APPINF
2003
14 years 1 months ago
2003
One of the primary advantages of artificial neural networks is their inherent ability to perform massively parallel, nonlinear signal processing. However, the asynchronous dynamics...
FLAIRS
2006
14 years 1 months ago
2006
In this paper, we apply artificial neural networks to control the targeting system of a robotic tank in a tank-combat computer game (RoboCode). We suggest an algorithm that not on...
ESANN
2006
14 years 1 months ago
2006
The purpose of this study is to identify the Hierarchical Wavelet Neural Networks (HWNN) and select important input features for each sub-wavelet neural network automatically. Base...
ESANN
2006
14 years 1 months ago
2006
Due to the various and dynamic nature of stimuli, decisions of intelligent agents must rely on the coordination of complex cognitive systems. This paper precisely focusses on a gen...
HIS
2004
14 years 1 months ago
2004
Many researchers have observed that neurons process information in an imprecise manner - if a logical inference emerges from neural computation, it is inexact at best. Thus, there...
EGITALY
2006
14 years 1 months ago
2006
Palette re-ordering is a well known and very effective approach for improving the compression of color-indexed images. If the spatial distribution of the indexes in the image is s...
FLAIRS
2004
14 years 1 months ago
2004
This article describes an indirectly encoded evolutionary learning algorithm to train morphological neural networks. The indirect encoding method is an algorithm in which the trai...
DMIN
2006
14 years 1 months ago
2006
- This paper deals with the application of a well-known data mining technique, multi-layer back-propagation neural network, for forecasting of an avalanche in Himalayan region. Met...
DMIN
2006
14 years 1 months ago
2006
Data mining has emerged to be a very important research area that helps organizations make good use of the tremendous amount of data they have. In data classification tasks, fuzzy ...
CDES
2006
14 years 1 months ago
2006
A neural network approach is presented for modeling and characterization of on-chip copper spiral inductors. The approach involves the creation of neural network models to map 3D ...