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APPLICATIONS OF RADIAL BASIS NEURAL NETWORKS FOR AREA FOREST
"... Abstract: This paper proposes a new method using radial basis neural networks in order to find the classification and the recognition of trees species for forest inventories. This method computes the wood volume using a set of data easily obtained. The results that are obtained improve the used clas ..."
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Abstract: This paper proposes a new method using radial basis neural networks in order to find the classification and the recognition of trees species for forest inventories. This method computes the wood volume using a set of data easily obtained. The results that are obtained improve the used
Decentralized adaptive control of nonlinear systems using radial basis neural networks
- IEEE Transactions on Automatic Control
, 1999
"... Abstract — Stable direct and indirect decentralized adaptive radial basis neural network controllers are presented for a class of interconnected nonlinear systems. The feedback and adaptation mechanisms for each subsystem depend only upon local measurements to provide asymptotic tracking of a refere ..."
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Cited by 23 (0 self)
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Abstract — Stable direct and indirect decentralized adaptive radial basis neural network controllers are presented for a class of interconnected nonlinear systems. The feedback and adaptation mechanisms for each subsystem depend only upon local measurements to provide asymptotic tracking of a
Modular Radial Basis Neural Network for Stop Consonant Recognition
"... This paper deals with modular radial basis neural networks applying them on stop consonant recognition. The two major areas of concern are the problem of time and the problem of scaling. Speech signals continuously vary over time. To decode these signals we need an appropriate representation of time ..."
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This paper deals with modular radial basis neural networks applying them on stop consonant recognition. The two major areas of concern are the problem of time and the problem of scaling. Speech signals continuously vary over time. To decode these signals we need an appropriate representation
Reformulated Radial Basis Neural Networks Trained by Gradient Descent
, 1999
"... This paper presents an axiomatic approach for constructing radial basis function (RBF) neural networks. This approach results in a broad variety of admissible RBF models, including those employing Gaussian RBFâs. The form of the RBFâs is determined by a generator function. New RBF models can be ..."
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Cited by 32 (1 self)
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This paper presents an axiomatic approach for constructing radial basis function (RBF) neural networks. This approach results in a broad variety of admissible RBF models, including those employing Gaussian RBFâs. The form of the RBFâs is determined by a generator function. New RBF models can
SIGNAL PROCESSING SYSTEM USING RADIAL-BASIS NEURAL NETWORK
"... In digital signal processing there are number of methods for solving interpolation and approximation problems. But the solution of these problems becomes very hard if the processes are complicated and difficult to access. The use modern technology, such as, neural networks allow to avoid these diffi ..."
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these difficulties. In this paper the interpolation of signals and classification of patterns by using radial basis network are considered. The structure and functioning principle of radial basis network that realizes Gaussian function are described. Using measured data the interpolation of oil well’s cross sections
Designing Radial Basis Neural Networks using a Distributed Architecture
"... Abstract:- Radial Basis Neural (RBN) network has the power of the universal approximation function and the convergence of that networks is very fast compared to multilayer feedforward neural networks. However, how to determine the architecture of the RBN networks to solve a given problem is not stra ..."
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Abstract:- Radial Basis Neural (RBN) network has the power of the universal approximation function and the convergence of that networks is very fast compared to multilayer feedforward neural networks. However, how to determine the architecture of the RBN networks to solve a given problem
FUSION REACTOR BURN CONTROL WITH RADIAL BASIS NEURAL NETWORKS: PRELIMINARY RESULTS
"... In previous work [1] a standard feedforward artificial neural network (ANN) with sigmoidal activation functions was used to demonstrate the capabilities of ANN for the stabilization of burn conditions, at nearly ignited conditions, of a thermonuclear reactor operating in the low temperature region. ..."
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In previous work [1] a standard feedforward artificial neural network (ANN) with sigmoidal activation functions was used to demonstrate the capabilities of ANN for the stabilization of burn conditions, at nearly ignited conditions, of a thermonuclear reactor operating in the low temperature region
An agent-driven semantical identifier using radial basis neural networks
"... and reinforcement learning ..."
2 Fuzzy Signature Based Radial Basis Neural Network
, 2011
"... Gedeon and his PhD student Dingyun Zhu. I also thank my friends Huajie Wu and Tengfei ..."
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Gedeon and his PhD student Dingyun Zhu. I also thank my friends Huajie Wu and Tengfei
Growing radial basis neural networks: Merging supervised and unsupervised learning with network growth techniques
- IEEE Transactions on Neural Networks
, 1997
"... Abstract—This paper proposes a framework for constructing and training radial basis function (RBF) neural networks. The proposed growing radial basis function (GRBF) network begins with a small number of prototypes, which determine the locations of radial basis functions. In the process of training, ..."
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Cited by 58 (3 self)
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Abstract—This paper proposes a framework for constructing and training radial basis function (RBF) neural networks. The proposed growing radial basis function (GRBF) network begins with a small number of prototypes, which determine the locations of radial basis functions. In the process of training
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