Results 41 to 50 of about 35,631 (308)
An on-line training radial basis function neural network for optimum operation of the UPFC [PDF]
The concept of Flexible A.C. Transmission Systems (FACTS) technology was developed to enhance the performance of electric power networks (both in steady-state and transient-state) and to make better utilization of existing power transmission facilities ...
Farrag, M. E. A. +6 more
core +1 more source
ABSTRACT Objective Cognitive decline is a disabling and variable feature of Parkinson disease (PD). While cholinergic system degeneration is linked to cognitive impairments in PD, most prior research reported cross‐sectional associations. We aimed to fill this gap by investigating whether baseline regional cerebral vesicular acetylcholine transporter ...
Taylor Brown +6 more
wiley +1 more source
A Depolarizing Leak in Sodium Bicarbonate Cotransporter NBCe1 Causes Brain Edema
ABSTRACT Objectives SLC4A4 encodes electrogenic sodium bicarbonate cotransporter NBCe1, prominently expressed in kidney and brain. Recessive loss‐of‐function variants in SLC4A4 cause proximal renal tubular acidosis, no brain edema. In the brain, NBCe1 is expressed by astrocytes, where it regulates pH and mediates astrocyte volume changes.
Quinty Bisseling +16 more
wiley +1 more source
Additive Gaussian Process Regression for Predictive Design of High‐Performance, Printable Silicones
A chemistry‐aware design framework for tuning printable polydimethylsiloxane (PDMS) for vat photopolymerization (VPP) is developed using additive Gaussian process (GP) modeling. Polymer network mechanics informs variable groupings, feasible formulation constraints, and interaction variables.
Roxana Carbonell +3 more
wiley +1 more source
Modeliranje 3D-ploskev z nevronskimi mrežami z radialnimi baznimi aktivacijskimi funkcijami ( = The employment of a radial basis function network for 3D surface modelling) [PDF]
Determination of the mathematical model of elevation computation is based on a discrete data set, which could be used for elevation modelling.
Polona Pavlovčič Prešeren +2 more
doaj +1 more source
Learning and Generalization in Radial Basis Function Networks [PDF]
The two-layer radial basis function network, with fixed centers of the basis functions, is analyzed within a stochastic training paradigm. Various definitions of generalization error are considered, and two such definitions are employed in deriving generic learning curves and generalization properties, both with and without a weight decay term.
Jason A. S. Freeman, David Saad
openaire +2 more sources
A simplified thermoplastic pultrusion model is developed to predict thermal fields in glass fiber/polyethylene terephthalate (GF/PET) composites with reduced computational cost. By combining effective material homogenization, validation against literature data, and Gaussian‐process‐based optimization, the study reveals how heating limits, pulling speed,
Elder Soares +3 more
wiley +1 more source
Radial basis function neural network is a type of three-layer feedforward non-linear network. It has many good properties, such as powerful ability for function approximation, classification.
陆爽, 侯跃谦, 田野
doaj
Complex-valued symmetric radial basis function network for beamforming
The complex-valued radial basis function (RBF) network proposed by Chen et al. (1994) has found many applications for processing complex-valued signals, in particular, for communication channel equalization and signal detection.
Sheng Chen, Chen, Sheng
core +1 more source
Additive manufacturing provides precise control over the placement of continuous fibres within polymer matrices, enabling customised mechanical performance in composite components. This article explores processing strategies, mechanical testing, and modelling approaches for additive manufactured continuous fibre‐reinforced composites.
Cherian Thomas, Amir Hosein Sakhaei
wiley +1 more source

