Winner-take-all networks of O(N) complexity
Advances in neural information processing systems 1
The roots of backpropagation: from ordered derivatives to neural networks and political forecasting
The roots of backpropagation: from ordered derivatives to neural networks and political forecasting
What is the goal of sensory coding?
Neural Computation
C++ and object-oriented numeric computing for scientists and engineers
C++ and object-oriented numeric computing for scientists and engineers
Spiking Neuron Models: An Introduction
Spiking Neuron Models: An Introduction
Scalable Biologically Inspired Neural Networks with Spike Time Based Learning
LAB-RS '08 Proceedings of the 2008 ECSIS Symposium on Learning and Adaptive Behaviors for Robotic Systems
Which model to use for cortical spiking neurons?
IEEE Transactions on Neural Networks
Detecting load conditions in human walking using expectation maximization and neural networks
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Segmentation and Edge Detection Based on Spiking Neural Network Model
Neural Processing Letters
Cell microscopic segmentation with spiking neuron networks
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part I
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Learning methods for spiking neural networks are not as well developed as the traditional rate based networks, which widely use the back-propagation learning algorithm. We propose and implement an efficient Hebbian learning method with homeostasis for a network of spiking neurons. Similar to STDP, timing between spikes is used for synaptic modification. Homeostasis ensures that the synaptic weights are bounded and the learning is stable. The winner take all mechanism is also implemented to promote competitive learning among output neurons. We have implemented this method in a C++ object oriented code (called CSpike). We have tested the code on four images of Gabor filters and found bell-shaped tuning curves using 36 test set images of Gabor filters in different orientations. These bell-shapes curves are similar to those experimentally observed in the VI and MTN5 area of the mammalian brain.