Add to ORKGThis book presents in detail the newly developed sequential learning algorithm for radial basis function neural networks, which realizes a minimal network. This algorithm, created by the authors, is referred to as Minimal Resource Allocation Networks (MRAN). The book describes the application of MRAN in different areas, including pattern recognition, time series prediction, system identification, control, communication and signal processing. Benchmark problems from these areas have been studied, and MRAN is compared with other algorithms. In order to make the book self-contained, a review of
Radial basis function (RBF) neural network is constructed of certain number of RBF neurons, and thes...
Radial basis function neural networks are used in a variety of applications such as pattern recognit...
Radial basis function neural networks (RBF neural networks), as an alternative to multilayer percept...
This thesis presents a new sequential learning algorithm for realizing a minimal Radial Basis Funct...
This thesis presents the theoretical and experimental analysis of computational complexity and perfo...
This thesis focuses on developing a dynamic minimal radial basis function (RBF) network referred to ...
This thesis presents the application of a minimal radial basis function (RBF) neural network, referr...
This thesis presents the application of a minimal radial basis function (RBF) neural network, referr...
In the context of pattern classification, the success of a classification scheme often depends on th...
Computationally efficient sequential learning algorithms are developed for direct-link resource-allo...
The newal-network training algorithm can be divided into 2 categories: (I) Batch mode and (2) Sequen...
This thesis presents the application of a minimal radial basis function neural network, refered to a...
Abstract. Radial Basis Neural (RBN) network has the power of the universal approximation function an...
This paper extends the sequential learning algorithm strategy of two different types of adaptive ra...
This paper proposes a novel learning algorithm for constructing data classifiers with radial basis f...
Radial basis function (RBF) neural network is constructed of certain number of RBF neurons, and thes...
Radial basis function neural networks are used in a variety of applications such as pattern recognit...
Radial basis function neural networks (RBF neural networks), as an alternative to multilayer percept...
This thesis presents a new sequential learning algorithm for realizing a minimal Radial Basis Funct...
This thesis presents the theoretical and experimental analysis of computational complexity and perfo...
This thesis focuses on developing a dynamic minimal radial basis function (RBF) network referred to ...
This thesis presents the application of a minimal radial basis function (RBF) neural network, referr...
This thesis presents the application of a minimal radial basis function (RBF) neural network, referr...
In the context of pattern classification, the success of a classification scheme often depends on th...
Computationally efficient sequential learning algorithms are developed for direct-link resource-allo...
The newal-network training algorithm can be divided into 2 categories: (I) Batch mode and (2) Sequen...
This thesis presents the application of a minimal radial basis function neural network, refered to a...
Abstract. Radial Basis Neural (RBN) network has the power of the universal approximation function an...
This paper extends the sequential learning algorithm strategy of two different types of adaptive ra...
This paper proposes a novel learning algorithm for constructing data classifiers with radial basis f...
Radial basis function (RBF) neural network is constructed of certain number of RBF neurons, and thes...
Radial basis function neural networks are used in a variety of applications such as pattern recognit...
Radial basis function neural networks (RBF neural networks), as an alternative to multilayer percept...