Search Results - (( parameters variation case algorithm ) OR ( parallel estimation method algorithm ))
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Parallel visualization approach of a 3D heart model
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Digital quadrature compensators scheme for analog imperfections of quadrature modulator in wireless communication systems
Published 2016“…Offline on the other hand, is a mode where adaptive algorithms cannot estimate the imperfections in parallel with the transmission. …”
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3
Backstepping Integral Super Twisting Sliding Mode Control Algorithm For Autonomous Underwater Glider
Published 2019“…The BISTSMC was tested for external disturbance and parameter variations. The BISTSMC has been benchmarked its performances with other sliding mode control (SMC) strategies to evaluate the chattering suppression of the controllers. …”
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4
The effect of key parameters on the design of an optimized CAES power plant
Published 2017“…In order to obtain a more tangible realization, it is necessary to verify the results against the variation of key parameters. In this study, the sensitivity analysis is performed based on main parameters including plant loading and ambient condition and the resultant trends of each case are presented. …”
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Algorithm optimization and low cost bit-serial architecture design for integer-pixel and sub-pixel motion estimation in H.264/AVC / Mohammad Reza Hosseiny Fatemi
Published 2012“…This thesis is concerned with algorithm optimization and efficient low cost architecture design for integer motion estimation (IME) and sub-pixel motion estimation (SME) of H.264/AVC. …”
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6
Early detection of breast cancer using wave elliptic equation with high performance computing
Published 2008“…This paper focuses on the implementation of parallel algorithm for the simulation of breast cancer tumor using two dimensional Helmholtz’s wave equation on a distributed parallel computer system (DPCS). …”
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Development of controller for an underactuated autonomous underwater vehicle (AUV)
Published 2019“…The simulation results have shown that the proposed controller provides the smallest chattering about more than 1000 times smaller than STSMC, more than 100 times smaller than back-stepping SMC in nominal, disturbance and parameter variation cases respectively. The steady error of the proposed controller also gives the smallest steady state error of four times smaller than STSMC and back-stepping SMC in all cases for pitching angle and 100 times smaller than STSMC and back-stepping for excess mass. …”
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Scheduling dynamic cellular manufacturing systems in the presence of cost uncertainty using heuristic method
Published 2016“…It is observed that in 67% of studied cases, inflation rate can strengthen cell load variation. …”
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9
Extreme air pollutant data analysis using classical and Bayesian approaches
Published 2015“…MTM algorithm is an extension of MH algorithm, designed to improve the convergence of MH algorithm by performing parallel computation. …”
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10
Image reconstruction using iterative transpose algorithm for optical tomography
Published 2007“…This paper describes a transpose algorithm for use with an optical tomography system. …”
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Development of optimization Alghorithm for uncertain non-linear dynamical system
Published 2004“…An algorithm that definitely can satisfy the objectives is the Dynamic Integrated Systems Optimization and Parameter Estimation (DISOPE) algorithm. …”
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Variational Bayesian inference for exponentiated Weibull right censored survival data
Published 2023“…The results from the experiments reveal that the Variational Bayesian (VB) approach is better than the competing Metropolis-Hasting Algorithm and the reference maximum likelihood estimates.…”
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Iterative methods for solving split common fixed point problems in Hilbert spaces
Published 2016“…In other words, we construct parallel and cyclic algorithms for solving the split common fixed point problems for strictly pseudocontractive mappings and prove the convergence results of these algorithms. …”
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Optimisation of fed-batch fermentation process using deep reinforcement learning
Published 2023“…When dealing with model mismatch (±15% parameter variation in critical growth and maximum glucose uptake rate) and process disturbance (±20% deviation in substrate feeding concentration), the proposed algorithm was able to handle the changes with a minor effect on the yeast yield up to 13.78% and 2.52%, respectively, across all different initial condition cases. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…Given the multitude of components to manage, streamflow forecasting is preferable to employ an algorithm with low sensitivity to parameter variations. …”
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