Sciweavers

NN
2002
Springer
114views Neural Networks» more  NN 2002»
13 years 4 months ago
Learning the parts of objects by auto-association
Recognition-by-components is one of the possible strategies proposed for object recognition by the brain, but little is known about the low-level mechanism by which the parts of o...
Xijin Ge, Shuichi Iwata
RAS
2000
136views more  RAS 2000»
13 years 4 months ago
A comparative study of soft-computing methodologies in identification of robotic manipulators
This paper investigates the identification of nonlinear systems by utilizing soft-computing approaches. As the identification methods, Feedforward Neural Network architecture (FNN...
Mehmet Önder Efe, Okyay Kaynak
IJCSA
2007
213views more  IJCSA 2007»
13 years 4 months ago
Adaptive Depth Control for Autonomous Underwater Vehicles Based on Feedforward Neural Networks
This paper studies the design and application of the neural network based adaptive control scheme for autonomous underwater vehicle's (AUV's) depth control system that i...
Yang Shi, Weiqi Qian, Weisheng Yan, Jun Li
CSL
2007
Springer
13 years 4 months ago
Modeling durations of syllables using neural networks
In this paper, we propose a neural network model for predicting the durations of syllables. A four layer feedforward neural network trained with backpropagation algorithm is used ...
K. Sreenivasa Rao, B. Yegnanarayana
PAKDD
1998
ACM
158views Data Mining» more  PAKDD 1998»
13 years 8 months ago
Data Mining Using Dynamically Constructed Recurrent Fuzzy Neural Networks
Abstract. Approaches to data mining proposed so far are mainly symbolic decision trees and numerical feedforward neural networks methods. While decision trees give, in many cases, ...
Yakov Frayman, Lipo Wang
ICRA
2000
IEEE
85views Robotics» more  ICRA 2000»
13 years 9 months ago
Neural Network Controller for Constrained Robot Manipulators
In this paper, a neural network controller for constrained robot manipulators is presented. A feedforward neural network is used to adaptively compensate for the uncertainties in ...
Shenghai Hu, Marcelo H. Ang, Hariharan Krishnan
IEEEICCI
2002
IEEE
13 years 9 months ago
Quasi-Morphism and Comprehensibility of Rules in Inductive Learning
We present a model of creating a hierarchical set of rules that encode generalizations and exceptions derived from induction learning. The rules use the input features directly an...
Wiphada Wettayaprasit, Chidchanok Lursinsap, Chee-...
ISNN
2004
Springer
13 years 9 months ago
Evolving Flexible Neural Networks Using Ant Programming and PSO Algorithm
A flexible neural network (FNN) is a multilayer feedforward neural network with the characteristics of: (1) overlayer connections; (2) variable activation functions for different...
Yuehui Chen, Bo Yang, Jiwen Dong
FUZZY
2004
Springer
125views Fuzzy Logic» more  FUZZY 2004»
13 years 10 months ago
A Feedforward Neural Network based on Multi-Valued Neurons
A feedforward neural network based on multi-valued neurons is considered in the paper. It is shown that using a traditional feedforward architecture and a high functionality multi-...
Igor N. Aizenberg, Claudio Moraga, Dmitriy Paliy
IWANN
2005
Springer
13 years 10 months ago
Face Recognition System Based on PCA and Feedforward Neural Networks
Face recognition is one of the most important image processing research topics which is widely used in personal identification, verification and security applications. In this pape...
Alaa Eleyan, Hasan Demirel