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» Training Methods for Adaptive Boosting of Neural Networks
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NCA
2006
IEEE
14 years 9 months ago
Evolutionary training of hardware realizable multilayer perceptrons
The use of multilayer perceptrons (MLP) with threshold functions (binary step function activations) greatly reduces the complexity of the hardware implementation of neural networks...
Vassilis P. Plagianakos, George D. Magoulas, Micha...
AINA
2010
IEEE
14 years 8 months ago
Compensation of Sensors Nonlinearity with Neural Networks
—This paper describes a method of linearizing the nonlinear characteristics of many sensors using an embedded neural network. The proposed method allows for complex neural networ...
Nicholas J. Cotton, Bogdan M. Wilamowski
RAS
2000
136views more  RAS 2000»
14 years 9 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
CCECE
2006
IEEE
15 years 3 months ago
Adaptive Bilateral Control using Operator Elbow Impedance
— Human arm dynamics can be used for control of human-machine interfaces in haptic applications. In this paper, a novel method for online estimation of human operator elbow imped...
Farid Mobasser, Keyvan Hashtrudi-Zaad
IJCNN
2000
IEEE
15 years 2 months ago
Input Window Size and Neural Network Predictors
Neural Network approaches to time series prediction are briefly discussed, and the need to specify an appropriately sized input window identified. Relevant theoretical results fro...
Ray J. Frank, Neil Davey, S. P. Hunt