Paper
25 November 2014 Fast learning method for RAAM based on sensitivity analysis
Author Affiliations +
Proceedings Volume 9290, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2014; 92902R (2014) https://doi.org/10.1117/12.2074625
Event: Symposium on Photonics Applications in Astronomy, Communications, Industry and High-Energy Physics Experiments, 2014, Warsaw, Poland
Abstract
This article presents a novel combination of the Recursive Auto-Associative Memory model with the Sensitivity- Based Linear Learning Method. Training results on the syntactic trees dataset are presented, confirming that the application of the SBLLM method to the RAAM model results in very fast learning and yields clustering results of the same quality as the original RAAM model.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
A. Barcz "Fast learning method for RAAM based on sensitivity analysis", Proc. SPIE 9290, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2014, 92902R (25 November 2014); https://doi.org/10.1117/12.2074625
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KEYWORDS
Data modeling

Neural networks

Neurons

Error analysis

Image processing

Statistical modeling

Computer programming

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