Results 111 to 120 of about 274,124 (332)
Advanced Healthcare Materials, EarlyView.Cerebral organoids are transforming brain research, yet the field remains fragmented. This comprehensive systematic review maps 738 studies published between 2014 and 2024 to uncover trends, gaps, and opportunities across neuroscience. Introducing OrganoidMap—an interactive, open‐access platform to explore and compare models—this work enables ...
Anna Wolfram +10 more
wiley +1 more source
Flash-flood forecasting by means of neural networks and nearest neighbour approach – a comparative study [PDF]
Nonlinear Processes in Geophysics, 2006 In this paper, Multi-Layer Perceptron and Radial-Basis Function Neural Networks, along with the Nearest Neighbour approach and linear regression are utilized for flash-flood forecasting in the mountainous Nysa Klodzka river catchment.
A. Piotrowski +2 more
doaj
Neural adaptive sliding mode controller for unmanned surface vehicle steering system
Advances in Mechanical Engineering, 2018 Unmanned surface vehicle has the properties such as complexity, nonlinearity, time variability, and uncertainty, which lead to the difficulty of obtaining a precise kinematics model.
Lili Wan +4 more
doaj +1 more source
Radial basis function network using Lambert-Tsallis Wq function
, 2019 The present work brings two applications of the Lambert-Tsallis Wq function in radial basis function networks (RBFN). Initially, a RBFN is used to discriminate between entangled and disentangled bipartite of qubit states. The kernel used is based on the Lambert-Tsallis Wq function for q = 2 and the quantum relative disentropy is used as distance ...
da Silva, J. L. M. +2 more
openaire +3 more sources
Nanotherapies for Atherosclerosis: Targeting, Catalysis, and Energy Transduction
Advanced Healthcare Materials, EarlyView.Atherosclerosis management is hindered by poor drug targeting and plaque heterogeneity. Nanotechnology overcomes these barriers via three core strategies: (1) target‐engineered nanocarriers that achieve lesion‐specific precision via ligand modification, biomimetic camouflage, stimuli‐responsive release, and self‐propelling nanomotors; (2) catalytic ...
Yuqi Yang +4 more
wiley +1 more source
Long-Term Peak Demand Forecasting by Using Radial Basis Function Neural Networks
Iranian Journal of Electrical and Electronic Engineering, 2010 Prediction of peak loads in Iran up to year 2011 is discussed using the Radial Basis Function Networks (RBFNs). In this study, total system load forecast reflecting the current and future trends is carried out for global grid of Iran.
L. Ghods, M. Kalantar
doaj
Fractal and FractionalThis paper investigates the tracking problem of fractional-order multi-agent systems. Both the order and parameters of the leader are unknown. Firstly, based on the positive system approach, the asymptotically stable criteria for incommensurate linear ...
Conggui Huang, Fei Wang
doaj +1 more source
Orthogonal least squares learning algorithm for radial basis function networks
IEEE Trans. Neural Networks, 1991 Shang-Liang Chen, C. Cowan, P. Grant
semanticscholar +1 more source
Advanced Materials, EarlyView.Screen gate‐based transistors are presented, enabling tunable analog sigmoid and Gaussian activations. The SA‐transistor improves MRI classification accuracy, while the GA‐transistor supports precise Gaussian kernel tuning for forecasting. Both functions are implemented in a single device, offering compact, energy‐efficient analog AI processing ...
Junhyung Cho +9 more
wiley +1 more source
Deep Radial Basis Function Networks
Radial basis function (RBF) networks are often viewed as instable when used in multi-layered architectures and therefore are mostly used in a single-layered manner. Universal approximation theorems for single-layered RBF networks further render deeper architectures useless.
Fabian Wurzberger, Friedhelm Schwenker
openaire +1 more source