Selection of the learning gain matrix of an iterative learning control algorithm in presence of measurement noise by Saab, Samer S.

“…This work also provides a recursive algorithm that generates the appropriate learning gain functions that meet the arbitrary high precision output tracking objective. …”
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Optimal selection of the forgetting matrix into an iterative learning control algorithm by Saab, Samer S.

“…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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A kernelization algorithm for d-Hitting Set by Abu-Khzam, Faisal N.

“…In this paper, a kernelization algorithm for the 3-Hitting Set problem is presented along with a general kernelization for d -Hitting Set. …”
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A method for the minimum coloring problem using genetic algorithms by Harmanani, Haidar

“…The algorithm was implemented and tested on various set of instances including large DIMACS challenge benchmark graphs, all yielding favorable results.…”
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An improved kernelization algorithm for r-Set Packing by Abu-Khzam, Faisal N.

“…Such parameterized reductions are known as kernelization algorithms, and a reduced instance is called a problem kernel. …”
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A Neural Networks Algorithm for the Minimum Colouring Problem Using FPGAs† by Harmanani, Haidar

“…The algorithm was implemented using VHSIC hardware description language (VHDL) and downloaded on a field programmable gate array (FPGA) device. …”
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A Parallel Neural Networks Algorithm for the Clique Partitioning Problem by Harmanani, Haidar M.

“…This paper presents a parallel algorithm to solve the Clique Partitioning Problem, an NP-complete problem. …”
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A stochastic iterative learning control algorithm with application to an induction motor by Saab, Samer S.

“…The convergence characteristics are shown to be similar to the ones of the optimal recursive algorithm. The proposed ILC algorithms are applied to two different models of an induction motor for angular speed tracking control. …”
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Fuzzy Logic Adaptive Crow Search Algorithm for MPPT of a Partially Shaded Photovoltaic System by Mohamed Ali Zeddini (22047920)

“…<p dir="ltr">The arbitrary selection of the Crow Search Algorithm (CSA) parameters, the Awareness Probability (AP) and the Flight Length (fl) results in poor convergence performance and efficiency even if the CSA performs well when solving global optimization problems. …”

Learn while Tracking by Saab, Samer S.

“…Numerical simulations of an unstable linear system, an induction motor, and a nonlinear one-link flexible manipulator are included to show the performance potential of the proposed algorithm.…”
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Complexities of special matrix multiplication problems by Takche, J.

“…Efficient algorithms are also developed to multiply a tridiagonal matrix by an arbitrary matrix, and to multiply two tridiagonal matrices.…”
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A MIMO Sampling-Rate-Dependent Controller by Saab, Samer S.

“…Performance is compared to a PID controller with fuzzy gain scheduling, four multivariable PID controllers, an H ∞ optimal controller, and an iterative-learning-control algorithm.…”
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Shuffled Linear Regression with Erroneous Observations by Saab, Samer S.

“…The proposed algorithm aims for per-iteration minimization of the mean square estimate error. …”
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An explicit finite-difference scheme for wave propagation in nonlinear optical structures by Al-Sunaidi, M. A.

“…In this paper, we present an algorithm that solves a time-domain nonlinear coupled system arising in nonlinear optics. …”

Learn while tracking. (c2013) by Toukhtarian, Raffi

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The architecture of a highly reconfigurable RISC dataflow array processor by Sait, Sadiq M.

“…The array can be programmed to execute arbitrary algorithms in both static and dynamic manner. …”
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Fast, effective vertex cover kernelization by Abu-Khzam, F.N.

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A quadratic kernel for 3-set packing by Abu-Khzam, Faisal N.

“…Such parameterized reductions are known as kernelization algorithms, and each reduced instance is called a problem kernel. …”
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Crown Structures for Vertex Cover Kernelization by Abu-Khzam, Faisal N.

“…Crown structures in a graph are defined and shown to be useful in kernelization algorithms for the classic vertex cover problem. Two vertex cover kernelization methods are discussed. …”
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Using C++ to Calculate SO(10) Tensor Couplings by Bhagwagar, Azadan

“…Therefore, there exists an opportunity to leverage the abilities of computer software in order to algorithmically perform these calculations on demand. …”
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