An introduction to symbolic dynamics and coding
An introduction to symbolic dynamics and coding
Dynamical cell assembly hypothesis—theoretical possibility of spatio-temporal coding in the cortex
Neural Networks - 1996 Special issue: four major hypotheses in neuroscience
The handbook of brain theory and neural networks
Crustacean stomatogastric system
The handbook of brain theory and neural networks
RBF neural networks with orthogonal basis functions
Radial basis function networks 1
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Towards Novel Neuroscience-Inspired Computing
Emergent Neural Computational Architectures Based on Neuroscience - Towards Neuroscience-Inspired Computing
| Hi-index | 0.00 |
A new interpretation of the brain chaos is proposed in this paper. The fundamental ideas are grounded in approximation theory. We show how the chaotic brain activity can lead to the emergence of highly precise behavior. To provide a simple example we use the Sierpinski triangles and we introduce the Sierpinski brain. We analyze the learning processes of brains working with chaotic neural objects. We discuss the general implications of the presented work, with special emphasis on messages for AI research.