Self-Organizing Maps (SOM) are very powerful tools for data mining, in particular for visualizing the distribution of the data in very highdimensional data sets. Moreover, the 2D m...
Abstract. This paper proposes a new sliding mode controller using neural networks. Multilayer neural networks with the error back-propagation learning algorithm are used to compens...
In this paper we describe a neural network-based method aimed at automatically calibrating the detector module contained in a scanner for a highresolution positron emission tomogra...
Beatrice Lazzerini, Francesco Marcelloni, Giovanni...
: In this paper we present a new self-tuning procedure for PID controllers based on neuro-predictive control. A finite horizon optimal control problem is solved on-line, permitting...
To emphasize the electrical nature of information processing in the brain we use a compartmental model of single neurons. The realistic simulation of wave-like activity in the recu...
Karsten Kube, Andreas Herzog, Vadym Spravedlyvyy, ...
This paper presents some interesting results obtained by the algorithm by Bauer, Der and Hermann (BDH) [1] for magnification control in Self-Organizing Maps. Magnification control ...
The role of dendritic spines in neuronal information processing is still not completely clear. However, it is known that spines can change shape rapidly during development and duri...
Andreas Herzog, Vadym Spravedlyvyy, Karsten Kube, ...
We derive analytical expressions of local codim-1-bifurcations for a fully connected, additive, discrete-time RNN, where we regard the external inputs as bifurcation parameters. Th...