S Singer, J Nelder - Scholarpedia, 2009 - var.scholarpedia.org
The Nelder-Mead algorithm or simplex search algorithm, originally published in 1965 (Nelder and Mead, 1965), is one of the best known algorithms for multidimensional …
The existence of the curse of dimensionality is well known, and its general effects are well acknowledged. However, and perhaps due to this colloquial understanding, specific …
S Singer, S Singer - Applied Numerical Analysis & …, 2004 - Wiley Online Library
Abstract The Nelder–Mead or simplex search algorithm is one of the best known algorithms for unconstrained optimization of non–smooth functions. Even though the basic algorithm is …
M Nikooroo, Z Becvar - IEEE Transactions on Network Science …, 2022 - ieeexplore.ieee.org
The unmanned aerial vehicles (UAVs) acting as flying base stations (FlyBSs) are considered as an efficient way to enhance the capacity of mobile networks. The enhancement provided …
Target motion analysis (TMA) with wideband passive sonar has received much attention. Maximum likelihood probabilistic data association (ML-PDA) represents an asymptotically …
X Wang, Y Shi, W Xin, T Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Beamforming for multi-antenna wireless communication systems has been widely studied and applied in practice. However, its performance in high mobility scenarios deteriorates …
Y Yan, X Shen, F Hua, X Zhong - IEEE Sensors Journal, 2018 - ieeexplore.ieee.org
The received energy has been becoming an efficient and attractive measure for acoustic source localization due to its cost saving in both energy and computation capability. We …
Pairwise comparison matrices play a prominent role in multiple-criteria decision-making, particularly in the analytic hierarchy process (AHP). Another form of preference modeling …
S Yun, X Zhang, B Li - Journal of the American Statistical …, 2022 - Taylor & Francis
Comparing the spatial characteristics of spatiotemporal random fields is often at demand. However, the comparison can be challenging due to the high-dimensional feature and …