The human visual system is so incredibly complex that any attempt to understand how the brain processes visual information necessitates a range of approaches, on a number of different levels. Neurophysiological studies, at the single neuron level are required. We need to bring in neuropsychological studies of brain damaged patients in order to understand what different parts of the visual system do, and what each part is needed for. Neuroimaging work can provide valuable information on the locations in the brain where these processes are taking place. Additionally required is an understanding...

The human visual system is so incredibly complex that any attempt to understand how the brain processes visual information necessitates a range of approaches, on a number of different levels. Neurophysiological studies, at the single neuron level are required. We need to bring in neuropsychological studies of brain damaged patients in order to understand what different parts of the visual system do, and what each part is needed for. Neuroimaging work can provide valuable information on the locations in the brain where these processes are taking place. Additionally required is an understanding...

This book originated from a forefront R&D project pursued at Siemens Corporate Technology over the past several years. As a name for this project, we chose "Information Dynamics," which stands for information processing in complex dynamical systems. In the project, we wanted to grasp the flow of information in such systems in a quantitative manner, on the one hand by making use of an existing arsenal of methods and techniques from areas such as information theory, mathematical statistics, neural networks, nonlinear dynamics, probability theory, and statistical physics, and on the other hand...

Neural networks provide a powerful new technology to model and control nonlinear and complex systems. In this book, the authors present a detailed formulation of neural networks from the information-theoretic viewpoint. They show how this perspective provides new insights into the design theory of neural networks. In particular they show how these methods may be applied to the topics of supervised and unsupervised learning including feature extraction, linear and non-linear independent component analysis, and Boltzmann machines. Readers are assumed to have a basic understanding of neural...

This book offers a new, theoretical approach to information dynamics, i.e., information processing in complex dynamical systems. The presentation establishes a consistent theoretical framework for the problem of discovering knowledge behind empirical, dynamical data and addresses applications in information processing and coding in dynamical systems. This will be an essential reference for those in neural computing, information theory, nonlinear dynamics and complex systems modeling.