Results 31 to 40 of about 184,637 (335)

Thrombolytic proteins profiling: High‐throughput activity, selectivity, and resistance assays

FEBS Open Bio, EarlyView.
We present optimized biochemical protocols for evaluating thrombolytic proteins, enabling rapid and robust screening of enzymatic activity, inhibition resistance, and fibrin affinity, stimulation, and selectivity. The outcome translates to key clinical indicators such as biological half‐life and bleeding risk. These assays streamline the development of
Martin Toul, Alan Strunga, Jiri Damborsky, Zbynek Prokop   +3 more
wiley   +1 more source

Neural-Dynamic Based Synchronous-Optimization Scheme of Dual Redundant Robot Manipulators

Frontiers in Neurorobotics, 2018
In order to track complex-path tasks in three dimensional space without joint-drifts, a neural-dynamic based synchronous-optimization (NDSO) scheme of dual redundant robot manipulators is proposed and developed. To do so, an acceleration-level repetitive
Zhijun Zhang, Qiongyi Zhou, Weisen Fan
doaj   +1 more source

Robust Energy-Efficient Hybrid Beamforming Design for Massive MIMO LEO Satellite Communication Systems

IEEE Access, 2022
In low earth orbit (LEO) satellite communication systems, the limited energy supply capacity and the difficulty in obtaining channel state information (CSI) are the practical challenges.
Yang Liu, Changqing Li, Jiong Li, Lu Feng   +3 more
doaj   +1 more source

A Method to Guarantee Local Convergence for Sequential Quadratic Programming with Poor Hessian Approximation

, 2017
Sequential Quadratic Programming (SQP) is a powerful class of algorithms for solving nonlinear optimization problems. Local convergence of SQP algorithms is guaranteed when the Hessian approximation used in each Quadratic Programming subproblem is close ...
Butler, Hans, Lazar, Mircea, Nguyen, Tuan T.   +2 more
core   +1 more source

A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems

International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam, Anthony Siming Chen, Guido Herrmann   +2 more
wiley   +1 more source

A Global Optimization Algorithm for Generalized Quadratic Programming

Journal of Applied Mathematics, 2013
We present a global optimization algorithm for solving generalized quadratic programming (GQP), that is, nonconvex quadratic programming with nonconvex quadratic constraints.
Hongwei Jiao, Yongqiang Chen
doaj   +1 more source

Tightening a Discrete Formulation of the Quadratic Assignment Problem

Chemical Engineering Transactions, 2013
The quadratic assignment problem is a well studied and notoriously difficult combinatorial problem. Recently, a discrete linear formulation of the quadratic assignment problem was presented that solved five previously unsolved instances from the ...
A. Nyberg, T. Westerlund
doaj   +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

A Rank-Two Feasible Direction Algorithm for the Binary Quadratic Programming

Journal of Applied Mathematics, 2013
Based on the semidefinite programming relaxation of the binary quadratic programming, a rank-two feasible direction algorithm is presented. The proposed algorithm restricts the rank of matrix variable to be two in the semidefinite programming relaxation ...
Xuewen Mu, Yaling Zhang
doaj   +1 more source

An accelerating algorithm for globally solving nonconvex quadratic programming

Journal of Inequalities and Applications, 2018
To globally solve a nonconvex quadratic programming problem, this paper presents an accelerating linearizing algorithm based on the framework of the branch-and-bound method. By utilizing a new linear relaxation approach, the initial quadratic programming
Li Ge, Sanyang Liu
doaj   +1 more source