This paper presents a parallel architecture for a radial basis function (RBF) neural network used for pattern recognition. This architecture allows defining sub-networks which can be activated sequentially. It can be used as a fruitful classification mechanism in many application fields. Several implementations of the network on a Xilinx FPGA Virtex 4 - (xc4vsx25) are presented, with speed and area evaluation metrics. Some network improvements have been achieved by segmenting the critical path. The results expressed in terms of speed and area are satisfactory and have been applied to pattern recognition problems.IV Workshop Arquitectura, Redes y Sistemas Operativos (WARSO)Red de Universidades con Carreras en Informática (RedUNCI
This research investigates a digital hardware oriented system that uses a genetic algorithm (GA) fo...
In this paper we discuss the learning problem of Radial Basis Function (RBF) Neural Networks. We pro...
Colloque avec actes et comité de lecture. internationale.International audienceNeural networks are c...
This paper presents a parallel architecture for a radial basis function (RBF) neural network used fo...
This paper presents a parallel architecture for a radial basis function (RBF) neural network used fo...
Abstract. This paper presents a parallel architecture for a radial basis function (RBF) neural netwo...
This paper presents the work regarding the implementation of neural network using radial basis funct...
Radial Basis Function Neural Networks (RBFNN) are used in variety of applications such as pattern re...
In this paper we present design and analysis of scalable hardware architectures for training learnin...
A scalable and reconfigurable architecture for accelerating classification using Radial Basis Functi...
Neural networks (NNs) have been used in several areas, showing their potential but also their limita...
Neural networks are family statistical learning algorithms and structures and are used to estimate o...
Radial basis function neural networks (RBF neural networks), as an alternative to multilayer percept...
This paper presents a novel VLSI architecture for the training of radial basis function (RBF) networ...
In the context of pattern classification, the success of a classification scheme often depends on th...
This research investigates a digital hardware oriented system that uses a genetic algorithm (GA) fo...
In this paper we discuss the learning problem of Radial Basis Function (RBF) Neural Networks. We pro...
Colloque avec actes et comité de lecture. internationale.International audienceNeural networks are c...
This paper presents a parallel architecture for a radial basis function (RBF) neural network used fo...
This paper presents a parallel architecture for a radial basis function (RBF) neural network used fo...
Abstract. This paper presents a parallel architecture for a radial basis function (RBF) neural netwo...
This paper presents the work regarding the implementation of neural network using radial basis funct...
Radial Basis Function Neural Networks (RBFNN) are used in variety of applications such as pattern re...
In this paper we present design and analysis of scalable hardware architectures for training learnin...
A scalable and reconfigurable architecture for accelerating classification using Radial Basis Functi...
Neural networks (NNs) have been used in several areas, showing their potential but also their limita...
Neural networks are family statistical learning algorithms and structures and are used to estimate o...
Radial basis function neural networks (RBF neural networks), as an alternative to multilayer percept...
This paper presents a novel VLSI architecture for the training of radial basis function (RBF) networ...
In the context of pattern classification, the success of a classification scheme often depends on th...
This research investigates a digital hardware oriented system that uses a genetic algorithm (GA) fo...
In this paper we discuss the learning problem of Radial Basis Function (RBF) Neural Networks. We pro...
Colloque avec actes et comité de lecture. internationale.International audienceNeural networks are c...