We present a dynamical architecture for a Radial Basis Function Network. The scheme is based on the Simulated Annealing procedure for learning. Increase of performances with respect to classical methods and opportunity to vary the size of the network are reported....
神经网络的灵敏性测量: W. W. Y. Ng and D. S. Yeung, “Selection of weight quantisation accu- racy for radial basis function neural network using stochastic sensitivity measure,” Inst. Electr. Eng. Electron. Lett., pp. 787–789, 2003 W. W. Y. Ng, D. S. Yeung, X.-Z. Wang, an...
A New Radial Basis Function Networks Structure: Application to Time Series Prediction (PDF) This article describes a new structure to create a RBF neural network; this new structure has four main characteristics: firstly, the special RBF network a... I Rojas,H Pomares,J Gonzalez,... - Inter...
results of the controller design and analysis, including parking problem analysis, stability analysis for the feedback controller, formulation and optimal solution of the parking trajectory planning problem, and design of a parking motion planning architecture based on a radial basis function network. Tw...
Its architecture is very similar to this of the Radial Basis Function neural network (RBF), however it utilizes an entirely different learning algorithm. This algorithm is composed of four main parts: changing positions of reception fields, changing their sizes, insertion of new hidden neurons and...
This paper describes the algorithms applied to a Radial Basis Function (RBF) neural network. This neural network is used as a classifier to design a human face authentication system. The aim of this project is to obtain a low cost system on chip (SoC) to replace password identification for ...
摘要: The sections in this article are 1 Perceptron 2 Multilayer Network 3 Recurrent Network 4 Radial Basis Function Network 5 Neural Networks for Control出版时间: DEC 1999 ISBN: 9780471346081 收藏 引用 批量引用 报错 分享 全部来源 求助全文 Wiley ...
import torch import torch.nn as nn import torch.nn.functional as F # 定义径向基函数层 (RBF) class RadialBasisFunctionLayer(nn.Module): def __init__(self, num_centers, cutoff): super(RadialBasisFunctionLayer, self).__init__() self.centers = nn.Parameter(torch.linspace(0, cutoff, num_...
ML Algorithms(a.k.a. Modelling Phases): The classification algorithms trained include linear (LinSVM) and radial basis function SVM (RbfSVM), k-nearest neighbors (k-nn), and Naïve Bayes (NB). NB is used for text classification and SMS spam detection (similar to Data2Class, Delany, 201...
Decorrelated Hebbian Learning for Clustering and Function Approximation This paper presents a new learning paradigm that consists of a Hebbian and anti-Hebbian learning. A layer of radial basis functions is adapted in an unsupe... G Deco,D Obradovic - 《Neural Computation》 被引量: 6发表: 2014...