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Research ArticleOpen accessIn the keywordsMODEL SELECTION VIA ROBUST VERSION OF R-SQUAREDShokrya SalehR-squared (R2) is a popular method for variable selection in linear regression models. R2 based on Least Squares (LS) regression minimizes the sum of the squared residuals; LS is sensitive to outlier observation. Alternative criterion based on M-estimators, which is less sensitive to outlying observation has been proposed. In this study explicit expression for such criterion is obtained when the … …Journal of Mathematics and Statistics, Vol. 10, Issue 3 · 9 Oct 2014 · 7,460 accessesView PDFCite
Research ArticleOpen accessIn the keywordsReceived Signal Strength Indication Modeling in Indoor Wireless Sensor NetworksEdson Taira Procopio, Alexandre de Assis Mota, Lia Toledo Moreira Mota, Luiz Rodolfo Barreto da SilvaThis study aims to identify mathematical models that represent the relation between Received Signal Strength Indication (RSSI) and objects in an indoor Wireless Sensor Network (WSN). Using the Least Squares Method, four linear models have been identified: The first one relates uplink RSSI and objects; the second one relates downlink RSSI and objects; the third one relates uplink RSSI and … …American Journal of Applied Sciences, Vol. 10, Issue 9 · 24 Aug 2013 · 6,863 accessesView PDFCite
Research ArticleOpen accessIn the keywordsOn Multiresponse Semiparametric Regression ModelSri Haryatmi, I. Nyoman Budiantara, Wahyu WibowoThe modeling between predictors and response in statistics sometimes deals with more than one response or multiresponse situation. Furthermore, it can be happen that some predictors have linear relationship with the responses and the others predictor have unknown relationship. To overcome this modeling problem we proposed multiresponse semiparametric regression model. This model has more than one response and contains both … …Journal of Mathematics and Statistics, Vol. 8, Issue 4 · 20 Feb 2013 · 7,068 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSpline Smoothing for Multi-Response Nonparametric Regression Model in Case of Heteroscedasticity of VarianceBudi Lestari, I. Nyoman Budiantara, Sony Sunaryo, Muhammad MashuriProblem statement: Assume that data (yki, tki), k = 1,2,…, p; i = 1,2,…,nk where nk represents the number of repeated measurement of kth object follows multi-response nonparametric regression model with variances of errors are heteroscedastic. Nonparametric regression curves are unknown and assumed to be smooth which are contained in Sobolev space. Random Errors are independent and normally distributed with … …Journal of Mathematics and Statistics, Vol. 8, Issue 3 · 13 Oct 2012 · 7,955 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAnalysis of Handwriting Velocity to Identify Handwriting Process from Electromyographic SignalsMohamed Benrejeb, Afef Abdelkrim, Ines ChihiProblem statement: Handwriting movement is one of the most complex activities of human motions. It’s a blend of kinesthetic, cognitive, perceptual and motor components. The study of this biological process shows that a bell-shaped velocity profiles are generally observed in the handwriting motion. We, therefore, assume that the handwriting speed has an important role in control and generation of this … …American Journal of Applied Sciences, Vol. 9, Issue 10 · 27 Aug 2012 · 7,917 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA New Self-Adaptive Neuro Fuzzy Inference System for the Removal of Non-Linear Artifacts from the Respiratory SignalA. Bhavani Sankar, D. Kumar, K. SeethalakshmiProblem statement: In this study, a new ANFIS-based adaptive filter is proposed to remove the non-linear artifacts from the respiratory signal measured using MEMS based accelerometer sensor. The data recorded from the abdomen movement includes the respiratory signal, electromyogram, 50Hz power line interference and the random electrode noise. In order to avoid convergence into local extremes, the system employs ANFIS … …Journal of Computer Science, Vol. 8, Issue 5 · 16 Feb 2012 · 6,891 accessesView PDFCite
Research ArticleOpen accessIn the keywordsApplication of Adaptive Predictive Control to a Newborn IncubatorMed Aymen Zermani, Elyes Feki, Abdelkader MamiProblem statement: This study presents an application of Indirect Adaptive Generalized Predictive Control (IAGPC) of an incubator for newborn, in order to improve the performance of temperature control. Approach: Analysis of physical phenomena of incubator was involved together knowledge of the dynamic behavior. Incubator was identified by means of Recursive Least Square (RLS) technique associated with a projection of the … …American Journal of Engineering and Applied Sciences, Vol. 4, Issue 2 · 13 Jul 2011 · 8,242 accessesView PDFCite
Research ArticleOpen accessIn the keywordsError Vector Normalized Adaptive Algorithm Applied to Adaptive Noise Canceller and System IdentificationZayed RamadanProblem statement: This study introduced a variable step-size Least Mean-Square (LMS) algorithm in which the step-size is dependent on the Euclidian vector norm of the system output error. The error vector includes the last L values of the error, where L is a parameter to be chosen properly together with other parameters in the proposed algorithm to achieve a trade-off … …American Journal of Engineering and Applied Sciences, Vol. 3, Issue 4 · 5 Nov 2010 · 8,208 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSpline Estimator in Multi-Response Nonparametric Regression Model with Unequal Correlation of ErrorsBudi Lestari, I. Nyoman Budiantara, Sony Sunaryo, Muhammad MashuriProblem statement: In many applications two or more dependent variables are observed at several values of the independent variables, such as at time points. The statistical problems are to estimate functions that model their dependences on the independent variables and to investigate relationships between these functions. Nonparametric regression model, especially smoothing splines provide powerful tools to model the functions which … …Journal of Mathematics and Statistics, Vol. 6, Issue 3 · 30 Sep 2010 · 8,168 accessesView PDFCite
Research ArticleOpen accessIn the keywordsImage Reconstruction Algorithm for Electrical Charge Tomography SystemM. F. Rahmat, M. D. Isa, K. Jusoff et al.Problem statement: Many problems in scientific computing can be formulated as inverse problem. A vast majority of these problems are ill-posed problems. In Electrical Charge Tomography (EChT), normally the sensitivity matrix generated from forward modeling is very ill-condition. This condition posts difficulties to the inverse problem solution especially in the accuracy and stability of the image being reconstructed. The objective … …American Journal of Applied Sciences, Vol. 7, Issue 9 · 30 Sep 2010 · 8,330 accessesView PDFCite