Search Results - (( _ normalization based algorithm ) OR ( parameter estimation method algorithm ))

Dynamic robust bootstrap method based on LTS estimators by Midi, Habshah, Uraibi, Hassan Sami, Al-Talib, Bashar Abdul Aziz Majeed

“…We call this method Dynamic Robust Bootstrap-LTS based (DRBLTS) because here we have employed the LTS estimator in the modified bootstrap algorithm. …”
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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

“…The Ordinary Least Squares (OLS) method is often used to estimate the parameters of a linear model. …”
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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

“…Results suggest that the PSO algorithm is viable alternative to other established algorithms for LLS parameter estimation. …”
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ADAPTIVE LINEAR ALGORITHMS FOR POWER SYSTEM FUNDAMENTAL AND HARMONIC ESTIMATION by MUBARAK MOHMMED, HUSSAM ALHAJ

“…Hence, one of the objectives of this thesis is to address and enhance the introduced fundamental frequency adaptive filter method which was based on modified variable step size LMS (MVSS) algorithm using generalized square error normalized LMS algorithm. …”
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Reduced-rank technique for joint channel estimation in TD-SCDMA systems. by Ismail, Alyani, Sali, Aduwati, Mohd Ali, Borhanuddin, Khatun, Sabira

“…We exploit the rank deficient of H to reduce the number of parameters that characterizes this matrix. The adopted reduced rank technique is based on singular value decomposition algorithm. …”
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Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems by Marzook, Ali Kamil, Ismail, Alyani, Mohd Ali, Borhanuddin, Sali, Aduwati, Khalaf, Mohannad H., Khatun, Sabira

“…We exploit the rank deficient of H to reduce the number of parameters that characterizes this matrix. The adopted reduced rank technique is based on singular value decomposition algorithm. …”
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Reduced Rank Technique for Joint Channel Estimation and Joint Data Detection in TD-SCDMA Systems by Sabira, Khatun, Ali K., Marzook, Alyani, Ismail, Aduwati, Sali, Mohannad Hamed, Khalaf, Borhan, M. Ali

“…We exploit the rank deficient of H to reduce the number of parameters that characterizes this matrix. The adopted reduced rank technique is based on singular value decomposition algorithm. …”
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Modified least trimmed squares method for face recognition / Nur Azimah Abdul Rahim by Abdul Rahim, Nur Azimah

“…The genetic algorithm configuration for n (number of observations) and p (parameter) was changed to assess the performance of modified method. …”
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

“…Firstly, an improved EM (IEM) algorithm is presented to estimate the five parameters of the single PV-module system. …”
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Particle filter approach for tracking indoor user location using IEEE 802.11 signals by Mantoro, Teddy, Ayu, Media Anugerah, Raman, Shakiratul Husna, Latiff , N. H. M.

“…Moreover, the use of light estimation algorithms such as fingerprinting, ranking algorithm, Weighted Centroid method, k-Nearest Neighbour, did not give a good tracking result. …”
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Particle filter approach for estimating indoor mobile user location using IEEE 802.11 signals (F1090) by Mantoro, Teddy, Ayu, Media Anugerah, Raman, Shakiratul Husna, Md. Latiff , Nurul Hidayati

“…Moreover, the use of light estimation algorithms such as fingerprinting, ranking algorithm, Weighted Centroid method, k-Nearest Neighbour, did not give a good tracking result. …”
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Application of Evolutionary Algorithm for Assisted History Matching by Zahari, Muhammad Izzat

“…Today, tremendous efforts are made to develop Automatic History Matching algorithms. While the automatic method focus on optimization which is normally computer based. …”
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Fraud detection in telecommunication using pattern recognition method / Mohd Izhan Mohd Yusoff by Mohd Yusoff, Mohd Izhan

“…Due to the complexity of GMM, we use Expectation Maximization (or EM) algorithm by Dempster et al. (1977) to obtain the maximum likelihood estimates of the GMM parameters. …”
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Rank-based inference for the accelerated failure time model in the presence of interval censored data by Karimi, Mostafa, Ibrahim, Noor Akma, Abu Bakar, Mohd Rizam, Arasan, Jayanthi

“…In this paper a class of asymptotically normal rank estimators is developed which can be aquired via linear programming for estimating the parameters of the model, and a two-step iterative algorithm is introduce for solving the estimating equations. …”
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Estimating Crack Effects on Electrical Characteristics of PV Modules Based on Monitoring Data and I-V Curves by Feng L., Zhang J., Kiong T.S., Ding K., Amin N., Hamelmann F.U.

“…Meanwhile, an innovative parameter optimization algorithm based on particle swarm optimization is developed to extract the parameters. …”

A new hybrid multiaxial fatigue life model based on critical plane continuum damage mechanics and genetic algorithm by Masood, Kamal

“…Material parameter including stress sensitivity factor for normal or shear stress can be incorporated to improve the calibration process. …”
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The largest studentized residual test for bad data identification in state estimation of a power system by Khan, Z., Razali, R.B., Daud, H., Nor, N.M., Firuzabad, M.F.

“…The presence of systematic errors can alter the results of state estimation. The chi-square and normalized residual tests are the common post estimation procedures usually used for detection and identification of gross errors in the estimation algorithm. …”
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Interpolation and extrapolation techniques based Neural Network in estimating the missing ionospheric TEC data by Jayapal V., Zain A.F.M.

“…A multilayer feed-forward network with a back propagation algorithm is applied to estimate the TEC over Parit Raja (Lat. 1�52?…”

Interpolation and Extrapolation Techniques Based Neural Network in Estimating the Missing Ionospheric TEC Data by Jayapal, V, Zain, AFM

Robust estimation methods for fixed effect panel data model having block-concentrated outliers by Abu Bakar @ Harun, Nor Mazlina

“…The Ordinary Least Squares (OLS) is the commonly used method to estimate the parameters of fixed effect panel data model. …”
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