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» Evolving Multilayer Perceptrons
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IEAAIE
2004
Springer
15 years 2 months ago
Data Mining Approach for Analyzing Call Center Performance
Abstract. The aim of our research was to apply well-known data mining techniques (such as linear neural networks, multi-layered perceptrons, probabilistic neural networks, classifi...
Marcin Paprzycki, Ajith Abraham, Ruiyuan Guo, Srin...
ROBOCUP
2004
Springer
95views Robotics» more  ROBOCUP 2004»
15 years 2 months ago
Visual Robot Detection in RoboCup Using Neural Networks
Abstract. Robot recognition is a very important point for further improvements in game-play in RoboCup middle size league. In this paper we present a neural recognition method we d...
Ulrich Kaufmann, Gerd Mayer, Gerhard K. Kraetzschm...
IJCNN
2000
IEEE
15 years 1 months ago
On Derivation of MLP Backpropagation from the Kelley-Bryson Optimal-Control Gradient Formula and Its Application
The well-known backpropagation (BP) derivative computation process for multilayer perceptrons (MLP) learning can be viewed as a simplified version of the Kelley-Bryson gradient f...
Eiji Mizutani, Stuart E. Dreyfus, Kenichi Nishio
IJCNN
2000
IEEE
15 years 1 months ago
The Inefficiency of Batch Training for Large Training Sets
Multilayer perceptrons are often trained using error backpropagation (BP). BP training can be done in either a batch or continuous manner. Claims have frequently been made that bat...
D. Randall Wilson, Tony R. Martinez
ISCAS
1999
IEEE
114views Hardware» more  ISCAS 1999»
15 years 1 months ago
Channel equalization by feedforward neural networks
A signal su ers from nonlinear, linear, and additive distortion when transmitted through a channel. Linear equalizers are commonly used in receivers to compensate for linear chann...
Biao Lu, Brian L. Evans