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algorithm both » algorithm goa (Expand Search), algorithm aoa (Expand Search), algorithm its (Expand Search)
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Consensus-Based Distributed Formation Control of Multi-Quadcopter Systems: Barrier Lyapunov Function Approach
Published 2023“…<p dir="ltr">The problem of formation tracking control for a group of quadcopters with nonlinear dynamics using Barrier Lyapunov Functions (BLFs) is studied in this paper where the quadcopters are following a desired predefined trajectory in a predefined formation shape. …”
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Tracking analysis of the NLMS algorithm in the presence of both random and cyclic nonstationarities
Published 2003“…Tracking analysis of the normalized least mean square (NLMS) algorithm is carried out in the presence of two sources of nonstationarities: 1) carrier frequency offset between transmitter and receiver; 2) random variations in the environment. …”
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Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach
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4
Genetic and heuristic algorithms for regrouping service sites. (c2000)
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5
Design and Implementation of an Advanced Control and Guidance Algorithm of a Single Rotor Helicopter
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6
Salp swarm algorithm: survey, analysis, and new applications
Published 2024“…The behavior of the species when traveling and foraging in the waters is the main source of SSA and MSSA. These two algorithms are put to test on a variety of mathematical optimization functions to see how they behave when it comes to finding the best solutions to optimization problems. …”
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Iterative Least Squares Functional Networks Classifier
Published 2007“…Both methodology and learning algorithm for this kind of computational intelligence classifier using the iterative least squares optimization criterion are derived. …”
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Cross entropy error function in neural networks
Published 2002“…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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Optimization of Support Structures for Offshore Wind Turbines using Genetic Algorithm with Domain-Trimming (GADT)
Published 2017“…The two versions of the optimization problem are nonlinearly constrained where the objective function is the material weight of the supporting truss. …”
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10
Evolutionary algorithm for protein structure prediction
Published 2010“…A protein is characterized by its 3D structure, which defines its biological function. The protein structure prediction problem has real-world significance where several diseases are associated with the wrong folding of proteins. …”
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11
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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An improved kernelization algorithm for r-Set Packing
Published 2010“…We present a reduction procedure that takes an arbitrary instance of the r -Set Packing problem and produces an equivalent instance whose number of elements is in O(kr−1), where k is the input parameter. Such parameterized reductions are known as kernelization algorithms, and a reduced instance is called a problem kernel. …”
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Learning continuous functions using decision tree learning algorithms
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15
A New Penalty Function Algorithm For Convex Quadratic Programming
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16
New fault models and efficient BIST algorithms for dual-portmemories
Published 1997“…These modifications allow multiple access of memory cells for increased test speed with minimal overhead on both silicon area and device performance. New fault models are proposed, and efficient O(n) test algorithms are described for both the memory array and the address decoders. …”
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A comparative study of RSA based digital signature algorithms
Published 2006“…We implement the classical and modified RSA cryptosystem to compare and to test their functionality, reliability and security. To test the security of the algorithms we implement attack algorithms to solve the factorization problem in Z, Z[<i>i</i>] and F[<i>x</i>]. …”
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Iterative Methods for the Solution of a Steady State Biofilter Model
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19
Evolutionary algorithms, simulated annealing and tabu search: a comparative study
Published 2020“…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
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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