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Associative spatial networks: Artificial cognition of space using neural networks with spectral graph theory

Harding, John

Authors

John Harding John3.Harding@uwe.ac.uk
External Adviser / Panel Member - SAS



Abstract

This work stems from a backdrop of cybernetics and associative computing closely related to the artificial simulation of the human brain. Using associative techniques, a system to comprehend complex inputs in order to make appropriate architectural interventions is proposed.

A combination of abstract representations of space (graph theory) and a time based neural network clustering model (growing neural gas) are combined to create new spatial configurations based on pattern recognition and relationships formed from differences.

Citation

Harding, J. Associative spatial networks: Artificial cognition of space using neural networks with spectral graph theory. (Dissertation). University of East London. Retrieved from https://uwe-repository.worktribe.com/output/1018920

Thesis Type Dissertation
Keywords self-organising maps, graph spectra, growing neural gas, spatial cognition, feedback
Public URL https://uwe-repository.worktribe.com/output/1018920