Results 1 to 10 of about 265,049 (212)

Learning in Deep Radial Basis Function Networks [PDF]

open access: yesEntropy
Learning in neural networks with locally-tuned neuron models such as radial Basis Function (RBF) networks is often seen as instable, in particular when multi-layered architectures are used. Furthermore, universal approximation theorems for single-layered
Fabian Wurzberger, Friedhelm Schwenker
doaj   +5 more sources

Efficient VLSI Architecture for Training Radial Basis Function Networks [PDF]

open access: yesSensors, 2013
This paper presents a novel VLSI architecture for the training of radial basis function (RBF) networks. The architecture contains the circuits for fuzzy C-means (FCM) and the recursive Least Mean Square (LMS) operations.
Wen-Jyi Hwang, Zhe-Cheng Fan
doaj   +2 more sources

Magnetic Modeling of Synchronous Reluctance and Internal Permanent Magnet Motors Using Radial Basis Function Networks [PDF]

open access: yesIEEE transactions on industrial electronics (1982. Print), 2018
The general trend toward more intelligent energy-aware ac drives is driving the development of new motor topologies and advanced model-based control techniques.
L. Ortombina, F. Tinazzi, M. Zigliotto
semanticscholar   +3 more sources

Radial Basis Function Networks [PDF]

open access: yes, 2017
Radial Basis Function networks, commonly known as RBF, can also be employed in almost every kind of problems solved by MLPs, including those involving curve fitting and pattern classification.
I. Silva   +4 more
semanticscholar   +2 more sources

Filtered-X Radial Basis Function Neural Networks for Active Noise Control [PDF]

open access: yesITB Journal of Engineering Science, 2004
This paper presents active control of acoustic noise using radial basis function (RBF) networks and its digital signal processor (DSP) real-time implementation.
Bambang Riyanto   +2 more
doaj   +3 more sources

RBFNN Design Based on Modified Nearest Neighbor Clustering Algorithm for Path Tracking Control

open access: yesSensors, 2021
Radial basis function neural networks are a widely used type of artificial neural network. The number and centers of basis functions directly affect the accuracy and speed of radial basis function neural networks.
Dongxi Zheng, Wonsuk Jung, Sunghoon Kim
doaj   +1 more source

Estimation of Groundwater Seepage Risks into Tunnel Using Radial Basis Function Networks [PDF]

open access: yesعلوم و مهندسی آبیاری, 2022
In this study, Site Groundwater Rating (SGR) in the Amirkabir tunnel has been estimated using Radial Basis Function Networks (RBFNs). SGR is the first rating method that by considering the parameters like joint frequency, joint aperture, schistosity ...
Hadi Farhadian, Seyed Ahmad Eslaminezhad
doaj   +1 more source

Chess Position Evaluation Using Radial Basis Function Neural Networks

open access: yesComplexity, 2023
The game of chess is the most widely examined game in the field of artificial intelligence and machine learning. In this work, we propose a new method for obtaining the evaluation of a chess position without using tree search and examining each candidate
Dimitrios Kagkas   +2 more
doaj   +1 more source

Snow cover thickness estimation using radial basis function networks [PDF]

open access: yesThe Cryosphere, 2013
This paper reports an experimental study designed for the in-depth investigation of how the radial basis function network (RBFN) estimates snow cover thickness as a function of climate and topographic parameters.
E. Binaghi   +3 more
doaj   +1 more source

Radial Basis Function Cascade Correlation Networks

open access: yesAlgorithms, 2009
A cascade correlation learning architecture has been devised for the first time for radial basis function processing units. The proposed algorithm was evaluated with two synthetic data sets and two chemical data sets by comparison with six other standard
Peter de B. Harrington, Weiying Lu
doaj   +1 more source

Home - About - Disclaimer - Privacy