Search Results - (( variable extractions method algorithm ) OR ( time estimation means algorithm ))

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  1. 1

    Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui by Muhammad Faisal , Siddiqui

    Published 2016
    “…The use of eigenvectors decomposition (E-maps) and pre-scan methods for estimating sensitivity maps are also investigated. …”
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    Thesis
  2. 2

    Detection and Classification of Moving Objects for an Automated Surveillance System by Md. Tomari, Mohd Razali

    Published 2006
    “…Finally, classification algorithm that makes use of the extracted moment values from the detected objects successfully categorize objects into pre-defined classes of human and vehicle with 89.08% of accuracy. …”
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    Thesis
  3. 3

    Detection and classification of moving objects for an automated surveillance system by Md Tomari, Mohd Razali

    Published 2006
    “…Finally, classification algorithm that makes use of the extracted moment values from the detected objects successfully categorize objects into pre-defined classes of human and vehicle with 89.08% of accuracy. …”
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    Thesis
  4. 4

    Detection and classification of moving objects for an automated surveillance system by Md Tomari, Mohd Razali

    Published 2006
    “…Finally, classification algorithm that makes use of the extracted moment values from the detected objects successfully categorize objects into pre-defined classes of human and vehicle with 89.08% of accuracy. …”
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    Thesis
  5. 5

    Perturbation stochastic model updating of a bolted structure / Mohamad Azam Shah Aziz Shah by Aziz Shah, Mohamad Azam Shah

    Published 2022
    “…For the latter, the bolted structure was reassembled 100 times to evaluate the variability of the dynamic behaviour of the structure. …”
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    Thesis
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    LASSO-type estimations for threshold autoregressive and heteroscedastic time series models. by Muhammad Jaffri Mohd Nasir

    Published 2020
    “…In this thesis, we propose Least Absolute Shrinkage and Selection Operator (LASSO) type estimators to perform simultaneous parameter estimation and model selection for five specific univariate and multivariate time series models, and develop several algorithms to compute these estimators. …”
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    UMK Etheses
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    Severity Estimation of Plant Leaf Diseases Using Segmentation Method by Chyntia Jaby, Entuni, Tengku Mohd Afendi, Zulcaffle, Kuryati, Kipli, Fatih, Kurugollu

    Published 2020
    “…The best severity estimation algorithm and color space used to estimate the diseases severity of plant leaf is the combination of Fuzzy C-Means and YCbCr color space. …”
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    Article
  10. 10

    On time-domain OFDM channel estimation: Use of pilots correlation for digital video broadcasting (DVB) cable receiver by Khan, A.M., Jeoti, V.

    Published 2015
    “…In this paper, an improved OFDM time domain channel estimation algorithm is proposed for (DVB) Cable receivers. …”
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    Article
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  12. 12

    Reduced-rank technique for joint channel estimation in TD-SCDMA systems. by Ismail, Alyani, Sali, Aduwati, Mohd Ali, Borhanuddin, Khatun, Sabira

    Published 2013
    “…The adopted reduced rank technique is based on singular value decomposition algorithm. Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. …”
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    Article
  13. 13

    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

    Published 2011
    “…In the first sub-algorithm, the state mean propagation removes the Gaussian white noise to obtain the expected solution. …”
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    Thesis
  14. 14

    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

    Published 2013
    “…The adopted reduced rank technique is based on singular value decomposition algorithm. Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. …”
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    Article
  15. 15

    Modified artificial neural network (ANN) models for Malaysian construction costs indices (MCCI) data / Saadi Ahmad Kamaruddin by Ahmad Kamaruddin, Saadi

    Published 2018
    “…Theoretically, the most common algorithm to train the network is the backpropagation (BP) algorithm which is based on the minimization of the ordinary least squares (LS) estimator in terms of mean squared error (MSE). …”
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    Book Section
  16. 16

    Performance of MIMO space-time coded system and training based channel estimation for MIMO-OFDM system by Abdolee, Reza

    Published 2006
    “…At the next stage of the project, the effect of channel estimation algorithm on performance of MIMO-OFDM system was investigated. …”
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    Thesis
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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

    Published 2012
    “…The adopted reduced rank technique is based on singular value decomposition algorithm. Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. …”
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    Article
  19. 19

    Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network by Mohamad Afiq, Mohd Asrul

    Published 2023
    “…Model validity describes the first sub-objective, which is to solve the complexity of the nonlinear interaction of multiple MEC input variables related to the hydrogen production rate response using artificial neural networks (ANN) before validating the mathematical modeling results by comparing experimental data with the predicted substrate concentration profile and hydrogen production rate profile based on the re-estimated input values of the model parameters using single-objective optimization based on the nonlinear convex method using gradient descent algorithm. …”
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    Thesis
  20. 20

    Segmentation of MRI brain images using statistical approaches by Balafar, Mohammad Ali

    Published 2011
    “…The non-Local means (NL-means) algorithm is a state-of-the art neighbourhood-based noisereduction method which is time-consuming and its accuracy can be improved. …”
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    Thesis