Bücher der Reihe The Springer International Series in Engineering and Computer Science

Effective Polynomial Computation is an introduction to the algorithms of computer algebra. It discusses the basic algorithms for manipulating polynomials including factoring polynomials. These algorithms are discussed from both a theoretical and practical perspective. Those cases where theoretically optimal algorithms are inappropriate are discussed and the practical alternatives are explained. Effective Polynomial Computation provides much of the mathematical motivation of the algorithms discussed to help the reader appreciate the mathematical mechanisms underlying the algorithms, and so that the algorithms will not appear to be constructed out of whole cloth. Preparatory to the discussion of algorithms for polynomials, the first third of this book discusses related issues in elementary number theory. These results are either used in later algorithms (e.g. the discussion of lattices and Diophantine approximation), or analogs of the number theoretic algorithms are used for polynomial problems (e.g. Euclidean algorithm and p-adic numbers). Among the unique features of Effective Polynomial Computation is the detailed material on greatest common divisor and factoring algorithms for sparse multivariate polynomials. In addition, both deterministic and probabilistic algorithms for irreducibility testing of polynomials are discussed.

Most machine learning research has been concerned with the development of systems that implememnt one type of inference within a single representational paradigm. Such systems, which can be called monostrategy learning systems, include those for empirical induction of decision trees or rules, explanation-based generalization, neural net learning from examples, genetic algorithm-based learning, and others. Monostrategy learning systems can be very effective and useful if learning problems to which they are applied are sufficiently narrowly defined. Many real-world applications, however, pose learning problems that go beyond the capability of monostrategy learning methods. In view of this, recent years have witnessed a growing interest in developing multistrategy systems, which integrate two or more inference types and/or paradigms within one learning system. Such multistrategy systems take advantage of the complementarity of different inference types or representational mechanisms. Therefore, they have a potential to be more versatile and more powerful than monostrategy systems. On the other hand, due to their greater complexity, their development is significantly more difficult and represents a new great challenge to the machine learning community. Multistrategy Learning contains contributions characteristic of the current research in this area.

It is a great honor to provide an introduction for Dr. Frank Op 't Eynde's and Dr. Willy Sansen's book "e;Analog Interfaces for Digital Signal Processing Systems"e;. The field of analog integrated circuit design is undergoing rapid evolution. The pervasiveness of digital processing has considerably modified the micro-system architectures: the analog part of complex mixed systems is more and more pushed at the boundary limits of the processing chain. Moreover, the increased performance of digital circuits, in terms of accuracy and speed, are making the specification requirements of analog circuits very strict. In addition to this, the technology, supply voltage and power consumption of analog circuits must be compatible with those, typical for digital circuits. Therefore, in a few words, analog circuits are becoming complex and specialised interfaces between the real world and digital signal processing domains. This technological evolution should be accompanied by an equivalently fast evolution in designer competencies. Knowledge of complicated signal handling should be quickly replaced by know-how of simple but very accurate and very fast signal processing and a solid background in data conversion techniques. All of this through the use of the CMOS (and possibly BiCMOS) technology.

Neural Network Parallel Computing is the first book available to the professional market on neural network computing for optimization problems. This introductory book is not only for the novice reader, but for experts in a variety of areas including parallel computing, neural network computing, computer science, communications, graph theory, computer aided design for VLSI circuits, molecular biology, management science, and operations research. The goal of the book is to facilitate an understanding as to the uses of neural network models in real-world applications. Neural Network Parallel Computing presents a major breakthrough in science and a variety of engineering fields. The computational power of neural network computing is demonstrated by solving numerous problems such as N-queen, crossbar switch scheduling, four-coloring and k-colorability, graph planarization and channel routing, RNA secondary structure prediction, knight's tour, spare allocation, sorting and searching, and tiling. Neural Network Parallel Computing is an excellent reference for researchers in all areas covered by the book. Furthermore, the text may be used in a senior or graduate level course on the topic.

One of the most intriguing questions in image processing is the problem of recovering the desired or perfect image from a degraded version. In many instances one has the feeling that the degradations in the image are such that relevant information is close to being recognizable, if only the image could be sharpened just a little. This monograph discusses the two essential steps by which this can be achieved, namely the topics of image identification and restoration. More specifically the goal of image identifi- cation is to estimate the properties of the imperfect imaging system (blur) from the observed degraded image, together with some (statistical) char- acteristics of the noise and the original (uncorrupted) image. On the basis of these properties the image restoration process computes an estimate of the original image. Although there are many textbooks addressing the image identification and restoration problem in a general image processing setting, there are hardly any texts which give an indepth treatment of the state-of-the-art in this field. This monograph discusses iterative procedures for identifying and restoring images which have been degraded by a linear spatially invari- ant blur and additive white observation noise. As opposed to non-iterative methods, iterative schemes are able to solve the image restoration problem when formulated as a constrained and spatially variant optimization prob- In this way restoration results can be obtained which outperform the lem. results of conventional restoration filters.

