Search Results - (( parallel estimation based algorithm ) OR ( variables selection method algorithm ))
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Cryptanalysis on the modulus N=p2q and design of rabin-like cryptosystem without decryption failure
Published 2015“…In this thesis, we also develop a new cryptographic hard problem based on a special instance of a linear Diophantine equation in two variables, with some provided restrictions and carefully selected parameters. …”
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A parallel genetic algorithm-based TSK-Fuzzy system for dynamic car-following modeling
Published 2009“…This paper presents the application of Parallel Genetic Algorithm (PGA)-based Takagi Sugeno Kang (TSK)-Fuzzy approach for dynamic car-following modeling in the traffic simulation software. …”
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New algorithm for gyroless spacecraft angular rate Estimation and its application
Published 2006“…A new algorithm for estimating the angular velocity using quaternion measurements is developed based on the concept of the global optimality resulting when using a centralized or master Kalman filter. …”
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Taguchi?s T-method with Normalization-Based Binary Bat Algorithm
Published 2025Subjects:Conference paper -
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A bit-serial sum of absolute difference accelerator for variable block size motion estimation of H.264
Published 2009“…In this paper, we propose the first least significant bit (LSB) bit-serial sum of absolute difference (SAD) hardware accelerator for integer variable block size motion estimation (VBSME) of H.264. This hardware accelerator is based on a previous state-of-art bit-parallel architecture namely propagate partial SAD. …”
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Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers
Published 2016“…To overcome the instability selection problem, a stability selection approach is put forward to enhance the performance of single-split variable selection method. …”
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Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique
Published 2015“…There are many types of motion estimation method but the most used method is the block matching method which is the fixed block matching and the variable block matching. …”
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Enhancing Model Selection Based On Penalized Regression Methods And Empirical Mode Decomposition
Published 2021“…The penalized regularization methods are statistical techniques used to regularize and select the necessary predictor variables that have substantial effects on the response variable. …”
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Resource Minimization in a Real-time Depth-map Processing System on FPGA
Published 2011“…Depth-map algorithm allows camera system to estimate depth. It is a computational intensive algorithm, but can be implemented with high speed on hardware due to the parallelism property. …”
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Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification
Published 2011“…Evolutionary computation (EC) is known to be an effective search and optimization method and in this paper EC is proposed as a model structure selection algorithm. …”
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New selection algorithm for Mengubah Destini Anak Bangsa (MDAB) students / Zamali Tarmudi ... [et al.]
Published 2014“…This research introduces a new algorithm to select students from low income family the so-called Mengubah Destini Anak Bangsa (MDAB) using fuzzy approach. …”
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Characteristic wavelength optimization for partial least squares regression using improved flower pollination algorithm
Published 2023“…This study proposes a new wavelength selection method, interval flower pollination algorithm (iFPA), for spectral variable selection in the partial least squares regression (PLSR) model. …”
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Conjunctions in biological neural architectures for visual pose estimation / Tom´As Maul
Published 2006“…A highly parallel approach based on simple inter-map conjunctions, or correspondence distributions, is chosen and tested on synthetic and real patterns. …”
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Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…Sure screening-based correlation methods are popular tools used to select the most significant variables in the true model in sparse and high dimensional analysis. …”
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Sure (EM)-Autometrics: An Automated Model Selection Procedure with Expectation Maximization Algorithm Estimation Method (S/O 14925)
Published 2021“…Hence, this study concentrates on an automated model selection procedure for the SURE model by integrating the expectation-maximization (EM) algorithm estimation method, named SURE(EM)-Autometrics. …”
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Penalized Quantile Regression Methods And Empirical Mode Decomposition For Improving The Accuracy Of The Model Selection
Published 2024“…Moreover, selecting the relevant variables when fitting the regression model is critical. …”
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Feature selection methods for optimizing clinicopathologic input variables in oral cancer prognosis
Published 2011“…However, due to time, cost and tissue limitations, the number of prognosis variables need to be reduced. In this research, we demonstrated the use of feature selection methods to select a subset of variables that is highly predictive of oral cancer prognosis. …”
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