Search for: robust-methods
Article International IEEE/EMBS Conference on Neural Engineering, NER, San Diego, CA ; 2013 , Pages 1070-1075 ; 19483546 (ISSN); 9781467319690 (ISBN) ; Bahrani, M ; Setarehdan, S. K ; Sharif University of Technology
This research presents a robust method for P300 component recognition and classification in EEG signals for a P300 Speller Brain-Computer Interface (BCI). The multiresolution wavelet decomposition technique was used for feature extraction. The feature selection was done using an improved t-test method. For feature classification the Quadratic Discriminant Analysis was employed. No any particular specification is previously assumed in the proposed algorithm and all the constants of the system are optimized to generate the highest accuracy on a validation set. The method is first verified in offline experiments on 'BCI competition 2003' data set IIb and data recorded by Emotiv Neuroheadset and...
Article IET Signal Processing ; 2021 ; 17519675 (ISSN) ; Behnia, F ; Shokouhmand, A ; Shaker, G ; Sharif University of Technology
Institution of Engineering and Technology 2021
A robust method for ultra-wideband (UWB) imaging of buried shallow objects based on time gating, Wiener filtering, as well as constant false alarm rate (CFAR) is proposed. Moreover, it is demonstrated that Wiener filtering can be used as a clutter removal tool in UWB signal applications. Basically, the problem with time gating method is that the length of the timing window for unknown targets cannot be determined accurately in advance. In fact, it is a blind methodology and some targets can be missed due to a lack of pre-knowledge about their depth. Imprecise window length selection leads to missing some parts of the target signals along with the clutter, which in turn increases the missed...
Novel approaches for online modal estimation of power systems using PMUs data contaminated with outliers, Article Electric Power Systems Research ; Volume 124 , July , 2015 , Pages 74-84 ; 03787796 (ISSN) ; Hatami, M ; Parniani, M ; Sharif University of Technology
Elsevier Ltd 2015
One of the most important issues in modal estimation of power systems using PMUs data is the negative effect of outliers. Hence, in addition to the techniques of analyzing PMUs data, the necessity of implementing some kinds of approach to overcome these outliers is tangible. This paper aims to present different approaches to overcome outliers and also estimate the electromechanical modes of the system accurately when there is suspicion that the PMUs data may be contaminated by discordant measurements. Proposed approaches are generally categorized into two main classifications: the first category detects and modifies outliers in the pre-processing stage adaptively and then prepares the...
Article Applied Mathematical Modelling ; Volume 36, Issue 5 , 2012 , Pages 2128-2141 ; 0307904X (ISSN) ; Karimi Taheri, A ; Sharif University of Technology
In this paper the previous velocity field proposed by the authors for the prediction of strain field and deformation load of circular cross section billet in ECAE process has been extended to take into account the deformation behavior of bimetal circular billet in the same process. Accordingly, using Bezier method, as a robust method for determining the geometry of the streamlines, the strain field developed in the circular bimetal billet is calculated. Then, based on the kinematically admissible velocity and strain fields and using the upper bound theorem the ECAE load is predicted. It was found that at constant inner corner angle of ECAE die, with decreasing of outer curve corner the...
Application of the active learning method to the retrieval of pigment from spectral remote sensing reflectance data, Article International Journal of Remote Sensing ; Volume 30, Issue 4 , 2009 , Pages 1045-1065 ; 01431161 (ISSN) ; Bagheri Shouraki, S ; Fell, F ; Schaale, M ; Fischer, J ; Tavakoli, A ; Preusker, R ; Tajrishy, M ; Vatandoust, M ; Khodaparast, H ; Sharif University of Technology
Due to the noise that is present in remote sensing data, a robust method to retrieve information is needed. In this study, the active learning method (ALM) is applied to spectral remote sensing reflectance data to retrieve in-water pigment. The heart of the ALM is a fuzzy interpolation method that is called the ink drop spread (IDS). Three datasets (SeaBAM, synthetic and NOMAD) are used for the evaluation of the selected ALM approach. Comparison of the ALM with the ocean colour 4 (OC4) algorithm and the artificial neural network (ANN) algorithm demonstrated the robustness of the ALM approach in retrieval of in-water constituents from remote sensing reflectance data. In addition, the ALM...
Article Journal of Constructional Steel Research ; Volume 83 , 2013 , Pages 147-155 ; 0143974X (ISSN) ; Bahaari, M. R ; Bagheri, V ; Ebrahimian, H ; Sharif University of Technology
Jacket-type offshore platforms play an important role in oil and gas industries in shallow and intermediate water depths such as Persian Gulf region. Such important structures need accurate considerations in analysis, design and assessment procedures. In this paper, nonlinear response of jacket-type platforms against extreme waves is examined utilizing sensitivity analyses. Results of this paper can reduce the number of random variables and consequently the computational effort in reliability analysis of jacket platforms, noticeably. Effects of foundation modeling have been neglected in majority of researches on the response of jacket platforms against wave loads. As nonlinear response of...