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ICIC
2007
Springer
14 years 5 months ago
Edge Detection Based on Spiking Neural Network Model
Inspired by the behaviour of biological receptive fields and the human visual system, a network model based on spiking neurons is proposed to detect edges in a visual image. The st...
Qingxiang Wu, T. Martin McGinnity, Liam P. Maguire...
JMLR
2010
140views more  JMLR 2010»
13 years 5 months ago
Learning Non-Stationary Dynamic Bayesian Networks
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
Joshua W. Robinson, Alexander J. Hartemink
COGSR
2011
99views more  COGSR 2011»
13 years 5 months ago
A biologically realistic cleanup memory: Autoassociation in spiking neurons
Methods for cleaning up (or recognizing) states of a neural network are crucial for the functioning of many neural cognitive models. For example, Vector Symbolic Architectures pro...
Terrence C. Stewart, Yichuan Tang, Chris Eliasmith
GECCO
2004
Springer
14 years 4 months ago
Evolved Motor Primitives and Sequences in a Hierarchical Recurrent Neural Network
This study describes how complex goal-directed behavior can evolve in a hierarchically organized recurrent neural network controlling a simulated Khepera robot. Different types of ...
Rainer W. Paine, Jun Tani
AB
2008
Springer
14 years 5 months ago
Neural Algebra and Consciousness: A Theory of Structural Functionality in Neural Nets
Abstract. Thoughts are spatio-temporal patterns of coalitions of firing neurons and their interconnections. Neural algebras represent these patterns as formal algebraic objects, a...
Erwin Engeler