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Everything about Radial basis function network
Type of artificial neural network
In the field of mathematical modeling, a radial basis function network is an artificial neural network that uses radial basis functions as activation functions. The output of the network is a linear combination of radial basis functions of the inputs and neuron parameters. Radial basis function networks have many uses, including function approximation, time series prediction, classification, and system control. They were first formulated in a 1988 paper by Broomhead and Lowe, both researchers at the Royal Signals and Radar Establishment. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Radial basis function networkA 5-minute orientation
- Skim a recent paper: Mixed Radial Basis Function Neural Network Training Using Genetic AlgorithmInfluential work since 2022
- Pick up a classic book: Neural Information ProcessingThe most-reprinted book on the subject
- Read the landmark paper: Radial basis function network configuration using genetic algorithmsCited 212 times
- Go sideways: Hyper basis function networkA closely related topic
- Go sideways: Radial basis functionA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Radial basis function network configuration using genetic algorithms
Radial-Basis-Function-Based Neural Network for Harmonic Detection
Median radial basis function neural network
Radial Basis Function Neural Network for Modeling Rating Curves
A radial basis function neural network controller for UPFC
Recurrent radial basis function network for time-series prediction
Radial basis function (RBF) network adaptive power system stabilizer
Scale-based clustering using the radial basis function network
🆕 Influential since 2022
Mixed Radial Basis Function Neural Network Training Using Genetic Algorithm
An Aeromagnetic Compensation Algorithm Based on Radial Basis Function Artificial Neural Network
Ensemble models based on radial basis function network for landslide susceptibility mapping
Energy processes prediction by a convolutional radial basis function network
An obsolescence forecasting method based on improved radial basis function neural network
📚 Books worth reading
Neural Information ProcessingTingwen Huang · 2012
The Elements of Statistical LearningTrevor Hastie, Robert Tibshirani · 2001
Gaussian processes for machine learningCarl Edward Rasmussen · 2005
Automated EEG-based diagnosis of neurological disordersHojjat Adeli · 2010
A Brief Introduction to Neural NetworksDavid Kriesel · 2007
Neuro-fuzzy and soft computingJyh-Shing Roger Jang, Chuen-Tsai Sun · 1996
Evolutionary Computation, Machine Learning and Data Mining in BioinformaticsLeonardo Vanneschi · 2012
Regularized radial basis function networksPaul Van Yee, Paul V. Yee · 2001
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
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- Hierarchical RBF In computer graphics, hierarchical RBF is an interpolation method based on radial basis functions (RBFs). Hierarchical RBF interpolation has applications…