Canonical models in mathematical neuroscience.
Cognition: Differential-geometrical view on neural networks.
Comparison of supervised learning methods for spike time coding in spiking neural networks
In this review we focus our attention on supervised learning methods for spike time coding in Spiking Neural Networks (SNNs). This study is motivated by recent experimental results regarding information coding in biological neural systems, which suggest that precise timing of individual spikes may be essential for efficient computation in the brain. We are concerned with the fundamental question: What paradigms of neural temporal coding can be implemented with the recent learning methods? In order...
Complete classification and stability of equilibria in a delayed ring network.
Convergence analysis for principal component flows
A common framework for analyzing the global convergence of several flows for principal component analysis is developed. It is shown that flows proposed by Brockett, Oja, Xu and others are all gradient flows and the global convergence of these flows to single equilibrium points is established. The signature of the Hessian at each critical point is determined.
Convergence and periodicity in a delayed network of neurons with threshold nonlinearity.
Convergence and periodicity of solutions for a class of difference systems.
Convergence of batch split-complex backpropagation algorithm for complex-valued neural networks.
Convergence of Cohen-Grossberg neural networks with delays and time-varying coefficients.