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EDMONTON, December 11, 1998 - Dendronic Decisions Limited successfully completed a two year research and development contract by the Defence Research Establishment Suffield (DRES) under the title "Development of Adaptive Logic Networks for Pattern Recognition and Control in an Autonomous Vehicle."

The Advanced Guidance Concepts Group (AGCG) at DRES performs research on the use of real-time imagery, visible and infrared, for applications in the guidance and control of autonomous vehicles and for the recognition and classification of targets and landmines.

For these applications, neural network research at DRES has focused on feed-forward and recurrently connected artificial neural networks, composed of sigmoidal processing nodes. Adaptive Logic Networks (ALNs) are an alternative distributed processing technique, using trees of logical processing nodes, that may provide several advantages over the networks studied at DRES.

The successful outcome of this research will create a powerful new tool for the development of advanced autonomous systems for the Canadian Forces, and will open up a wide field of commercial applications in machine and process control in Canadian industry.

Dendronic Decisions Limited is the developer and owner of the Adaptive Logic Networks technology, which learns relationships in data for solutions to analysis, prediction, and control problems. The technology has been used for predicting short term electrical load on the Alberta power grid, controlling computer assisted walking aids, recognising and classifying acoustic signals, estimating fat content in beef from ultrasound images, and detecting fraudulent management behaviour in audit risk assessments. Dendronic’s proprietary pattern recognition technology is rapidly gaining acceptance in the industry where speed and accuracy play an important role. Our solutions continue to provide our clients with unique competitive advantages.

To learn more about the use of ALNs in 3D world modelling and robot navigation, visit the website of Dmitry O. Gorodnichy http://www.cs.ualberta.ca/~dmitri/WorldModeling

 

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Date Modified: March 1, 2003.