18 June 2015 Experimental analysis of a Lotka-Volterra neural network for classification
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An experimental study of a neural network modeled by an adaptive Lotka-Volterra system follows. With totally inhibitory connections, this system can be embedded in a simple classification network. This network is able to classify and monitor its inputs in a spontaneous nonlinear fashion without prior training. We describe a framework for leveraging this behavior through an example involving breast cancer diagnosis.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Christopher L. Sukhu, Christopher L. Sukhu, Joseph Stanton, Joseph Stanton, Marc Aylesworth, Marc Aylesworth, "Experimental analysis of a Lotka-Volterra neural network for classification", Proc. SPIE 9494, Next-Generation Robotics II; and Machine Intelligence and Bio-inspired Computation: Theory and Applications IX, 94940N (18 June 2015); doi: 10.1117/12.2177214; https://doi.org/10.1117/12.2177214


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