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Accuracy versus complexity in RBF neural networks
IEEE Instrumentation & Measurement Magazine, 2001We have introduced a methodology for solving the tradeoff between accuracy and complexity in complex virtual systems directly at the system level. Such methodology can be inserted in an application-level compiler for transforming a high-level description of the application into a lower level.
C. Alippi, V. Piuri, F. Scotti
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Discrete RBF Neural Network Control
2017The discrete-time implementation of controllers is important. There are two methods for designing the digital controller. One method, called emulation, is to design a controller based on the continuous-time system, then discrete the controller.
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Application of PSO-RBF neural network in gesture recognition of continuous surface EMG signals
Journal of Intelligent & Fuzzy Systems, 2019In view of the fact that independent gesture recognition cannot fully meet the natural, convenient and effective needs of actual human-computer interaction, this paper analyzes the current research status of gesture recognition based on EMG signal, and ...
Ming-Chao Yu +6 more
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Fuzzy Calculus by RBF Neural Networks
2003The paper presents novel modeling of fuzzy inference system by using the ‘fuzzified’ radial basis function (RBF) neural network (NN). RBF NN performs the mapping of the antecedent fuzzy numbers (a.k.a. membership functions, attributes, possibilities degrees) into the consequent ones. In this way, an RBF NN is capable of performing the rigorous calculus
Vojislav Kecman, Zhenquan Li
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A Generalized Growing and Pruning RBF (GGAP-RBF) Neural Network for Function Approximation
IEEE Transactions on Neural Networks, 2005This paper presents a new sequential learning algorithm for radial basis function (RBF) networks referred to as generalized growing and pruning algorithm for RBF (GGAP-RBF). The paper first introduces the concept of significance for the hidden neurons and then uses it in the learning algorithm to realize parsimonious networks.
Guang-Bin, Huang +2 more
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RBF Neural Network Case Teaching Research
2011In this paper, the RBF neural network case teaching has been studied. In the actual teaching process, we find it more difficult for student to learn the course, duing to the RBF neural network curriculum theory is more stronger. Many students do not know how to use the theory to solve practical problems.Therefore, we equip students with basic knowledge
JingBing Li +3 more
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An efficient multilayer RBF neural network and its application to regression problems
Neural computing & applications (Print), 2021Qinghua Jiang +3 more
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Cataract Detection and Grading with Retinal Images Using SOM-RBF Neural Network
IEEE Symposium Series on Computational Intelligence, 2019A cataract is the prevailing cause of visual impairment in the modern world. The detection of cataract at early stages can lessen the risk of blindness.
A. Imran +5 more
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RBF Neural Network Design and Simulation
2012This chapter introduces RBF neural network design method, gives RBF neural network approximation algorithm based on gradient descent, analyzes the effects of Gaussian function parameters on RBF approximation, and introduces RBF neural network modeling method based on off-line training. Several simulation examples are given.
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