Results 121 to 130 of about 5,532 (307)
Optimality Conditions for Approximate Solutions in Multiobjective Optimization Problems
Journal of Inequalities and Applications, 2010 We study first- and second-order necessary and sufficient optimality conditions for approximate (weakly, properly) efficient solutions of multiobjective optimization problems. Here, tangent cone, -normal cone, cones of feasible directions, second-order
Lee HeungWingJoseph +2 more
doaj
Iterative methods for efficient sampling-based optimal motion planning of nonlinear systems
International Journal of Applied Mathematics and Computer Science, 2018 This paper extends the RRT* algorithm, a recently developed but widely used sampling based optimal motion planner, in order to effectively handle nonlinear kinodynamic constraints.
Ha Jung-Su +2 more
doaj +1 more source
Asymptotic theory of integrated conditional moment tests
In this paper we derive the asymptotic distribution of the test statistic of a generalized version of the integrated conditional moment (ICM) test of Bierens (1982, 1984), under a class of Vn-local alternatives, where n is the sample size.
Ploberger, W., Bierens, H.J.
core
Robust generalized cross-validation for choosing the regularization parameter
, 2006 Let fλ be the regularized solution for the problem of estimating a function or vector f0 from noisy data yi ≤ Lif0 + εi, i ≤ 1, ..., n, where Li are linear functionals.
Lukas, M.A.
core
Asymptotic Optimality of Binary Faster-than-Nyquist Signaling
, 2018 In this letter, the asymptotic information rate of faster-than-Nyquist (FTN) signaling is examined when the data sequence consists of independent and identically distributed (i.i.d.) binary symbols.
Cho, JH, Yoo, YG
core +1 more source
Advanced Intelligent Systems, EarlyView.This work presents a bio‐inspired computing framework for Parkinson's disease analog recognition using electroencephalogram signals. Temporally encoded EEG features stimulate a mycelium‐inspired memristive reservoir, where disease‐related patterns emerge through physical spatiotemporal dynamics.
Ioannis K. Chatzipaschalis +5 more
wiley +1 more source
Advanced Intelligent Systems, EarlyView.A physics‐guided deep learning framework, ParamNet, is introduced for the intelligent self‐inversion of vacuum optical tweezers. By fuzing dual‐branch time–frequency features with physical dynamical constraints, it achieves high‐accuracy calibration of trap parameters from short‐window, low‐frequency trajectories, outperforming traditional methods ...
Qi Zheng +4 more
wiley +1 more source
Worst-case estimation and asymptotic theory for models with unobservables [PDF]
, 2004 This paper proposes a worst-case approach for estimating econometric models containing unobservable variables. Worst-case estimators are robust against the adverse effects of unobservables.
Vidal-Sanz, Jose M. +1 more
core
Design Optimization of Soft Fabric Pneumatic Actuators
Advanced Intelligent Systems, EarlyView.This study presents a systematic optimization framework for elongating and bending fabric‐based soft pneumatic actuators. After a preliminary design‐space reduction, the framework minimizes energy consumption under mechanical performance constraints by integrating validated finite element modeling with statistical surrogate models. Optimal designs were
Grigorios M. Chatziathanasiou +2 more
wiley +1 more source
American Journal of Agricultural Economics, EarlyView.Abstract Crop insurance is undoubtedly an extremely valuable element in protecting agricultural businesses, but in many cases standard indemnity‐based products have had very low uptake due to high transaction costs elevating premiums to unaffordable levels.
Amogh Prakasha Kumar +2 more
wiley +1 more source