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ISMIS
2000
Springer
13 years 11 months ago
Design of Rough Neurons: Rough Set Foundation and Petri Net Model
This paper introduces the design of rough neurons based on rough sets. Rough neurons instantiate approximate reasoning in assessing knowledge gleaned from input data. Each neuron c...
James F. Peters, Andrzej Skowron, Zbigniew Suraj, ...
IJON
2006
123views more  IJON 2006»
13 years 7 months ago
A novel approach to model neuronal signal transduction using stochastic differential equations
We introduce a new approach to model the behavior of neuronal signal transduction networks using stochastic differential equations. We present first a mathematical formulation for...
Tiina Manninen, Marja-Leena Linne, Keijo Ruohonen
IJON
2000
76views more  IJON 2000»
13 years 7 months ago
Fast neural network simulations with population density methods
The complexity of neural networks of the brain makes studying these networks through computer simulation challenging. Conventional methods, where one models thousands of individua...
Duane Q. Nykamp, Daniel Tranchina
NECO
2010
147views more  NECO 2010»
13 years 6 months ago
Connectivity, Dynamics, and Memory in Reservoir Computing with Binary and Analog Neurons
Abstract: Reservoir Computing (RC) systems are powerful models for online computations on input sequences. They consist of a memoryless readout neuron which is trained on top of a ...
Lars Büsing, Benjamin Schrauwen, Robert A. Le...
IJCNN
2006
IEEE
14 years 1 months ago
Event modeling of message interchange in stochastic neural ensembles
— We propose a modeling framework based on the event-driven paradigm for populations of neurons which interchange messages. Unlike other strategies our approach is focused on the...
Vicenç Gómez, Andreas Kaltenbrunner,...