Results 71 to 80 of about 39,060 (206)

A Convex Programming Method for Rocket Powered Landing With Angle of Attack Constraint

IEEE Access, 2020
Real time trajectory planning is vital in rocket precision powered landing guidance. Due to the nonconvex angle of attack (AOA) constraint and other constraints, including nonlinear dynamics and thrust constraint, the powered landing trajectory planning ...
Lei Xie, Hongbo Zhang, Xiang Zhou, Guojian Tang   +3 more
doaj   +1 more source

A Quantised Push‐Sum Distributed Adaptive Momentum Algorithm for Optimisation Over Directed Networks

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT In this paper, we investigate a distributed constrained optimisation problem over directed networks. The agents in the networks conduct local computations and communications, endeavouring to collaboratively minimise the aggregation of all locally known convex cost functions subject to a global constraint set.
Qingguo Lü, Mingyu Guan, Chenglong He, Chen Chen, Xiangguang Dai, Man‐Fai Leung, Wei Zhang   +6 more
wiley   +1 more source

Energy-Efficient Optimization in Multi-Sensor WBAN With Multi-Antenna AP

IEEE Access, 2019
This paper optimizes the energy efficiency performance by joint time and beamforming weights allocation in a wireless body area network (WBAN), which consists of a multi-antenna access point (AP), in particular, the AP intends to broadcast radio ...
Zhi Mao, Fengye Hu, Zhijun Li, Zhuang Ling, Shuang Li   +4 more
doaj   +1 more source

Double‐Integration‐Enhanced Stochastic Gradient Descent Based on Neural Dynamics for Improving Generalisation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Generalisation is a crucial aspect of deep learning, enabling models to perform well on unseen data. Currently, most optimisers that improve generalisation typically suffer from efficiency bottlenecks. This paper proposes a double‐integration‐enhanced stochastic gradient descent (DIESGD) optimiser, which treats the negative gradient as an ...
Ting Li, Longbang Wang, Jiexing Li, Jicheng Li   +3 more
wiley   +1 more source

Hidden Convexity in Partially Separable Optimization [PDF]

The paper identifies classes of nonconvex optimization problems whose convex relaxations have optimal solutions which at the same time are global optimal solutions of the original nonconvex problems. Such a hidden convexity property was so far limited to
Ben-Tal, A., Hertog, D. den, Laurent, M.
core   +1 more source

Convergent Interval Confirmation for Three‐Step Discrete Specific Zeroing Neural Dynamics Illustrated With Repetitive Motion Planning of Redundant Manipulators

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Repetitive motion planning (RMP) for redundant manipulators with high convergent precision becomes an intense research topic due to its more degrees of freedom. In this paper, a specific zeroing neural dynamics (SZND) model for the RMP is first set up via zeroing neurodynamics.
Ying Kong, Shaoyuan Sun, Yunliang Jiang, Lin Wei   +3 more
wiley   +1 more source

Global-Initialization-Based Model Predictive Control for Mobile Robots Navigating Nonconvex Obstacle Environments

Actuators
This paper proposes a nonlinear model predictive control (MPC) framework initialized using an initial-guess particle swarm optimization (IG-PSO) algorithm for mobile robots navigating in environments with nonconvex obstacles.
Seung-Mok Lee
doaj   +1 more source

Cuckoo optimization algorithm with penalty function and binary approach for combined heat and power economic dispatch problem

Energy Reports, 2020
This paper is related to a solution approach for the nonlinear and nonconvex combined heat and power economic dispatch problem (CHPED). It combines the cuckoo optimization algorithm with penalty function (PFCOA) published in “Mellal and Williams (2015 ...
Mohamed Arezki Mellal, Edward J. Williams   +1 more
doaj   +1 more source

Allocative efficiency and the productivity slowdown

Canadian Journal of Economics/Revue canadienne d'économique, EarlyView.
Abstract This paper evaluates the contribution of cross‐sector allocative efficiency to the productivity slowdown in the US during the 1970s and 2000s. We extend the framework of Oberfield (2013) to derive sufficient statistics for allocative efficiency and decompose aggregate productivity growth in a multisector economy.
Lin Shao, Rongsheng Tang
wiley   +1 more source

Duality in nonconvex optimization

Journal of Mathematical Analysis and Applications, 1978
AbstractWe examine a notion of duality which appears to be useful in situations where the usual convex duality theory is not appropriate because the functional to be minimized is not convex. The principle is a generalization of a duality theorem derived previously (J. F. Toland, University of Essex Fluid Mechanics Research Institute, Report No.
openaire   +2 more sources