A Dual Neural Network for Kinematic Control of Redundant Manipulators Using Input Pattern Switching

2010 ◽  
Vol 63 (1) ◽  
pp. 101-113 ◽  
Author(s):  
Ahmad Reza Khoogar ◽  
Alireza K. Tehrani ◽  
Mehdi Tajdari
Keyword(s):  
Neural Network ◽  
Input Pattern ◽  
Redundant Manipulators ◽  
Kinematic Control

MAGNOCELLULAR PATHWAY FOR ROTATION INVARIANT NEOCOGNITRON

1993 ◽  
Vol 04 (01) ◽  
pp. 43-54 ◽  
Author(s):  
CHRISTOPHER HIAN-ANN TING
Keyword(s):  
Neural Network ◽  
Visual System ◽  
Neural Network Model ◽  
Visual Information ◽  
Input Pattern ◽  
Arbitrary Orientation ◽  
Magnocellular Pathway ◽  
Rotation Invariant ◽  
Parvocellular Pathway ◽  
Simulation Programme

In the mammalian visual system, magnocellular pathway and parvocellular pathway cooperatively process visual information in parallel. The magnocellular pathway is more global and less particular about the details while the parvocellular pathway recognizes objects based on the local features. In many aspects, Neocognitron may be regarded as the artificial analogue of the parvocellular pathway. It is interesting then to model the magnocellular pathway. In order to achieve "rotation invariance" for Neocognitron, we propose a neural network model after the magnocellular pathway and expand its roles to include surmising the orientation of the input pattern prior to recognition. With the incorporation of the magnocellular pathway, a basic shift in the original paradigm has taken place. A pattern is now said to be recognized when and only when one of the winners of the magnocellular pathway is validified by the parvocellular pathway. We have implemented the magnocellular pathway coupled with Neocognitron parallel on transputers; our simulation programme is now able to recognize numerals in arbitrary orientation.

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