Results 31 to 40 of about 59,339 (255)

A Novel Kernel for RBF Based Neural Networks [PDF]

Abstract and Applied Analysis, 2014
Radial basis function (RBF) is well known to provide excellent performance in function approximation and pattern classification. The conventional RBF uses basis functions which rely on distance measures such as Gaussian kernel of Euclidean distance (ED) between feature vector and neuron’s center, and so forth.
Wasim Aftab, Muhammad Moinuddin, Muhammad Shafique Shaikh   +2 more
openaire   +4 more sources

Artificial Neural Network Approaches for Predicting the Heat Transfer in a Mini-Channel Heatsink with Alumina/Water Nanofluid [PDF]

Journal of Heat and Mass Transfer Research
This work uses artificial neural networks to evaluate heat transfer in a mini-channel heatsink using an alumina/water nanofluid. The multi-layer perceptron (MLP) and radial basis function (RBF) neural networks are employed for the modeling.
Mohammad Mahdi Tafarroj, Seyed Soheil Mousavi Ajarostaghi, C.J. Ho, Wei-Mon Yan   +3 more
doaj   +1 more source

Parallel implementation of RBF neural networks [PDF]

, 1996
This report presents several parallel implementations, on a MIMD machine, of a learning algorithm called OLS (Orthogonal Least Squares) for RBF (Radial Basis Function) neural networks. The sequential version is first described, and a straightforward parallel version is proposed.
V. Demian, F. Desprez, H. Paugam-Moisy, M. Pourzandi   +3 more
openaire   +1 more source

Efficient training of RBF neural networks for pattern recognition [PDF]

IEEE Transactions on Neural Networks, 2001
The problem of training a radial basis function (RBF) neural network for distinguishing two disjoint sets in R(n) is considered. The network parameters can be determined by minimizing an error function that measures the degree of success in the recognition of a given number of training patterns.
F. LAMPARIELLO, SCIANDRONE, MARCO
openaire   +5 more sources

Prediction in Photovoltaic Power by Neural Networks [PDF]

, 2017
The ability to forecast the power produced by renewable energy plants in the short and middle term is a key issue to allow a high-level penetration of the distributed generation into the grid infrastructure. Forecasting energy production is mandatory for
Altilio, Rosa, Araneo, Rodolfo, Panella, Massimo, Rosato, Antonello   +3 more
core   +1 more source

GRNN-Based Scattering Parameter Modeling Investigation for HBT at Different Temperature

IEEE Access, 2023
In this paper, the scattering parameter (S-parameter) modeling method for heterojunction bipolar transistor (HBT) at different temperatures is investigated. S-parameters of HBT at different temperatures are randomly divided into training and testing sets,
Qian Lin, Xiao-Zheng Wang, Hai-Feng Wu
doaj   +1 more source

Using growing RBF-nets in rubber industry process control [PDF]

, 2010
This paper describes the use of a Radial Basis Function (RBF) neural network in the approximation of process parameters for the extrusion of a rubber profile in tyre production. After introducing the rubber industry problem, the RBF network model and the
Brause, Rüdiger W., Pietruschka, Ulf
core  

Transistor‐Level Activation Functions via Two‐Gate Designs: From Analog Sigmoid and Gaussian Control to Real‐Time Hardware Demonstrations

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, Youngmin Han, Won Woo Lee, Youngwoo Yoo, Kannan Udaya Mohanan, Chang‐Hyun Kim, Junhwan Choi, Young‐Joon Kim, Wonjun Shin, Hocheon Yoo   +9 more
wiley   +1 more source

A State‐Adaptive Koopman Control Framework for Real‐Time Deformable Tool Manipulation in Robotic Environmental Swabbing

Advanced Robotics Research, EarlyView.
This work presents a state‐adaptive Koopman linear quadratic regulator framework for real‐time manipulation of a deformable swab tool in robotic environmental sampling. By combining Koopman linearization, tactile sensing, and centroid‐based force regulation, the system maintains stable contact forces and high coverage across flat and inclined surfaces.
Siavash Mahmoudi, Amirreza Davar, Dongyi Wang   +2 more
wiley   +1 more source

Structural parameter optimization of radial basis function neural network based on improved genetic algorithm and cost function model

Advances in Mechanical Engineering
This paper investigates the structural parameter optimization of RBF networks with the goal of economic control. The cost function and its implementation method are analyzed, and the cost function model of RBF neural network is established.
Lianhui Li, Adham Manyara, Jie Liu
doaj   +1 more source