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Physical Sciences and Mathematics Commons

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Portland State University

Series

2014

Neural networks (Computer science)

Articles 1 - 2 of 2

Full-Text Articles in Physical Sciences and Mathematics

Learning Two-Input Linear And Nonlinear Analog Functions With A Simple Chemical System, Peter Banda, Christof Teuscher Apr 2014

Learning Two-Input Linear And Nonlinear Analog Functions With A Simple Chemical System, Peter Banda, Christof Teuscher

Computer Science Faculty Publications and Presentations

The current biochemical information processing systems behave in a predetermined manner because all features are defined during the design phase. To make such unconventional computing systems reusable and programmable for biomedical applications, adaptation, learning, and self-modification baaed on external stimuli would be highly desirable. However, so far, it haa been too challenging to implement these in real or simulated chemistries. In this paper we extend the chemical perceptron, a model previously proposed by the authors, to function as an analog instead of a binary system. The new analog asymmetric signal perceptron learns through feedback and supports MichaelisMenten kinetics. The results …


Damage Spreading In Spatial And Small-World Random Boolean Networks, Qiming Lu, Christof Teuscher Feb 2014

Damage Spreading In Spatial And Small-World Random Boolean Networks, Qiming Lu, Christof Teuscher

Computer Science Faculty Publications and Presentations

The study of the response of complex dynamical social, biological, or technological networks to external perturbations has numerous applications. Random Boolean networks (RBNs) are commonly used as a simple generic model for certain dynamics of complex systems. Traditionally, RBNs are interconnected randomly and without considering any spatial extension and arrangement of the links and nodes. However, most real-world networks are spatially extended and arranged with regular, power-law, small-world, or other nonrandom connections. Here we explore the RBN network topology between extreme local connections, random small-world, and pure random networks, and study the damage spreading with small perturbations. We find that …