Organized and supported by IIASS and other Italian institutions, this Workshop in Vietri sul Mare has now become a permanent annual event. The aim is to foster closer links among all groups and individuals working in Europe in this inter- and multi-disciplinary area. Topics cover models, architectures and applications.

The textbook aims to present general relativity and modern cosmology in a friendly form suitable for advanced undergraduates. The text begins with a self-contained introduction to the theory of manifolds and then develops the tools needed to understand curved spaces and curved spacetimes. Special relativity can then be understood in a geometrical context, bypassing some of the difficulties students have when encountering relativistic effects (e.g. time dilation and length contraction) for the first time. The theory of curvature and its effects leads to the Einstein field equations and its classic tests in the precession of Mercury and the deflection of starlight.The second part of the book covers modern cosmology, starting with the evolution equations for the expansion of the universe. The microwave background, evidence for dark matter, and the clustering of galaxies are examined in detail.

The proceedings of this workshop include invited lectures by Professors Stan Gielen and Lotfi Zadeh. The workshop was the last to be organised by the late Professor Eduardo R. Cainello, known worldwide for his fundamental contributions to cybernetics and theoretical physics, and to whom this volume is dedicated.

The book we have at hand is the fourth monograph I wrote for Springer Verlag. The previous one named "Self-Organization and Associative Mem ory" (Springer Series in Information Sciences, Volume 8) came out in 1984. Since then the self-organizing neural-network algorithms called SOM and LVQ have become very popular, as can be seen from the many works re viewed in Chap. 9. The new results obtained in the past ten years or so have warranted a new monograph. Over these years I have also answered lots of questions; they have influenced the contents of the present book. I hope it would be of some interest and help to the readers if I now first very briefly describe the various phases that led to my present SOM research, and the reasons underlying each new step. I became interested in neural networks around 1960, but could not in terrupt my graduate studies in physics. After I was appointed Professor of Electronics in 1965, it still took some years to organize teaching at the uni versity. In 1968 - 69 I was on leave at the University of Washington, and D. Gabor had just published his convolution-correlation model of autoasso ciative memory. I noticed immediately that there was something not quite right about it: the capacity was very poor and the inherent noise and crosstalk were intolerable. In 1970 I therefore sugge~ted the auto associative correlation matrix memory model, at the same time as J.A. Anderson and K. Nakano.

This volume contains the proceedings of the 7ICIAP held in Monopoli, Italy.Some of the Areas Covered Include: Active Vision, Computer Vision System; Data Structures and Representations; Feature Extraction; Geometric Modelling; Human Perception and Computer Vision; Image Analysis; Language for Image Modelling; Processing and Retrieval; Motion Analysis and Time Varying Images; Neurocomputing for Recognition; Parallel Computer Architecture; Pattern Recognition; Picture and Video Coding.

This book contains 22 long papers and 13 short ones selected for the Scientific Track of the Third Congress of the Italian Association for Artificial Intelligence. The long papers report completed work whereas the short papers are mainly devoted to ongoing research. The papers report significant work carried out in the different subfields of artificial intelligence not only in Italy but also elsewhere: 8 of the papers come from outside Italy, with 2 from the United States and 1 eachfrom Australia, Austria, Germany, The Netherlands, Spain, and Turkey. The papers in the book are grouped into parts on: automated reasoning; cognitive models; connectionist models and subsymbolic approaches; knowledge representation and reasoning; languages, architectures and tools for AI; machine learning; natural language; planning and robotics; and reasoning about physical systems and artifacts.

This Festschrift volume in honour of Prof. E R Caianiello contains invited papers of eminent scientists who have worked in the several areas to which Prof. Caianiello has given seminal contributions: quantum field theory, foundations of quantum mechanics and maximal acceleration (Vol. 1); neural nets, general systems theory and various topics of cybernetics (Vol. 2). The wide range of topics covered shows the fruitfulness of a higher unifying perspective on seemingly diverse subjects.

Perceptual processes in humans and machines, investigated and simulated by means of the computational approach, are the subject matter of this volume. Researchers in artificial intelligence, pattern recognition, and psychology discuss aspects of vision, speech understanding, sensory-motor coordination, and their interplay with cognitive and behavioral functionalities. The papers adopt the computational approach as the basic research paradigm. Connectionist models, numerical and statistical techniques, symbolic (logic-based) formalisms, and hybrid representations provide the formal background to the research. Some of the papers were prepared for a workshop held in Trieste, Italy, in October 1992.

The present volume is a natural follow-up to Neural Networks: Advances and Applications which appeared one year previously. As the title indicates, it combines the presentation of recent methodological results concerning computational models and results inspired by neural networks, and of well-documented applications which illustrate the use of such models in the solution of difficult problems. The volume is balanced with respect to these two orientations: it contains six papers concerning methodological developments and five papers concerning applications and examples illustrating the theoretical developments. Each paper is largely self-contained and includes a complete bibliography. The methodological part of the book contains two papers on learning, one paper which presents a computational model of intracortical inhibitory effects, a paper presenting a new development of the random neural network, and two papers on associative memory models. The applications and examples portion contains papers on image compression, associative recall of simple typed images, learning applied to typed images, stereo disparity detection, and combinatorial optimisation.

This publication deals with the application of advanced digital signal processing techniques and neural networks to various telecommunication problems. The editor presents the latest research results in areas such as arrays, mobile channels, acoustic echo cancellation, speech coding and adaptive filtering in varying environments.