Bücher veröffentlicht von Springer US

Neural Networks in Telecommunications consists of a carefully edited collection of chapters that provides an overview of a wide range of telecommunications tasks being addressed with neural networks. These tasks range from the design and control of the underlying transport network to the filtering, interpretation and manipulation of the transported media. The chapters focus on specific applications, describe specific solutions and demonstrate the benefits that neural networks can provide. By doing this, the authors demonstrate that neural networks should be another tool in the telecommunications engineer's toolbox. Neural networks offer the computational power of nonlinear techniques, while providing a natural path to efficient massively-parallel hardware implementations. In addition, the ability of neural networks to learn allows them to be used on problems where straightforward heuristic or rule-based solutions do not exist. Together these capabilities mean that neural networks offer unique solutions to problems in telecommunications. For engineers and managers in telecommunications, Neural Networks in Telecommunications provides a single point of access to the work being done by leading researchers in this field, and furnishes an in-depth description of neural network applications.

Hybrid Neural Network and Expert Systems presents the basics of expert systems and neural networks, and the important characteristics relevant to the integration of these two technologies. Through case studies of actual working systems, the author demonstrates the use of these hybrid systems in practical situations. Guidelines and models are described to help those who want to develop their own hybrid systems. Neural networks and expert systems together represent two major aspects of human intelligence and therefore are appropriate for integration. Neural networks represent the visual, pattern-recognition types of intelligence, while expert systems represent the logical, reasoning processes. Together, these technologies allow applications to be developed that are more powerful than when each technique is used individually. Hybrid Neural Network and Expert Systems provides frameworks for understanding how the combination of neural networks and expert systems can produce useful hybrid systems, and illustrates the issues and opportunities in this dynamic field.

With the publication of these proceedings from the Second Drug Discovery and Development Symposium, this forum has become the main mechanism for bringing together the principal groups involved in both discovering and developing new approaches to the treatment of cancer. This Second Symposium emphasized the types of materials being discovered and their therapeutic activity. This is especially evident in the natural product discovery programs, where unique and active structures are being identified. The major contributors to the meeting were the investigators participating in the National Cooperative (Natural Products) Drug Discovery Groups [NC(NP)DDG]. These groups reflect an association among researchers at universities or cancer centers, pharmaceutical companies and the National Cancer Institute. Their sources of materials are varied, reflecting chemical inventories of pharmaceutical companies, organic synthetic compounds from the laboratory, cytotoxics as well as biologics and their hybrids, and natural products obtained from plants, marine organisms and microorganisms. The models employed in the discovery systems vary from broadly cellular based to specific enzymes to defined cellular functions. Each of them is believed important to the malignant state and will allow for the discovery of compounds which will have efficacy in cancer therapy. The goal of the participants is both to discover new anticancer agents and to develop them as efficiently as possible into clinically useful additions to treatment. Of importance is the fact that there are a number of promising leads which will soon be moving into the clinic thereby testing the effectiveness of this NC (NP) DDG approach.

The purpose of this book is to introduce VHSIC Hardware Description Lan- guage (VHDL) and its use for synthesis. VHDL is a hardware description language which provides a means of specifying a digital system over different levels of abstraction. It supports behavior specification during the early stages of a design process and structural specification during the later implementation stages. VHDL was originally introduced as a hardware description language that per- mitted the simulation of digital designs. It is now increasingly used for design specifications that are given as the input to synthesis tools which translate the specifications into netlists from which the physical systems can be built. One problem with this use of VHDL is that not all of its constructs are useful in synthesis. The specification of delay in signal assignments does not have a clear meaning in synthesis, where delays have already been determined by the im- plementationtechnolo~y. VHDL has data-structures such as files and pointers, useful for simulation purposes but not for actual synthesis. As a result synthe- sis tools accept only subsets of VHDL. This book tries to cover the synthesis aspect of VHDL, while keeping the simulation-specifics to a minimum. This book is suitable for working professionals as well as for graduate or under- graduate study. Readers can view this book as a way to get acquainted with VHDL and how it can be used in modeling of digital designs.

For more than 30 years, the author has studied the model-theoretic aspects of the theory of valued fields and multi-valued fields. Many of the key results included in this book were obtained by the author whilst preparing the manuscript. Thus the unique overview of the theory, as developed in the book, has been previously unavailable. The book deals with the theory of valued fields and mutli-valued fields. The theory of Prufer rings is discussed from the `geometric' point of view. The author shows that by introducing the Zariski topology on families of valuation rings, it is possible to distinguish two important subfamilies of Prufer rings that correspond to Boolean and near Boolean families of valuation rings. Also, algebraic and model-theoretic properties of multi-valued fields with near Boolean families of valuation rings satisfying the local-global principle are studied. It is important that this principle is elementary, i.e., it can be expressed in the language of predicate calculus. The most important results obtained in the book include a criterion for the elementarity of an embedding of a multi-valued field and a criterion for the elementary equivalence for multi-valued fields from the class defined by the additional natural elementary conditions (absolute unramification, maximality and almost continuity of local elementary properties). The book concludes with a brief chapter discussing the bibliographic references available on the material presented, and a short history of the major developments within the field.