Search Results - (( square estimation method algorithm ) OR ( using classification using algorithm ))

Scene illumination classification based on histogram quartering of CIE-Y component by Hesamian, Mohammad Hesam

“…Those algorithms which performed estimation carrying out lots of calculation that leads in expensive methods in terms of computing resources. …”
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Fingerprint classification : a BI-resolution approach to singular point extraction by Leong, Chung Ern

“…Since the fingerprint is not segmented apriori, the algorithm makes use of the strength of the directional image as region of interest. …”
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Modified anfis architecture with less computational complexities for classification problems by Talpur, Noureen

“…Furthermore, researchers have mainly used metaheuristic algorithms to avoid the problem of local minima in standard learning method. …”
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Heart sound diagnosis using nonlinear ARX model / Noraishah Shamsuddin by Shamsuddin, Noraishah

“…The Resilient Backpropagation (RPROP) algorithm is used to train the network. The optimized learning parameter used is 0.07 and the network has best performance when hidden neurons equal to 220. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…In addition, the hyperparameter tuning problem is considered in this research to improve the developed hybrid model by using the AOA algorithm. Lastly, a new hybrid technique suggests tackling the current image encryption application problem by using the estimated parameters of chaotic systems with an optimization algorithm, the SKF algorithm. …”
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Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition by Burhan, Nuradebah

“…Electromyography (EMG) signal is a biomedical signal which measures physical activity of human muscle.It has been acknowledged to be widely used in rehabilitation or recovery application system assisting physiotherapist to monitor a patient’s physical strength,function,motion and overall well-being by addressing the underlying physical issues.In application system associated with rehabilitation,a signal processing and classification techniques are implemented to classify EMG signal obtained.For real time application in the rehabilitation, the classification is crucial issue.The success of the signal classification depends on the selection of the features that represent a raw EMG signal in the signal processing.Therefore,a robust and resilient denoising method and spectral estimation technique have been acknowledged as necessary to distinguish and detect the EMG pattern.The present study was undertaken to determine the characteristic of EMG features using denoising method and spectral estimation technique for assessing the EMG pattern based on a supervised classification algorithm.In the study,the combination of time-frequency domain (TFD) and time domain (TD) were identified as the preferred denoising method and spectral estimation techniques.In the first part of study, the recorded EMG signal filtered the contaminated noise by using wavelet transform (WT) approach which implemented discrete wavelet transform (DWT) method of the wavelet-denoising signal. …”
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Heart sound diagnosis using nonlinear arx model / Noraishah Shamsuddin by Shamsuddin, Noraishah

“…This thesis presents a research work on a diagnosis system for heart sound based on nonlinear ARX (NARX) model. The system uses neural network for model estimation and classification of several heart diseases. …”
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Benthic habitat mapping and coral bleaching detection using quickbird imagery and Kd algorithm by Kabiri, Keivan

“…Half numbers of these points were selected to determine the mentioned parameters using minimizing the sum of the squared residuals, and the other points were used for accuracy assessment of the applied method. …”
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Robust techniques for linear regression with multicollinearity and outliers by Mohammed, Mohammed Abdulhussein

“…The proposed method is formulated by incorporating robust MM-estimator and the modified generalized M-estimator (MGM) in the LRR algorithm. …”
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Generating an adaptive and robust walking pattern for prosthetic ankle-foot utilizing a nonlinear autoregressive network with exogenous inputs / Hamza Al Kouzbary by Hamza, Al Kouzbary

“…The trained NARX RNN estimated the foot orientation of all subjects at different walking speeds over a flat terrain with an average root mean square error of 2.1°±1.7°. …”
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Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui by Muhammad Faisal , Siddiqui

“…The use of eigenvectors decomposition (E-maps) and pre-scan methods for estimating sensitivity maps are also investigated. …”
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PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah by Abdullah, Siti Muniroh

“…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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Hybrid indoor positioning utilizing multipath- assisted fingerprint and geometric estimation for single base station systems by Manap, Zahariah

“…The methodological framework of the proposed method comprises two main phases which are fingerprinting phase and position estimation phase. …”
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A Computationally Efficient Least Square Channel Estimation Method for MIMO-OFDM Systems by Ahmad, Hasan, Motakabber, S. M. A., Anwar, Farhat, Habaebi, Mohamed Hadi, Ibrahimy, Muhammad Ibn

“…Some of the most popular methods used in cellular communication for channel estimation are the Least Squares (LS) algorithm and the Minimum Mean Square Error (MMSE) algorithm. …”
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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 by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

“…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…”

MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD by MOHAMED OSMAN, MOHAMED ABDELRAHIM

“…Channel isolation usmg partial correlation analysis and estimation of model parameters in the conventional multivariable closed-loop system identification approaches use the method of Least Square (LS) with the limitations, viz. …”
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Model selection approaches of water quality index data by Kamarudin, Nur Azulia, Ismail, Suzilah

“…In order to select the best model, it is vital to ensure that proper estimation method is chosen in the modelling process.Different estimators have been proposed for the estimation of parameters of a model, including the least square and iterative estimators.This study aims to evaluate the forecasting performances of two algorithms on water quality index (WQI) of a river in Malaysia based on root mean square error (RMSE) and geometric root mean square error (GRMSE).Feasible generalised least squares (FGLS) and iterative maximum likelihood (ML) estimation methods are used in the algorithms, respectively.The results showed that SUREMLE-Autometrics has surpassed SURE-Autometrics; another simultaneous selection procedure of multipleequation models.Two individual selections, namely Autometrics-SUREMLE and Autometrics-SURE, though showed consistency only for GRMSE.All in all, ML estimation is a more appropriate method to be employed in this seemingly unrelated regression equations (SURE) model selection.…”
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Orthogonal least square algorithm and its application for modelling suspension system by Ahmad, Robiah, Jamaluddin, Hishamuddin

“…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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Multiple equations model selection algorithm with iterative estimation method by Kamarudin, Nur Azulia, Ismail, Suzilah

“…This estimation method is equivalent to maximum likelihood estimation at convergence. …”
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Machine learning approach for tenaga nasional berhad (tnb) overhead powerline and electricity pole inventory using mobile laser scanning data by Mohd Rapheal M.S.A., Farhana A., Mohd Salleh M.R., Abd Rahman M.Z., Majid Z., Musliman I.A., Abdullah A.F., Abd Latif Z.