This volume contains the collected papers of the NATO Advanced Research Workshop on neurocomputing held in Les Arcs in February 1989. Various fields in neurocomputing are covered, including: - new or improved neural network algorithms: product units, recurrent multilayer networks, Boltzmann machines, Kohonen maps, growth algorithms; - topics in neural architectures: VLSI circuits, VLSI neurons, dedicated processors; - applications in speech processing: coding, link with hidden Markov Models (HMM), recognition, compression; - applications in image processing: recognition of digits, wind maps, mammographic images, compression; - models in neurobiology: cortical columns, posture, movement coordination. The book can be read at various levels. Newcomers will find in it a useful introduction to the field through the major papers, by leading scientists, and the collected bibliography at the end of the volume. Specialists will learn about some of the more advanced applications, architectures, chip designs and new algorithms. The book will interest all neural network scientists who wish to know what is happening in Europe.

The NATO Advanced Study Institute (ASI) on Face Recognition: From Theory to Applications took place in Stirling, Scotland, UK, from June 23 through July 4, 1997. The meeting brought together 95 participants (including 18 invited lecturers) from 22 countries. The lecturers are leading researchers from academia, govemment, and industry from allover the world. The lecturers presented an encompassing view of face recognition, and identified trends for future developments and the means for implementing robust face recognition systems. The scientific programme consisted of invited lectures, three panels, and (oral and poster) presentations from students attending the AS . As a result of lively interactions between the participants, the following topics emerged as major themes of the meeting: (i) human processing of face recognition and its relevance to forensic systems, (ii) face coding, (iii) connectionist methods and support vector machines (SVM), (iv) hybrid methods for face recognition, and (v) predictive learning and performance evaluation. The goals of the panels were to provide links among the lectures and to emphasis the themes of the meeting. The topics of the panels were: (i) How the human visual system processes faces, (ii) Issues in applying face recognition: data bases, evaluation and systems, and (iii) Classification issues involved in face recognition. The presentations made by students gave them an opportunity to receive feedback from the invited lecturers and suggestions for future work.