Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach حسب Sarif, Bambang

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Adaptive Time-Varying Brain Source Localization حسب Al-Momani, Sajedah A.

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Time-varying volatility model equipped with regime switching factor: valuation of option price written on energy futures حسب Leduc, Guillaume

"…We develop a semi-analytical method to determine the price of European options on these energy futures, involving the derivation of the characteristic function for the energy futures' dynamics. To determine the parameters of the regime switching model and identify when economic states change, we employ the EM algorithm, utilizing real gas futures price data. …"
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New Fast Arctangent Approximation Algorithm for Generic Real-Time Embedded Applications حسب Mohieddine Benammar (18103039)

"…A new 2nd order rational approximation formula is introduced for the first time in this work and benchmarked against existing alternatives as it improves the new algorithm performance. …"

Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids حسب Khayata, Mohammad Tarek

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Guaranteed Cost Control Of A Markov Jump Linear Uncertain System UsingA Time-Multiplied Cost Function حسب Boukas, EK

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Guaranteed Cost Control Of A Markov Jump Linear Uncertain System Using A Time-Multiplied Cost Function حسب Boukas, EK

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Guaranteed Cost Control Of A Markov Jump Linear Uncertain System Using A Time-Multiplied Cost Function حسب Boukas, EK

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Cross entropy error function in neural networks حسب Nasr, G.E.

"…The ANN is implemented using the cross entropy error function in the training stage. The cross entropy function is proven to accelerate the backpropagation algorithm and to provide good overall network performance with relatively short stagnation periods. …"
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A fuzzy basis function network for generator excitation control حسب Abido, M.A.

"…The proposed FBFN is trained over a wide range of operating conditions in order to re-tune the PSS parameters in real-time based on generator loading conditions. The orthogonal least squares learning algorithm is developed for designing an adequate and parsimonious FBFN model. …"
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Improving the Secure Socket Layer Protocol by modifying its Authentication function حسب El-Kassar, A. N.

"…The most common cryptographic algorithm used for this function is RSA. If we double the key length in RSA to have more secure communication, then it is known that the time needed for the encryption and decryption will be increased approximately eight times. …"
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A neural networks algorithm for data path synthesis حسب Harmanani, Haidar M.

"…The method formulates the allocation problem using the clique partitioning problem, an NP-complete problem, and handles multicycle functional units as well as structural pipelining. The algorithm has a running time complexity of O(1) for a circuit with n operations and c shared resources. …"
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Learning continuous functions using decision tree learning algorithms حسب Ibrahim, Ahmed Esmat Mahmoud

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A New Penalty Function Algorithm For Convex Quadratic Programming حسب Bendaya, M.

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Genetic and heuristic algorithms for regrouping service sites. (c2000) حسب Tabbara, Hiba

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Simulated evolution algorithm for multiobjective VLSI netlist bi-partitioning حسب Sait, Sadiq M.

"…In this paper the Simulated Evolution algorithm (SimE) is engineered to solve the optimization problem of multi-objective VLSI netlist bi-partitioning. …"
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STEM: spatial speech separation using twin-delayed DDPG reinforcement learning and expectation maximization حسب Muhammad Salman Khan (7202543)

Evolutionary algorithms, simulated annealing and tabu search: a comparative study حسب Youssef, H.

"…The three heuristics are applied on the same optimization problem and compared with respect to (1) quality of the best solution identified by each heuristic, (2) progress of the search frominitial solution(s) until stopping criteria are met, (3) the progress of the cost of the best solution as a function of time (iteration count), and (4) the number of solutions found at successive intervals of the cost function. …"
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Convergence analysis of the variable weight mixed-norm LMS-LMFadaptive algorithm حسب Zerguine, A.

"…In this work, the convergence analysis of the variable weight mixed-norm LMS-LMF (least mean squares-least mean fourth) adaptive algorithm is derived. The proposed algorithm minimizes an objective function defined as a weighted sum of the LMS and LMF cost functions where the weighting factor is time varying and adapts itself so as to allow the algorithm to keep track of the variations in the environment. …"
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A deterministic heuristic algorithm for optimal multiprocessor scheduling. (c1995) حسب Moujabber, Bassam N.

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