IAJIT
2010
13 years 11 months ago
2010
: This paper describes the development of neural network models for noise reduction. The networks used to enhance the performance of modeling captured signals by reducing the effec...
ECCC
2000
14 years 12 days ago
2000
A simple extension of standard neural network models is introduced which provides a model for neural computations that involve both firing rates and firing correlations. Such an ex...
TNN
2008
14 years 15 days ago
2008
This paper addresses the problem of the optimal design of numerical experiments for the construction of nonlinear surrogate models. We describe a new method, called learner disagre...
NECO
2008
14 years 16 days ago
2008
Deep Belief Networks (DBN) are generative neural network models with many layers of hidden explanatory factors, recently introduced by Hinton et al., along with a greedy layer-wis...
JUCS
2008
14 years 17 days ago
2008
: This paper describes the development of an Intellectual Property (IP) core in VHDL able to implement a Multilayer Perceptron (MLP) artificial neural network (ANN) topology with u...
JCP
2008
14 years 17 days ago
2008
In this paper, real-time system identification of an unmanned aerial vehicle (UAV) based on multiple neural networks is presented. The UAV is a multi-input multi-output (MIMO) nonl...
ESWA
2008
14 years 20 days ago
2008
In this study, a multistage neural network ensemble learning model is proposed to evaluate credit risk at the measurement level. The proposed model consists of six stages. In the ...
ICTAI
2007
IEEE
14 years 7 months ago
2007
IEEE
The provision of embedding neural networks into software applications can enable variety of Artificial Intelligence systems for individual users as well as organizations. Previous...
WWW
2005
ACM
15 years 1 months ago
2005
ACM
Recent developments in the area of neural networks provided new models which are capable of processing general types of graph structures. Neural networks are well-known for their ...