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» A spiking neuron model: applications and learning
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ICMLA
2010
13 years 5 months ago
Nonlinear Dynamical Multi-Scale Model of Associative Memory
How can we get such reliable behavior from the mind when the brain is made up of such unreliable elements as neurons? We propose that the answer is related to the emergence of stab...
Alexander M. Duda, Stephen E. Levinson
FUIN
2008
103views more  FUIN 2008»
13 years 7 months ago
Implementing Sorting Networks with Spiking Neural P Systems
Spiking neural P systems simulate the behavior of neurons sending signals through axons. Recently, some applications concerning Boolean circuits and sorting algorithms have been pr...
Rodica Ceterchi, Alexandru Ioan Tomescu
NIPS
2004
13 years 9 months ago
Rate- and Phase-coded Autoassociative Memory
Areas of the brain involved in various forms of memory exhibit patterns of neural activity quite unlike those in canonical computational models. We show how to use well-founded Ba...
Máté Lengyel, Peter Dayan
TNN
1998
112views more  TNN 1998»
13 years 7 months ago
A class of competitive learning models which avoids neuron underutilization problem
— In this paper, we study a qualitative property of a class of competitive learning (CL) models, which is called the multiplicatively biased competitive learning (MBCL) model, na...
Clifford Sze-Tsan Choy, Wan-Chi Siu
ICONIP
2007
13 years 9 months ago
Analog CMOS Circuits Implementing Neural Segmentation Model Based on Symmetric STDP Learning
We proposed a neural segmentation model that is suitable for implementation in analog VLSIs using conventional CMOS technology. The model consists of neural oscillators mutually co...
Gessyca Maria Tovar, Eric Shun Fukuda, Tetsuya Asa...