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The computational limitations of balanced networks

The computational limitations of balanced networks

This video was recorded at 5th European Conference on Complex Systems . Computation in neural networks relies crucially on non-linearity. In neural networks in the balanced state the non-linearity of the neuronal transfer function becomes functionally unimportant. The disappearance of this non- linearity strongly limits the computational power of balanced networks. I will show in examples of balanced networks for associative memory how one can try to circumvent this limitation of balanced networks and discuss the problems with these solutions.
Keywords:
videolectures, ocwc, oec
Disciplines:
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More about this material

Material Type:
Presentation
Date Added to MERLOT:
February 8, 2015
Date Modified in MERLOT:
February 8, 2015
Author:
Submitter:
The Open Education Consortium
Primary Audience:
College General Ed, College Lower Division, College Upper Division
Technical Format:
Video
Mobile Compatibility:
Not specified at this time
Language:
English
Cost Involved:
No
Source Code Available:
No
Creative Commons:
Creative Commons License
This work is licensed under a Attribution-NonCommercial-NoDerivs 3.0 United States

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