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» Modeling self-developing biological neural networks
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IJCNN
2007
IEEE
14 years 1 months ago
Odor Recognition with Synchronization using Integrate and Fire Neurons
— We constructed a new model of an olfactory system with expanded integrate and fire neurons to explore its behaviors with external inputs. The model is built in according to th...
Xiaobin Lin, Philippe De Wilde
JMLR
2010
140views more  JMLR 2010»
13 years 1 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
IJCNN
2006
IEEE
14 years 22 days ago
Shaping Realistic Neuronal Morphologies: An Evolutionary Computation Method
— Neuronal morphology plays a crucial role in the information processing capabilities of neurons. Despite the importance of morphology for neural functionality, biological data i...
Ben Torben-Nielsen, Karl Tuyls, Eric O. Postma
BIOCOMP
2008
13 years 8 months ago
Reverse Engineering Module Networks by PSO-RNN Hybrid Modeling
Background: Inferring a gene regulatory network (GRN) from high throughput biological data is often an under-determined problem and is a challenging task due to the following reas...
Yuji Zhang, Jianhua Xuan, Benildo de los Reyes, Ro...
GECCO
1999
Springer
130views Optimization» more  GECCO 1999»
13 years 11 months ago
Heterochrony and Adaptation in Developing Neural Networks
This paper discusses the simulation results of a model of biological development for neural networks based on a regulatory genome. The model’s results are analyzed using the fra...
Angelo Cangelosi