This text is devoted to adaptive processing of structured information similar to flexible and intelligent information processing by humans. It allows for a mixture of sequential and parallel processing of symbolic as well as sub-symbolic information with deterministic and probabilistic frameworks.

This book is devoted to adaptive processing of structured information similar to flexible and intelligent information processing by humans - in contrast to merely sequential processing of predominantly symbolic information within a deterministic framework. Adaptive information processing allows for a mixture of sequential and parallel processing of symbolic as well as subsymbolic information within deterministic and probabilistic frameworks. The book originates from a summer school held in September 1997 and thus is ideally suited for advanced courses on adaptive information processing and advanced learning techniques or for self-instruction. Research and design professionals active in the area of neural information processing will find it a valuable state-of-the-art survey.

The 15 coherent tutorial chapters contributed by leading authorities from the field of neural networks are organized in parts on architectures and learning in recurrent neural networks, processing of data structures, probabilistic models, analog versus symbolic computation, and applications (in pattern recognition and speech processing).