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SYNASC
2005
IEEE
97views Algorithms» more  SYNASC 2005»
14 years 3 months ago
A Reinforcement Learning Algorithm for Spiking Neural Networks
The paper presents a new reinforcement learning mechanism for spiking neural networks. The algorithm is derived for networks of stochastic integrate-and-fire neurons, but it can ...
Razvan V. Florian
BIOADIT
2004
Springer
14 years 3 months ago
Explaining Low-Level Brightness-Contrast Illusions Using Disinhibition
Conventional Difference of Gaussian (DOG) filter is usually used to model the early stage of visual processing. However, convolution operation used with DOG does not explicitly a...
Yingwei Yu, Takashi Yamauchi, Yoonsuck Choe
SAINT
2003
IEEE
14 years 3 months ago
Implementing Role-based Interactions for Internet Agents
Large-scale distributed environments, such as the Internet, achieve advantages in exploiting software agents for applications, thanks to their autonomy in carrying out tasks. In s...
Giacomo Cabri, Letizia Leonardi, Franco Zambonelli
EUROPAR
2007
Springer
14 years 1 months ago
Efficient Parallel Simulation of Large-Scale Neuronal Networks on Clusters of Multiprocessor Computers
To understand the principles of information processing in the brain, we depend on models with more than 105 neurons and 109 connections. These networks can be described as graphs o...
Hans E. Plesser, Jochen M. Eppler, Abigail Morriso...
CVPR
2008
IEEE
13 years 11 months ago
Probabilistic multi-tensor estimation using the Tensor Distribution Function
Diffusion weighted magnetic resonance (MR) imaging is a powerful tool that can be employed to study white matter microstructure by examining the 3D displacement profile of water m...
Alex D. Leow, Siwei Zhu, Katie McMahon, Greig I. d...