Results 1 to 10 of about 5,020,641 (311)
Journal of Marine Science and Engineering, 2022 Autonomous underwater vehicle (AUV) path planning in complex marine environments meets many chanllenges, such as many influencing factors, complex models and the performance of the optimization algorithm to be improved.
Bin Li +4 more
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IEEE Access, 2022 This paper is concerned with the fusion filtering problem for stochastic uncertain multi-sensor systems with time-correlated measurement noises, where the stochastic uncertainties are described by white multiplicative noises, and the additive measurement
Jing Ma, Sihong Liu, Qi Zhang
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Sensors, 2022 This paper concerns the distributed fusion filtering problem for descriptor systems with time-correlated measurement noises. The original descriptor is transformed into two reduced-order subsystems (ROSs) based on singular value decomposition.
Jing Ma, Liling Xu
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Pose-Graph Neural Network Classifier for Global Optimality Prediction in 2D SLAM
IEEE Access, 2021 The ability to decide if a solution to a pose-graph problem is globally optimal is of high significance for safety-critical applications. Converging to a local-minimum may result in severe estimation errors along the estimated trajectory.
Rana Azzam +3 more
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A Global Optimizer for Nanoclusters [PDF]
Frontiers in Chemistry, 2019 We have developed an algorithm to automatically build the global minimum and other low-energy minima of nanoclusters. This method is implemented in PyAR (https://github.com/anooplab/pyar) program. The global optimization in PyAR involves two parts, generation of several trial geometries and gradient-based local optimization of the trial geometries ...
Maya Khatun +2 more
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Effect of Objective Function on Data-Driven Greedy Sparse Sensor Optimization
IEEE Access, 2021 The problem of selecting an optimal set of sensors estimating a high-dimensional data is considered. Objective functions based on D-, A-, and E-optimality criteria of optimal design are adopted to greedy methods, that maximize the determinant, minimize ...
Kumi Nakai +4 more
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Some remarks on duality and optimality of a class of constrained convex quadratic minimization problems [PDF]
Yugoslav Journal of Operations Research, 2017 In this paper the duality and optimality of a class of constrained convex quadratic optimization problems have been studied. Furthermore, the global optimality condition of a class of interval quadratic minimization problems has also been ...
Roy Sudipta +2 more
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Sparse neural network optimization by Simulated Annealing
Franklin Open, 2023 The over-parameterization of neural networks and the local optimality of backpropagation algorithm have been two major problems associated with deep-learning.
Ercan Engin Kuruoglu +2 more
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Optimal Control Problems Involving Combined Fractional Operators with General Analytic Kernels
Mathematics, 2021 Fractional optimal control problems via a wide class of fractional operators with a general analytic kernel are introduced. Necessary optimality conditions of Pontryagin type for the considered problem are obtained after proving a Gronwall type ...
Faïçal Ndaïrou, Delfim F. M. Torres
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Learning to be Global Optimizer
CoRR, 2020 The advancement of artificial intelligence has cast a new light on the development of optimization algorithm. This paper proposes to learn a two-phase (including a minimization phase and an escaping phase) global optimization algorithm for smooth non-convex functions. For the minimization phase, a model-driven deep learning method is developed to learn
Haotian Zhang, Jianyong Sun, Zongben Xu
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