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Showing 1 - 18 results of 18 for search 'matrix optimization algorithm', query time: 0.07s Refine Results
  1. 1
    Optimal selection of the forgetting matrix into an iterative learning control algorithm

    Optimal selection of the forgetting matrix into an iterative learning control algorithm by Saab, Samer S.

    Published 2005
    “…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the optimal forgetting matrix and the learning gain matrix of a P-type iterative learning control (ILC) for linear discrete-time varying systems with arbitrary relative degree. …”
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  2. 2
    Neural Networks as a Convex Problem

    Neural Networks as a Convex Problem by Khalil, Baha

    Published 2016
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  3. 3
    Complexities of special matrix multiplication problems

    Complexities of special matrix multiplication problems by Takche, J.

    Published 1988
    “…This paper develops optimal algorithms to multiply an n × n symmetric tridiagonal matrix by: (i) an arbitrary n × m matrix using 2nm − m multiplications; (ii) a symmetric tridiagonal matrix using 6n − 7 multiplications; and (iii) a tridiagonal matrix using 7n −8 multiplications. …”
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  4. 4
    On the Optimization of Band Gaps in Periodic Waveguides

    On the Optimization of Band Gaps in Periodic Waveguides by Jamil Renno (14070771)

    Published 2025
    “…Five nature-inspired optimization algorithms: Genetic Algorithm (GA), Differential Evolution (DE), Grey Wolf Optimizer (GWO), Improved Grey Wolf Optimizer (IGWO), and Particle Swarm Optimization (PSO) are compared. …”
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  5. 5
    A stochastic iterative learning control algorithm with application to an induction motor

    A stochastic iterative learning control algorithm with application to an induction motor by Saab, Samer S.

    Published 2004
    “…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the learning gain matrix of a P-type ILC for linear discrete-time varying systems with arbitrary relative degree. …”
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  6. 6
    Stochastic P-type/D-type iterative learning control algorithms

    Stochastic P-type/D-type iterative learning control algorithms by Saab, Samer S.

    Published 2003
    “…The optimal algorithm is based on minimizing the trace of the input error covariance matrix. …”
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  7. 7
    On Higher-Order Iterative Learning Control Algorithm in Presence of Measurement Noise

    On Higher-Order Iterative Learning Control Algorithm in Presence of Measurement Noise by Saab, Samer S.

    Published 2005
    “…This paper addresses the optimality of HO-ILC in the sense of minimizing the control error covariance matrix in the presence of measurement noise. …”
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  8. 8
    Optimality of first-order ILC among higher order ILC

    Optimality of first-order ILC among higher order ILC by Saab, Samer S.

    Published 2006
    “…That is, an optimal HO-ILC does not add to the optimality of standard first-order ILC in the sense of minimizing the trace of the control error covariance matrix. …”
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  9. 9
    Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators

    Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators by Abu Zitar, Raed

    Published 2021
    “…The outcomes of the DNA microarray is a table/matrix, called gene expression data. Pattern recognition algorithms are widely applied to gene expression data to differentiate between health and cancerous patient samples. …”
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  10. 10
    Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images

    Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images by Ahila A (18394806)

    Published 2022
    “…The main novelty of this work is the computer-aided diagnosis scheme for detecting abnormalities in breast ultrasound images by integrating a wavelet neural network (WNN) and the grey wolf optimization (GWO) algorithm. Here, breast ultrasound (US) images are preprocessed with a sigmoid filter followed by interference-based despeckling and then by anisotropic diffusion. …”
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  11. 11
    StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features

    StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features by Muhammad Arif (769250)

    Published 2024
    “…Additionally, we applied the local interpretable model-agnostic explanations (LIME) algorithm to understand the contribution of selected features to the overall prediction. …”
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  12. 12
    Crashworthiness optimization of composite hexagonal ring system using random forest classification and artificial neural network

    Crashworthiness optimization of composite hexagonal ring system using random forest classification and artificial neural network by Monzure-Khoda Kazi (17191207)

    Published 2024
    “…These algorithms include random forest (RF) classification and artificial neural networks (ANN). …”
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  13. 13
    Bridge Structural Health Monitoring Using Mobile Sensor Networks

    Bridge Structural Health Monitoring Using Mobile Sensor Networks by Amin, Fouad

    Published 2022
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  14. 14
    Multidimensional Gains for Stochastic Approximation

    Multidimensional Gains for Stochastic Approximation by Saab, Samer S.

    Published 2019
    “…The two algorithms assume full knowledge of the Jacobian. The recursive algorithms are proposed for generating the optimal iterative-dependent matrix gain. …”
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  15. 15
    Determining Dominant Wind Directions

    Determining Dominant Wind Directions by Selim, S.Z.

    Published 2020
    “…Important properties of the problem are discussed and a convergent solution algorithm is designed. The algorithm could yield local optimal solutions. …”
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  16. 16
    A Stochastic Newton-Raphson Method with Noisy Function Measurements

    A Stochastic Newton-Raphson Method with Noisy Function Measurements by Saab, Khaled Kamal

    Published 2016
    “…The development of the proposed optimal algorithm is based on minimizing a stochastic performance index. …”
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  17. 17
    Dynamic single node failure recovery in distributed storage systems

    Dynamic single node failure recovery in distributed storage systems by Itani, M.

    Published 2017
    “…We then address three practical extensions that respectively account for newly arriving blocks, newly arriving nodes and variable priority files. A re-optimization mechanism for the storage allocation matrix is proposed for the first two extensions that can be easily implemented in real time without the need to redistribute original on-node blocks. …”
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  18. 18
    On the complexity of bilinear computations

    On the complexity of bilinear computations by Takche, Jean Halim

    Published 1984
    “…We will also consider special classes of three bilinear forms, and efficient algorithms will be developed, which are optimal in most cases.…”
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