This book comprises a selection of papers that were first presented at VSS98 (5th International Workshop on Variable Structure Systems) held in Sarasota, Florida. This workshop was the fifth in a series of VSS international workshops, and the first to be held in the United States. Work presented herein on theoretical developments and applications on VSS and Sliding Mode, reflects how trends have advanced beyond the original ideas that are now well documented in a number of books and research monographs. In particular, the concepts of Sliding Sector and Second Order Sliding Mode introduced in...

This book presents the proceedings of the 6th International Symposium on Experimental Robotics held in Sydney in March 1999. The editors and contributors represent the leading robotics research efforts from around the world. Micro-machines, interplanetary exploration, minimally invasive surgery and emerging humanoid robots are among the most obvious attainments of leading robotics research teams reported in this volume. Less obvious but equally significant are the fundamental advances in robot map-building and methods of communication between humans and machines that are demonstrated through...

Human Error and System Design and Management contains a collection of contributions presented at an international workshop with the same name held from March 24-26, 1999 at the Technical University of Clausthal, Germany. The purpose of this workshop was to discuss the results of a research project investigating the "Influences of Human-Machine-Interfaces on the Error-proneness of Operator Interaction with Technical Systems" in a broad context. Therefore experts from academia and industry were invited to participate so that practical as well as theoretical aspects of the subject matter...

This book develops the necessary mathematical background and basic results in control theory that are needed to set up and solve a class of multiple objective control design problems. Exact solutions for certain problems are provided, as well as approximations to more general problems. This book is intended for engineering and mathematics graduate students who are interested in control theory and the application of functional analysis and optimization tools to engineering problems.

Folding networks, a generalization of recurrent neural networks to tree structured inputs, are investigated as a mechanism to learn regularities on classical symbolic data, for example. The architecture, the training mechanism, and several applications in different areas are explained. After wards a theoretical foundation, proving that the approach is appropriate as a learning mechanism in principle, is presented: Their universal approximation ability is investigated - including several new results for standard recurrent neural networks such as explicit bounds on the required number of...

Modern methods of filter design and controller design often yield systems of very high order, posing a problem for their implementation. Over the past two decades or so, sophisticated methods have been developed to achieve simplification of filters and controllers. Such methods often come with easy-to-use error bounds, and in the case of controller simplification methods, such error bounds will usually be related to closed-loop properties.
This book is the first comprehensive treatment of approximation methods for filters and controllers. It is fully up to date, and it is authored by two...

Automatie object recognition is a multidisciplinary research area using con cepts and tools from mathematics, computing, optics, psychology, pattern recognition, artificial intelligence and various other disciplines. The purpose of this research is to provide a set of coherent paradigms and algorithms for the purpose of designing systems that will ultimately emulate the functions performed by the Human Visual System (HVS). Hence, such systems should have the ability to recognise objects in two or three dimensions independently of their positions, orientations or scales in the image. The HVS...

This volume provides students, researchers and application developers with the knowledge and tools to get the most out of using neural networks and related data modelling techniques to solve pattern recognition problems. Each chapter covers a group of related pattern recognition techniques and includes a range of examples to show how these techniques can be applied to solve practical problems.

Features of particular interest include:

- A NETLAB toolbox which is freely available
- Worked examples, demonstration programs and over 100 graded exercises
- Cutting edge...

Directly oriented towards real practical application, this book develops both the basic theoretical framework of extreme value models and the statistical inferential techniques for using these models in practice. Intended for statisticians and non-statisticians alike, the theoretical treatment is elementary, with heuristics often replacing detailed mathematical proof. Most aspects of extreme modeling techniques are covered, including historical techniques (still widely used) and contemporary techniques based on point process models. A wide range of worked examples, using genuine datasets,...

Many practical control problems are dominated by characteristics  such as  state, input and operational constraints, alternations between different operating regimes, and the interaction of continuous-time and discrete event systems. At present no methodology is available to design controllers  in a systematic manner for such systems. This book introduces a new design theory for controllers for such constrained and switching dynamical systems and leads to algorithms that systematically solve control synthesis problems. The first part  is a self-contained introduction to...