A novel FOCAL technique based on BP-ANN

In this paper, the feed-forward back-propagation artificial neural network (BP-ANN) algorithm is introduced in the traditional Focus Calibration using Alignment procedure (FOCAL) technique, and a novel FOCAL technique based on BP-ANN is proposed. The effects of the parameters, such as the number of neurons on the hidden-layer and the number of training epochs, on the measurement accuracy are analyzed in detail. It is proved that the novel FOCAL technique based on BP-ANN is more reliable and it is a better choice for measurement of the image quality parameters. (c) 2005 Elsevier GmbH. All rights reserved.

A new development on ANN in China - Biomimetic pattern recognition and multi weight vector neurons

A new model of pattern recognition principles-Biomimetic Pattern Recognition, which is based on "matter cognition" instead of "matter classification", has been proposed. As a important means realizing Biomimetic Pattern Recognition, the mathematical model and analyzing method of ANN get breakthrough: a novel all-purpose mathematical model has been advanced, which can simulate all kinds of neuron architecture, including RBF and BP models. As the same time this model has been realized using hardware; the high-dimension space geometry method, a new means to analyzing ANN, has been researched.

A new development on ANN in China - Biomimetic pattern recognition and multi weight vector neurons

A new model of pattern recognition principles-Biomimetic Pattern Recognition, which is based on "matter cognition" instead of "matter classification", has been proposed. As a important means realizing Biomimetic Pattern Recognition, the mathematical model and analyzing method of ANN get breakthrough: a novel all-purpose mathematical model has been advanced, which can simulate all kinds of neuron architecture, including RBF and BP models. As the same time this model has been realized using hardware; the high-dimension space geometry method, a new means to analyzing ANN, has been researched.