[Illinois]: Optimize Connectivity Profile of Activity-Bubble Network

By Jessica S Johnson1, NanoBio Node1

1. University of Illinois at Urbana-Champaign

Use genetic algorithm with binary chromosomes to optimize activity-bubble network.

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Version 1.0w - published on 18 Mar 2015

doi:10.4231/D3KD1QM34 cite this

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Abstract

This tool uses an algorithm simulating genetic combinations over generations while accounting for random mutation. It produces the minimum accumulated error, the mean error over generations, the most fit and the output responses over generations. The source code for this file is gaBubble.m published online and in Neural Systems Modeling by Thomas J. Anastasio.

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Thomas J. Anastasio - Author Nahil A. Sobh Jessica Johnson

Cite this work

Researchers should cite this work as follows:

  • Jessica S Johnson; NanoBio Node (2015), "[Illinois]: Optimize Connectivity Profile of Activity-Bubble Network," http://nanohub.org/resources/gabubble. (DOI: 10.4231/D3KD1QM34).

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