to formalize a process of fundamental PE ratio estimation by employing Dynamic Bayesian Network (DBN) methodology. Forward-backward inference … …Journal of Mathematics and Statistics, Vol. 13, Issue 3 · 29 Sep 2017 · 7,425 accessesView PDFCite
Research ArticleOpen accessIn the keywordsPARALLEL IMPLEMENTATION OF EXPECTATION-MAXIMISATION ALGORITHM FOR THE TRAINING OF GAUSSIAN MIXTURE MODELSG. F. Araújo, H. T. Macedo, M. T. Chella et al.Most machine learning algorithms need to handle large data sets. This feature often leads to limitations on processing time and memory. The Expectation-Maximization (EM) is one of such algorithms, which is used to train one of the most commonly used parametric statistical models, the Gaussian Mixture Models (GMM). All steps of the algorithm are potentially parallelizable once they iterate over … …Journal of Computer Science, Vol. 10, Issue 10 · 9 Jul 2014 · 6,937 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA New Modified Gaussian Mixture Model for Color-Texture SegmentationM. Sujaritha, S. AnnaduraiProblem statement: This study presents a new, simple and efficient modified Gaussian mixture model based clustering algorithm for color-texture segmentation. The proposed mixture model introduces a new component density function which incorporates spatial information and the weighting factor for neighborhood effect is fully adaptive to the image content. Approach: It enhances the smoothness towards piecewise-homogeneous segmentation and reduces the edge-blurring … …Journal of Computer Science, Vol. 7, Issue 2 · 25 Feb 2011 · 7,329 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Application of Session Based Clustering to Analyze Web Pages of User Interest from Web Log FilesC. P. Sumathi, R. Padmaja Valli, T. SanthanamProblem statement: With the continued growth and proliferation of e-commerce, Web services and Web-based information systems, the volumes of click-stream and user data collected by Web-based organizations in their daily operations have reached astronomical proportions. Analyzing such data can help these organizations optimize the functionality of web-based applications and provide more personalized content to visitors. This type of analysis involved … …Journal of Computer Science, Vol. 6, Issue 7 · 31 Jul 2010 · 6,877 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Extended Semi-Parametric Accelerated Failure Time Cure Model for Partial Cure Information KnownYu Wu, Yong Lin, Shou-En Lu et al.Cure model is a useful model for analyzing failure time data when there is evidence of long-term survivors. In traditional cure models, it is assumed that the cured or uncured status in the censored set cannot be distinguished. However, in many occasions, data of some diagnostic procedures, with some sensitivity and specificity, may have provided partial information about the cured … …Current Research in Biostatistics, Vol. 8, Issue 1 · 11 Dec 2018 · 7,618 accessesView PDFCite
Research ArticleOpen accessIn the keywordsShots Temporal Prediction Rules for High-Dimensional Data of Semantic Video RetrievalShaimaa Toriah Mohamed Toriah, Atef Zaki Ghalwash, Aliaa A.A. YoussifTemporal consistency stands as a vital property in semantic video retrieval. Few research studies can exploit this useful property. Most of the used methods in those studies depend on rules defined by experts and use ground-truth annotation. The Ground-truth annotation is time-consuming, labor intensive and domain specific. Additionally, it involves a limited number of annotated concepts and a limited number … …American Journal of Applied Sciences, Vol. 15, Issue 1 · 30 Jan 2018 · 8,117 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Efficient Unified K-Means Clustering Technique for Microarray Gene Expression DataP. Valarmathie, K. Dinakaran, T. RavichandranProblem statement: Using microarray techniques one could monitor the expressions levels of thousands of genes simultaneously. One challenge was how to derive meaningful insights into expressed data. This might be carried out by clustering techniques such as hierarchical and k-means, but most of the clustering techniques were largely heuristic in nature and are associated with some unresolved issues like how … …Journal of Computer Science, Vol. 7, Issue 7 · 28 Jun 2011 · 6,912 accessesView PDFCite
Research ArticleOpen accessIn the abstractGeneral Linear Models in a Missing Outcome Environment of Clinical Trials Incorporating with Splines for Time-Invariant Continuous AdjustmentMinjeong Park, Dejian Lai, Xianglin L. Du et al.Missing data is a common occurrence in longitudinal studies of health care research. Although many studies have shown the potential usefulness of current missing analyses, e.g., (1) Complete Case (CC) analysis; (2) imputation methods such as Last Observation Carried Forward (LOCF), multiple imputations, Expectation-Maximization algorithm approach; and (3) methods using all available data such as linear mixed model and generalized … …Current Research in Biostatistics, Vol. 5, Issue 1 · 18 Aug 2015 · 7,401 accessesView PDFCite