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Published in 2018 at "Nonlinear Dynamics"
DOI: 10.1007/s11071-018-4512-7
Abstract: In this paper, the classical problem of uncovering the maximal invariant set of a (discrete-time) dynamical system is illuminated from a novel perspective, which in particular leads to a novel sample-based computational procedure to compute…
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Keywords:
sample based;
computations invariant;
invariant set;
invariant sets ... See more keywords
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Published in 2019 at "Aerospace Science and Technology"
DOI: 10.1016/j.ast.2019.02.012
Abstract: Abstract Predicting aircraft dynamics and vibration loads at components' interfaces is a key task for ensuring a robust design and development of the product. Usually, whereas in the case of isolate components the dynamic behavior…
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Keywords:
loads components;
sample based;
approach estimate;
based approach ... See more keywords
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Published in 2019 at "Neurocomputing"
DOI: 10.1016/j.neucom.2018.11.083
Abstract: Abstract Inferring the camera pose with high accuracy is deemed crucial in many applications such as robot manipulation and virtual reality. Traditionally, features extracted from camera images are processed by Kalman-based schemes due to their…
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Keywords:
sample based;
kalman filtering;
camera pose;
camera ... See more keywords
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Published in 2022 at "Robotica"
DOI: 10.1017/s026357472200008x
Abstract: The main objective of a motion planning algorithm is to find a collision-free path in the workspace of a robotic manipulator in a point-to-point motion. Among the various motion planning methods available, sample-based motion planning…
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Keywords:
sample based;
motion;
based motion;
planning methods ... See more keywords
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Published in 2019 at "Organised Sound"
DOI: 10.1017/s1355771819000177
Abstract: In this article, based on four decades of experience of using samples in diverse ways in experimental, particularly electroacoustic compositions, the author investigates the world of what he calls ‘sample-based sound-based music’ and suggests that…
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Keywords:
sample based;
sound;
composing sounds;
sounds things ... See more keywords
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Published in 2022 at "Chaos"
DOI: 10.1063/5.0088379
Abstract: Sample-based methods are a useful tool in analyzing the global behavior of multi-stable systems originating from various branches of science. Classical methods, such as bifurcation diagrams, Lyapunov exponents, and basins of attraction, often fail to…
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Keywords:
sample based;
based methods;
review sample;
methods used ... See more keywords
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Published in 2021 at "Measurement Science and Technology"
DOI: 10.1088/1361-6501/abf865
Abstract: A surface defect is an important factor that affects product quality. However, due to the large differences in area of different surface defects, and noise on various surfaces, defect detection is challenging. The convolutional neural…
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Keywords:
sample based;
virtual sample;
detection;
defect detection ... See more keywords
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Published in 2018 at "IEEE Control Systems Letters"
DOI: 10.1109/lcsys.2018.2845546
Abstract: In this letter, a guidance and tracking control strategy for fixed-wing unmanned aerial vehicle autopilots is presented. The proposed control exploits recent results on sample-based stochastic model predictive control, which allows coping in a computationally…
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Keywords:
sample based;
fixed wing;
based smpc;
control ... See more keywords
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Published in 2018 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2017.2711659
Abstract: Background subtraction techniques are often treated as fundamental and significant ways to analyze and understand video content. In this paper, we propose a weight-sample-based method for foreground detection. This method allows us to use a…
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Keywords:
sample based;
method;
weight sample;
based method ... See more keywords
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Published in 2021 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2021.3102323
Abstract: This article introduces a neural approximation-based method for solving continuous optimization problems with probabilistic constraints. After reformulating the probabilistic constraints as the quantile function, a sample-based neural network model is used to approximate the quantile…
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Keywords:
based neural;
sample based;
neural approximation;
probabilistic constrained ... See more keywords