Search Results - (( using input based algorithm ) OR ( parameter estimation method algorithm ))
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MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD
Published 2017“…In this research. novel algorithms have been developed to: (I) isolate the less interacting channe Is using a modified partial correlation algorithm. (2) achieve unbiased and consistent parameter estimates using an iterative LLMS algorithm and (3) develop parsimonious models for closed-loop MIMO systems. …”
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PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah
Published 2017“…Typically, parameter estimation is performed using various types of Least Squares (LS) algorithms due to its stable and efficient numerical computation. …”
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Orthogonal least square algorithm and its application for modelling suspension system
Published 2001“…One of the issues in system identification is the parameter estimation and model structure selection where various methods have been studied including the orthogonal least square algorithm. …”
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Simultaneous Computation of Model Order and Parameter Estimation for System Identification Based on Gravitational Search Algorithm
Published 2015“…In this paper, a technique termed as Simultaneous Model Order and Parameter Estimation (SMOPE), which is specifically based on Gravitational Search Algorithm (GSA) is proposed to combine model order selection and parameter estimation in one process. …”
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Railway wheelset parameter estimation using signals from lateral velocity sensor
Published 2008“…A type of parameter estimation technique based on the linear integral filter (LIF) method, the least-absolute error with variable forgetting factor (LAE+VFF) estimation method, is proposed in this paper to estimate the railway wheelset parameters modelled as a time-varying continuous-time (C-T) system. …”
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A COMPARATIVE PERFORMANCE EVALUATION OF NEURAL NETWORK ALGORITHMS BASED STATE OF CHARGE ESTIMATION FOR LITHIUM-ION BATTERY
Published 2023“…Therefore, neural network algorithms based SOC estimation have received huge attention since they have the adaptively to adjust the network parameters automatically without battery model. …”
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Simultaneous Computation of Model Order and Parameter Estimation of a Heating System Based on Gravitational Search Algorithm for Autoregressive with Exogenous Inputs
Published 2015“…The next stage is to estimate the parameters of the model and finally, the mathematical model is validated. …”
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Identification of continuous-time hammerstein system using sine cosine algorithm
Published 2019“…The SCA based method is then used to estimate the parameters in both the linear and nonlinear parts based on the given input and output data. …”
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SLOW DRIFT MOTIONS IDENTIFICATION OF FLOATING STRUCTURES USING TIME-VARYING INPUT -OUTPUT MODELS
Published 2015“…Three steps of improvements had been made to increase the modeling capacity of input-output models. The first step is presenting the backward estimator and combined forward-backward estimator instead of the only forward estimator in the original input-output models; the second step is reformulating the input-output models into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the model coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Artificial Bee Colony (ABC) to form the PSO-KS, GA-KS and ABC-KS as estimation methods.…”
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Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques
Published 2003“…In this method of analysis the exponential signal is converted to a convolution model whose input is a train of weighted delta function that contains the signal parameters to be determined.The resolution of the estimated decay rates is poor if the conventional fast Fourier transform (FFT) algorithm is used to analyse the resulting deconvolved data. …”
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Identification of hammerstain model using stochastic perturbation simultaneous approximation
Published 2016“…The SPSA based method is then used to estimate the parameters in both the linear and non-linear parts based on the given input and output data with the present of delay in time. …”
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Enhanced location and positioning in wimax networks with virtual mimo base station
Published 2015“…Furthermore, a new hybrid algorithm enhancement of mobile station (MS) location estimation by using a single MIMO base station (SMBS) with the virtual base station has been introduced. …”
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Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River
Published 2025“…The estimation of SL values was achieved using inputs of previous SL and streamflow values provided to the models. …”
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Position control of robot manipulator: Design a novel SISO adaptive sliding mode fuzzy PD fuzzy sliding mode control.
Published 2011“…This research focuses on design Single Input Single Output (SISO) adaptive sliding mode fuzzy PD fuzzy sliding mode algorithm with estimates the equivalent part derived in the Lyapunov sense. …”
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Simultaneous computation of model order and parameter estimation for system identification based on opposition-based simulated Kalman filter
Published 2018“…Simultaneous Model Order and Parameter Estimation (SMOPE) has been proposed to address system identification problem efficiently using optimization algorithms. …”
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Restoration of blurred images using geometric and chebichef moments / Ahlad Kumar
Published 2016“…Once the blur parameters are estimated, image restoration of the proposed method is carried out using split Bregman algorithm. …”
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…The mMVO based method is then used for identifying the parameters of linear and nonlinear subsystems in the Hammerstein model using the given input and output data. …”
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Reference evapotranspiration estimation using adaptive neuro-fuzzy inference system
Published 2011“…In addition, traditional methods that require limited climatic parameters for ETO estimation are not applicable to all climatic conditions. …”
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