robust model based methods
Robust direct position determination methods in the presence of array model errors
... location methods, the direct position determination (DPD) technique has been proposed and extensively ...two-step methods, but estimates the source location directly, skipping the intermediate (first) ...
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The TSR-MM Based on Robust Location and Scales Measures in Dual Response Optimization in the Presence of Outliers and Heteroscedastic Errors
... OLS model is known to be not reliable in the presence of outliers, it is not included in the ...TSR-MM based methods were considered as decision criteria to judge the per- formance of the ...
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A Robust and Efficient Evolutionary Algorithm based on Probabilistic Model
... learning methods to extract relevant features of the search space through the selected individuals of the ...probabilistic model can provide explicit information about the interactions among the variables ...
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A Review on Neural Network based Noise Robust Speech Recognition Methods
... realized model is highly capable of suppressing the non- stationary ...The model can effectively work in real world environments where speech data is intensely contaminated by noisy ...a model ...
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Robust Parameter Estimation for Fixed Effect Panel Data Model in the Presence of Heteroscedasticity and High Leverage Points by Robust Method
... three robust weighting methods based on HLPs detection measures were used for robust HCCM estimator in FE panel data regression ...cient robust weighting technique is used in or- der to ...
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Robust Methods for Estimating Allele Frequencies
... is robust under different mutation ...mutation model, the whole procedure of predicting allele frequencies is not restricted to any specific mutation ...analysis based on the expected values among ...
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Methods in robust and adaptive control
... signal model order, in some situation, is not an easy ...signal model to be on the "safe" side, that is to choose the order higher than it ...Furthermore, based on those estimates of the ...
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Robust design for the lower extremity exoskeleton under a stochastic terrain by mimicking wolf pack behaviors
... existing methods (namely, direct and inverse kinematics) have their ...a robust design method using artificial intelligence and applies it to the lower extremity exoskeleton design under a stochastic ...
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Robust Design for MEMS Sensors Based on the Fuzzy Model
... put robust design ideas into the design of MEMS micro ...the robust design of MEMS sensor general principles and ...The robust design theory and the modeling method of MEMS sensors which based ...
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Robust Model Based Data Management
... Privacy preserving profile matching protocols, without relying on a client-server relationship nor any central server. We propose novel methods to reduce energy consumption and protocol run time, while achieving ...
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Learning a Robust Relevance Model for Search Using Kernel Methods
... BM25 was selected as a baseline, whose parameters were tuned by using the validation set. Query expansion (Xu and Croft, 1996) was also chosen as a baseline. Query expansion is a state-of-the-art technique to tackle term ...
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Case Mix Planning using The Technique for Order of Preference by Similarity to Ideal Solution and Robust Estimation: a Case Study
... LP model is developed to find the optimum case mix of the ...defined based on the data collected from Shahid Madani ...the model were estimated using the data collected from Shahid Madani ...a ...
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Alternative Tools of Statistical Analysis: L-moments and TL-moments of Probability Distributions
... Abstract: Moments and cumulants are commonly used to characterize the probability distribution or observed data set. The use of the moment method of parameter estimation is also common in the construction of an ...
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Robust Classification of Primary Brain Tumor in MRI Images Based on Multi Model Textures Features and Kernel Based SVM
... (MRF) based multivariate segmentation algorithm called “multivariate iterative region growing using semantics” (MIRGS) has been proposed by Shan Shen 13 ...
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A note on detecting statistical outliers in psychophysical data
... below the main body of data (imagine, for example, if a test of color discrimination was applied to a broad population of people, including both dichromats and tetrachromats, who would be expected to score systematically ...
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Robust Digital Watermarking for Compressed 3D Models based on Polygonal Representation
... This paper introduces a methodology of robust digital watermarking based on a wellknown spherical wavelet transformation, applied to 3D compressed model based on polygonal representation[r] ...
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Download Download PDF
... The result from the SYSTEM GMM analysis shows that higher education could be more important for growth in the SSA countries than investment in physical capital and other levels of education. The result from higher ...
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An analysis of the missing data methodology for different types of data : a thesis presented in partial fulfilment of the requirements for the degree of Master of Applied Statistics at Massey University
... Using model based methods for imputation is far superior for other types of data.. Model based methods for Likert data are achieved by means of inserting the linear by linear association[r] ...
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Ontology based semantic predictive model for reconfigurable automation systems
... semantic model, the information is logically extracted and ...3D based virtual modelling tools in order to improve the system design and reconfiguration ...
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1. Pso and surf algorithm for copy-move forgery detection
... In this study, a novel detection of copy moves forgery algorithm based on SURF and PSO is proposed. The method generates suitable parameter values for each test image to detect copy move forgeries. The higher ...
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