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NIPS
2007
13 years 5 months ago
Learning to classify complex patterns using a VLSI network of spiking neurons
We propose a compact, low power VLSI network of spiking neurons which can learn to classify complex patterns of mean firing rates on–line and in real–time. The network of int...
Srinjoy Mitra, Giacomo Indiveri, Stefano Fusi
NIPS
2007
13 years 5 months ago
Neural characterization in partially observed populations of spiking neurons
Point process encoding models provide powerful statistical methods for understanding the responses of neurons to sensory stimuli. Although these models have been successfully appl...
Jonathan Pillow, Peter E. Latham
NIPS
2008
13 years 5 months ago
Self-organization using synaptic plasticity
Large networks of spiking neurons show abrupt changes in their collective dynamics resembling phase transitions studied in statistical physics. An example of this phenomenon is th...
Vicenç Gómez, Andreas Kaltenbrunner,...
NIPS
2008
13 years 5 months ago
On Computational Power and the Order-Chaos Phase Transition in Reservoir Computing
Randomly connected recurrent neural circuits have proven to be very powerful models for online computations when a trained memoryless readout function is appended. Such Reservoir ...
Benjamin Schrauwen, Lars Buesing, Robert A. Legens...
IJCNN
2000
IEEE
13 years 7 months ago
Unsupervised Classification of Complex Clusters in Networks of Spiking Neurons
For unsupervised clustering in a network of spiking neurons we develop a temporal encoding of continuously valued data to obtain arbitrary clustering capacity and precision with a...
Sander M. Bohte, Johannes A. La Poutré, Joo...
ICANN
1997
Springer
13 years 7 months ago
Correlation Coding in Stochastic Neural Networks
Abstract. Stimulus4ependent changes have been observed in the correlations between the spike trains of simultaneously-recorded pairs of neurons from the auditory cortex of marmoset...
Raphael Ritz, Terrence J. Sejnowski
HYBRID
1998
Springer
13 years 7 months ago
High Order Eigentensors as Symbolic Rules in Competitive Learning
We discuss properties of high order neurons in competitive learning. In such neurons, geometric shapes replace the role of classic `point' neurons in neural networks. Complex ...
Hod Lipson, Hava T. Siegelmann
EVOW
2001
Springer
13 years 8 months ago
Evolution of Spiking Neural Controllers for Autonomous Vision-Based Robots
Abstract. We describe a set of preliminary experiments to evolve spiking neural controllers for a vision-based mobile robot. All the evolutionary experiments are carried out on phy...
Dario Floreano, Claudio Mattiussi
ISNN
2010
Springer
13 years 8 months ago
Visual Selection and Attention Shifting Based on FitzHugh-Nagumo Equations
In this paper, we make some analysis on the FitzHugh-Nagumo model and improve it to build a neural network, and the network is used to implement visual selection and attention shif...
Haili Wang, Yuanhua Qiao, Lijuan Duan, Faming Fang...
BIOADIT
2004
Springer
13 years 9 months ago
Towards Cortex Sized Attractor ANN
We review the structure of cerebral cortex to find out the number of neurons and synapses and its modular structure. The organization of these neurons is then studied and mapped on...
Christopher Johansson, Anders Lansner