Results 21 to 30 of about 131,594 (222)

Convex optimization problem prototyping for image reconstruction in computed tomography with the Chambolle-Pock algorithm [PDF]

, 2012
The primal-dual optimization algorithm developed in Chambolle and Pock (CP), 2011 is applied to various convex optimization problems of interest in computed tomography (CT) image reconstruction. This algorithm allows for rapid prototyping of optimization
Barrett H H, Bian J, Boyd S P, Combettes P L, De Man B, Defrise M, Elad M, Emil Y Sidky, Erdogan H, Green P, Jakob H Jørgensen, Jensen T L, Jørgensen J H, Jørgensen J H Hansen P C Sidky E Y Reiser I S Pan X, Li M, Nocedal J, Pan X, Pock T Chambolle A, Ritschl L, Rockafellar R T, Sidky E Y, Sidky E Y, Xiaochuan Pan, Xu F   +23 more
core   +2 more sources

A new local path planning approach based on improved dual covariant Hamiltonian optimization for motion planning method

Advances in Mechanical Engineering, 2019
We propose a new local path planning approach based on optimization methods with probabilistic completeness in this article. This approach adds a linear constraint to the original covariant Hamiltonian optimization for motion planning problem with a new ...
Bo You, Zhi Li, Liang Ding, Haibo Gao, Jiazhong Xu   +4 more
doaj   +1 more source

Learning Control Lyapunov Functions from Counterexamples and Demonstrations

, 2019
We present a technique for learning control Lyapunov-like functions, which are used in turn to synthesize controllers for nonlinear dynamical systems that can stabilize the system, or satisfy specifications such as remaining inside a safe set, or ...
Ravanbakhsh, Hadi, Sankaranarayanan, Sriram   +1 more
core   +1 more source

Learning Lyapunov (Potential) Functions from Counterexamples and Demonstrations

, 2017
We present a technique for learning control Lyapunov (potential) functions, which are used in turn to synthesize controllers for nonlinear dynamical systems.
Ravanbakhsh, Hadi, Sankaranarayanan, Sriram   +1 more
core   +1 more source

Novel Bounds for Incremental Hessian Estimation With Application to Zeroth-Order Federated Learning

IEEE Open Journal of Control Systems
The Hessian matrix conveys important information about the curvature, spectrum and partial derivatives of a function, and is required in a variety of tasks. However, computing the exact Hessian is prohibitively expensive for high-dimensional input spaces,
Alessio Maritan, Luca Schenato, Subhrakanti Dey   +2 more
doaj   +1 more source

Toward a More Complete, Flexible, and Safer Speed Planning for Autonomous Driving via Convex Optimization

Sensors, 2018
In this paper, we present a complete, flexible and safe convex-optimization-based method to solve speed planning problems over a fixed path for autonomous driving in both static and dynamic environments. Our contributions are five fold.
Yu Zhang, Huiyan Chen, Steven L. Waslander, Tian Yang, Sheng Zhang, Guangming Xiong, Kai Liu   +6 more
doaj   +1 more source

Infrared laser sampling of low volumes combined with shotgun lipidomics reveals lipid markers in palatine tonsil carcinoma

Molecular Oncology, EarlyView.
Nanosecond infrared laser (NIRL) low‐volume sampling combined with shotgun lipidomics uncovers distinct lipidome alterations in oropharyngeal squamous cell carcinoma (OPSCC) of the palatine tonsil. Several lipid species consistently differentiate tumor from healthy tissue, highlighting their potential as diagnostic markers.
Leonard Kerkhoff, Manuela Moritz, Dennis Eggert, Anna Worthmann, Joerg Heeren, Henrike Zech, Till S. Clauditz, Waldemar Wilczak, Hartmut Schlüter, Christian S. Betz, Arne Böttcher, Jan Hahn   +11 more
wiley   +1 more source

Phase Behavior of Colloidal Superballs: Shape Interpolation from Spheres to Cubes

, 2010
The phase behavior of hard superballs is examined using molecular dynamics within a deformable periodic simulation box. A superball's interior is defined by the inequality $|x|^{2q} + |y|^{2q} + |z|^{2q} \leq 1$, which provides a versatile family of ...
Frank H. Stillinger, I. Nezbeda, Robert D. Batten, S. Torquato, Salvatore Torquato   +4 more
core   +1 more source

Hopfield Neural Networks for Online Constrained Parameter Estimation With Time‐Varying Dynamics and Disturbances

International Journal of Adaptive Control and Signal Processing, EarlyView.
This paper proposes two projector‐based Hopfield neural network (HNN) estimators for online, constrained parameter estimation under time‐varying data, additive disturbances, and slowly drifting physical parameters. The first is a constraint‐aware HNN that enforces linear equalities and inequalities (via slack neurons) and continuously tracks the ...
Miguel Pedro Silva
wiley   +1 more source

Douglas–Rachford algorithm for control- and state-constrained optimal control problems

AIMS Mathematics
We consider the application of the Douglas–Rachford (DR) algorithm to solve linear-quadratic (LQ) control problems with box constraints on the state and control variables.
Regina S. Burachik, Bethany I. Caldwell, C. Yalçın Kaya   +2 more
doaj   +1 more source