A perceptron network for functional identification and control of nonlinear systems [0.03%]
非线性系统的功能识别与控制的感知器网络
N Sadegh
N Sadegh
Tracking control of a general class of nonlinear systems using a perceptron neural network (PNN) is presented. The basic structure of the PNN and its training law are first derived. A novel discrete-time control strategy is introduced that ...
A Petrowski,G Dreyfus,C Girault
A Petrowski
The supervised training of feedforward neural networks is often based on the error backpropagation algorithm. The authors consider the successive layers of a feedforward neural network as the stages of a pipeline which is used to improve th...
An improved algorithm for neural network classification of imbalanced training sets [0.03%]
一种改进的神经网络分类算法及其在不平衡数据集中的应用
R Anand,K G Mehrotra,C K Mohan et al.
R Anand et al.
The backpropagation algorithm converges very slowly for two-class problems in which most of the exemplars belong to one dominant class. An analysis shows that this occurs because the computed net error gradient vector is dominated by the bi...
S Wolpert,E Micheli-Tzanakou
S Wolpert
The neurological process known as lateral inhibition (LI) has long been acknowledged as a critical operation for the preprocessing many types of sensory stimuli. In the mammalian retina, LI is utilized to enhance visual images by performing...
Neural networks for shortest path computation and routing in computer networks [0.03%]
用于计算机网络中最短路径计算和路由的神经网络
M M Ali,F Kamoun
M M Ali
The application of neural networks to the optimum routing problem in packet-switched computer networks, where the goal is to minimize the network-wide average time delay, is addressed. Under appropriate assumptions, the optimum routing algo...
On solving constrained optimization problems with neural networks: a penalty method approach [0.03%]
用神经网络求解约束最优化问题的一种罚函数方法
W E Lillo,M H Loh,S Hui et al.
W E Lillo et al.
Deals with the use of neural networks to solve linear and nonlinear programming problems. The dynamics of these networks are analyzed. In particular, the dynamics of the canonical nonlinear programming circuit are analyzed. The circuit is s...
Identification and decentralized adaptive control using dynamical neural networks with application to robotic manipulators [0.03%]
基于动态神经网络的识别与分散自适应控制及其在机器人中的应用
A Karakasoglu,S I Sudharsanan,M K Sundareshan
A Karakasoglu
Efficient implementation of a neural network-based strategy for the online adaptive control of complex dynamical systems characterized by an interconnection of several subsystems (possibly nonlinear) centers on the rapidity of the convergen...
Approximations of continuous functionals by neural networks with application to dynamic systems [0.03%]
连续函数的神经网络逼近及其在动力系统中的应用
T Chen,H Chen
T Chen
The paper gives several strong results on neural network representation in an explicit form. Under very mild conditions a functional defined on a compact set in C[a, b] or L(p)[a, b], spaces of infinite dimensions, can be approximated arbit...
H Bourlard,N Morgan
H Bourlard
Over the period of 1987-1991, a series of theoretical and experimental results have suggested that multilayer perceptrons (MLP) are an effective family of algorithms for the smooth estimation of high-dimension probability density functions ...
Single layer neural networks for linear system identification using gradient descent technique [0.03%]
基于梯度下降技术的线性系统识别单层神经网络
S Bhama,H Singh
S Bhama
Recently, some researchers have focused on the applications of neural networks for the system identification problems. In this letter we describe how to use the gradient descent (GD) technique with single layer neural networks to identify t...