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algorithm steps » algorithm its (Expand Search)
algorithm cost » algorithm goa (Expand Search), algorithm aoa (Expand Search), algorithm its (Expand Search)
algorithm both » algorithm goa (Expand Search), algorithm aoa (Expand Search), algorithm its (Expand Search)
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Tracking analysis of the NLMS algorithm in the presence of both random and cyclic nonstationarities
Published 2003“…The results show that, unlike in the stationary case, the steady-state excess MSE is not a monotonically increasing function of the step size. Moreover, the ability of the adaptive algorithm to track the variations in the environment is shown to degrade with increasing frequency offset.…”
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Genetic and heuristic algorithms for regrouping service sites. (c2000)
Published 2000Get full text
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Distributed optimal coverage control in multi-agent systems: Known and unknown environments
Published 2024“…The proposed approach leverages a novel cost function for optimizing the agents’ coverage and the cost function eventually aligns with the conventional Voronoi-based cost function. …”
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Multi-Target Tracking Resources Allocation Using Multi-Agent Modeling and Auction Algorithm
Published 2023Subjects: Get full text
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ANT-colony optimization-direct torque control for a doubly fed induction motor : An experimental validation
Published 2022“…The new combined ACO-DTC strategy has been studied for optimizing the gains of the PID controller by using a cost function such as Integral Square Error (ISE). …”
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New enumeration algorithm for regular boolean functions
Published 2018“…After proving this equivalence, this paper introduces a novel data structure that may, with further tweaking, enable faster enumeration algorithms for both regular Boolean functions and all-capacities knapsack problem instances.…”
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Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization
Published 2024“…This hybrid approach, the Improved Prairie Dog Optimization Algorithm (IPDOA) with the Genetic Algorithm (GA), utilizes the strengths of both algorithms to improve the overall optimization performance. …”
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A New Penalty Function Algorithm For Convex Quadratic Programming
Published 2020“…In this paper, we develop an exterior point algorithm for convex quadratic programming using a penalty function approach. …”
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Convergence analysis of the variable weight mixed-norm LMS-LMFadaptive algorithm
Published 2000“…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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Modified arithmetic optimization algorithm for drones measurements and tracks assignment problem
Published 2023“…In particular, a new modified method based on the Arithmetic Optimization Algorithm is proposed. The optimization is applied to a formulated cost function that considers uncertainty, false alarms, and existing clutters. …”
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Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques
Published 2024“…An objective function utilizing the covariance of the fused tracks is used by the first algorithm while a cost function based on the Kullback-Leibler (KL) divergence measure is used in the second case for training the LSTM. …”
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A utility-based algorithm for joint uplink/downlink scheduling in wireless cellular networks
Published 2012“…While most existing literature focuses on downlink-only or uplink-only scheduling algorithms, the proposed algorithm aims at ensuring a utility function that jointly captures the quality of service in terms of delay and channel quality on both links. …”
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