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(Neural Computation. 2007;19:3293-3309.)
© 2007 The MIT Press


Letter

What Is the Optimal Architecture for Visual Information Routing?

Philipp Wolfrum

wolfrum{at}fias.uni-frankfurt.de Frankfurt Institute for Advanced Studies, D-60438 Frankfurt am Main, Germany

Christoph von der Malsburg

c.v.d.malsburg{at}fias.uni-frankfurt.de Frankfurt Institute for Advanced Studies, D-60438 Frankfurt am Main, Germany, and Computer Science Department, University of Southern California, Los Angeles, CA 90089, U.S.A.

Analyzing the design of networks for visual information routing is an underconstrained problem due to insufficient anatomical and physiological data. We propose here optimality criteria for the design of routing networks. For a very general architecture, we derive the number of routing layers and the fanout that minimize the required neural circuitry. The optimal fanout l is independent of network size, while the number k of layers scales logarithmically (with a prefactor below 1), with the number n of visual resolution units to be routed independently. The results are found to agree with data of the primate visual system.




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J. Lucke, C. Keck, and C. von der Malsburg
Rapid Convergence to Feature Layer Correspondences
Neural Comput., October 1, 2008; 20(10): 2441 - 2463.
[Abstract] [Full Text] [PDF]




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