Prediction of financial time series using artificial neural networks has been the subject of many publications, even if the predictability of financial series remains a subject of ...
Amaury Lendasse, John Aldo Lee, Eric de Bodt, Vinc...
Neural networks use neurons of the same type in each layer but such architecture cannot lead to data models of optimal complexity and accuracy. Networks with architectures (number ...
This paper presents an adaptive colour segmentation algorithm for Sony legged robots to play a football game. A Self-Organizing Map (SOM) is adopted to measure the current lightin...
We have developed models of how strategies are constructed and retained as male and female high school and university students gain experience in solving online qualitative chemic...
Ron Stevens, Amy Soller, Melanie Cooper, Marcia Sp...
Complex networks have received much attention in the last few years, and reveal global properties of interacting systems in domains like biology, social sciences and technology. O...
This paper proposes the methods to solve the constraint satisfaction problems (CSPs) using Q'tron neural networks (NNs). A Q'tron NN is local-minima free if it is built ...
Abstract. Artificial neural networks are intended to be used in future nanoelectronics since their biological examples seem to be robust to noise. In this paper, we analyze the rob...
This study borrowed sequence analysis techniques from the genetic sciences and applied them to a similar problem in email filtering and web searching. Genre identification is the ...
- Pulse-coupled neural network (PCNN) is different from traditional artificial neural networks, which can be applied in many fields, such as image processing. A crucial step in dev...
The way information is represented and processed in a neural network may have important consequences on its computational power and complexity. Basically, information representatio...