Synapses underlie rapid and flexible neural communication in the brain and they hold the key to understanding higher brain functions in health and disease. Because they are very small and highly dynamic, it is very difficult to study them with traditional techniques. Fortunately, recent ground-breaking advances in optical microscopy (e.g....

This brief monograph is the first one to deal exclusively with the quantitative approximation by artificial neural networks to the identity-unit operator. Here we study with rates the approximation properties of the "right" sigmoidal and hyperbolic tangent artificial neural network positive linear operators. In particular we study...

Soft computing, as a collection of techniques exploiting approximation and tolerance for imprecision and uncertainty in traditionally intractable problems, has become very effective and popular especially because of the synergy derived from its components. The integration of constituent technologies provides complementary methods that allow...

The book presents some of the most efficient statistical and deterministic methods for information processing and applications in order to extract targeted information and find hidden patterns. The techniques presented range from Bayesian approaches and their variations such as sequential Monte Carlo methods, Markov Chain Monte Carlo filters,...

• Go beyond the theory and put Deep Learning into practice with Java
• Find out how to build a range of Deep Learning algorithms...