Search Results - (( model estimation _ algorithm ) OR ( rate estimation based algorithm ))
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Evaluation of a spacecraft attitude and rate estimation algorithm
Published 2010“…Purpose: This paper aims to present the development and performance evaluation of an attitude and rate estimation algorithm using an extended Kalman filter structure based on a body‐referenced representation of the state. …”
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Robust remote heart rate estimation from multiple asynchronous noisy channels using autoregressive model with Kalman filter
Published 2019“…We propose a novel algorithm to estimate heart rate. Also, it can differentiate between a photo of a human face and an actual human face meaning that it can detect false signals and skip them. …”
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Performance of MIMO space-time coded system and training based channel estimation for MIMO-OFDM system
Published 2006“…Firstly it has investigated the performance of MIMO-STBC system and surveyed the effect of imperfect channel estimation on performance of MIMO-OFDM system. Secondly, it has focused on training based channel estimation algorithm for MIMO-OFDM system. …”
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Thesis -
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Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data
Published 2011“…In this thesis, we considered two methods via the expectation maximization (EM) algorithm for cure rate estimation based on the BCH model using the two censoring types common to cancer clinical trials; namely, right and interval censoring. …”
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Analysis of multiexponential transient signals using interpolation-based deconvolution and parametric modeling techniques
Published 2003“…Direct deconvolution approach often leads to poor resolution of ihe estimated decay rates since the fast Fourier transform (FFT) algorithm is used to analyze the resulting deconvolved data. …”
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Proceeding Paper -
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Optimal neural network approach for estimating state of energy of lithium-ion battery using heuristic optimization techniques
Published 2023Conference Paper -
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ADAPTIVE MODULATION AND CODING FOR WIMAX SYSTEMS
Published 2006“…First the SNR estimation using the three algorithms is implemented in Wimax system, based on the transmission protocols specified in Wimax. …”
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Final Year Project -
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Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm
Published 2019“…In conclusion, SURE(IFGLS)-Autometrics and SURE(EM)-Autometrics can be used as models selection algorithms. Additionally, both algorithms are suitable in improving performance of automated models selection procedures. …”
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Spacecraft sun-pointing using coplanar solar panels data and magnetic field measurements
Published 2013“…Another estimator also has been introduced by combining the two uncoupled sub-estimators into one estimator for attitude, rate, and sun vector estimation. …”
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Proceeding Paper -
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Stochastic optimal control of economic growth model under research and development investment with Kalman filtering approaches
Published 2022“…With these state estimates, two different computational algorithms are proposed, the EKF for state-control (EKF4SC) and UKF for state-control (UKF4SC) algorithms. …”
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Image-based air quality estimation using convolutional neural network optimized by genetic algorithms: A multi-dataset approach
Published 2025“…These improvements underscore the effectiveness of Genetic Algorithms in optimizing the model.…”
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Fractional chaotic ensemble particle swarm optimizer for identifying the single, double, and three diode photovoltaic models� parameters
Published 2023“…Heuristic algorithms; Particle swarm optimization (PSO); Photovoltaic cells; Renewable energy resources; Solar power generation; Commercial applications; Environmental conditions; Fast convergence rate; Meta heuristic algorithm; Optimization algorithms; Parameters estimation; Particle swarm optimizers; PV models; Diodes; algorithm; alternative energy; electrode; model; optimization; parameter estimation; photovoltaic system; temperature effect…”
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A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model
Published 2023“…Algorithms; Diodes; Errors; Iterative methods; Least squares approximations; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Coefficient of determination; Differential Evolution; Electromagnetism-like algorithm; Hybrid evolutionary algorithm; Photovoltaic; Photovoltaic modules; Root mean square errors; Single-diode models; Evolutionary algorithms; algorithm; comparative study; electromagnetic method; estimation method; experimental design; numerical method; parameterization; performance assessment; photovoltaic system…”
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Turnbull versus Kaplan-Meier estimators of cure rate estimation using interval censored data
Published 2012“…A comparison of the cure rate estimation based on the two estimators was done through a simulation study.…”
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Ant colony optimization and genetic algorithm models for suspended sediment discharge estimation for gorgan-river, Iran
Published 2011“…Different input combinations of ACO and GA models (i.e. ACO1 and GA1: the suspended sediment estimation based on current discharge; ACO2 and GA2: the estimation of suspended sediment based on current and one day of previous discharges; and ACO3 and GA3: the suspended sediment estimation based on current, one and two-day of previous discharges) were chosen based on similar meteorological requirements to those of the suspended sediment equations included in this study. …”
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Thesis -
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End-to-end DVB-S2X system design with deep learning-based channel estimation over satellite fading channels
Published 2021“…In the fourth part a deep learning (DL) algorithm of channel estimation for two fad�ing channel models, Tropical and Temperate in the satellite communication system is presented. …”
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Development of a hybrid PSO-ANN model for estimating glucose and xylose yields for microwave-assisted pretreatment and the enzymatic hydrolysis of lignocellulosic biomass
Published 2018“…The PSO algorithm suggested an optimum number of neurons in the hidden layer as 15 and a learning rate of 0.761 these consequently used to construct the ANN model. …”
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