Information is always required by organizations of coastal states about the movements, identities and intentions of vessels sailing in the waters of interest to them, which may be coastal waters, straits, inland waterways, rivers, lakes or open seas. This interest may stem from defense requirements or from needs for the protection of off-shore resources, enhanced search and rescue services, deterrence of smuggling, drug trafficking and other illegal activities and/or for providing vessel traffic services for safe and efficient navigation and protection of the environment. To meet these needs it is necessary to have a well designed maritime surveillance and control system capable of tracking ships and providing other types of information required by a variety of user groups ranging from port authorities, shipping companies, marine exchanges to governments and the military. Principles of Integrated Maritime Surveillance Systems will be of vital interest to anyone responsible for the design, implementation or provision of a well designed maritime surveillance and control system capable of tracking ships and providing navigational and other types of information required for safe navigation and efficient commercial operation. Principles of Integrated Maritime Surveillance Systems is therefore essential to a variety of user groups ranging from port authorities to shipping companies and marine exchanges as well as civil governments and the military.

CMOS Current Amplifiers presents design strategies for high performance current amplifiers based on CMOS technology. After an introduction to various architectures of operational amplifiers, the operating principles of the current amplifier are outlined. This book provides the reader with simple and compact design equations for use in a pencil and paper design and the following simulation step. Chapter 1 introduces the general aspects of current amplifiers. After a preliminary classification of operational amplifiers, ideal blocks and models are discussed for different architectures and a first high-level comparison is made between traditional amplifiers and current amplifiers. Analysis and examples of basic circuits, as well as signal processing applications involving current amplifiers, are also given. Non-idealities and second- order effects causing limitations in performance are then discussed and evaluated. Chapter 2 focuses on low-drive current amplifiers. Several design examples for current conveyors and class A current amplifiers are discussed in detail and design equations are presented for the main performance parameters, which allows a good trade-off between requirements. High-performance solutions for high bandwidth and low voltage capability are also considered, and, finally, current comparators with progressively enhanced performance are reported and analyzed critically. Chapter 3 deals with current amplifiers for off-chip loads. Several class AB current-mode output stages are discussed and design strategies which improve performance are presented. A detailed analysis of non-ideal effect is carried out with particular emphasis on linearity. Design examples are given and circuit arrangements for further developments are included. CMOS Current Amplifiers serves as an excellent reference for researchers and professionals of analog IC design, and may also be used as an advanced text on current amplifiers.

Constraint Logic Programming (CLP), an area of extreme research interest in recent years, extends the semantics of Prolog in such a way that the combinatorial explosion, a characteristic of most problems in the field of Artificial Intelligence, can be tackled efficiently. By employing solvers dedicated to each domain instead of the unification algorithm, CLP drastically reduces the search space of the problem, which leads to increased efficiency in the execution of logic programs. CLP offers the possibility of solving complex combinatorial problems in an efficient way, and at the same time maintains the advantages offered by the declarativeness of logic programming. The aim of this book is to present parallel and constraint logic programming, offering a basic understanding of the two fields to the reader new to the area. The first part of the book gives an introduction to the fundamental aspects of conventional logic programming which is necessary for understanding the parts that follow. The second part includes an introduction to parallel logic programming, architectures and implementations proposed in the area. Finally, the third part presents the principles of constraint logic programming. The last two parts also include descriptions of the supporting facilities for the two paradigms in two popular systems; ECLIPSe and SICStus. These platforms have been selected mainly because they offer both parallel and constraint features. Annotated and explained examples are also included in the relevant parts, offering a valuable guide and a first practical experience to the reader. Finally, applications of the covered paradigms are presented. The authors felt that a book of this kind should provide some theoretical background necessary for the understanding of the covered logic programming paradigms, and a quick start for the reader interested in writing parallel and constraint logic programming programs. However it is outside the scope of this book to provide a deep theoretical background of the two areas. In that sense, this book is addressed to a public interested in obtaining a knowledge of the domain, without spending the time and effort to understand the extensive theoretical work done in the field &endash; namely postgraduate and advanced undergraduate students in the area of logic programming. This book fills a gap in the current bibliography, since there is no comprehensive book of this level that covers the areas of conventional, parallel, and constraint logic programming. Parallel and Constraint Logic Programming: An Introduction to Logic, Parallelism and Constraints is appropriate for an advanced level course on Logic Programming or Constraints, and as a reference for practitioners and researchers in industry.

Coding for Channels with Feedback presents both algorithms for feedback coding and performance analyses of these algorithms, including analyses of perhaps the most important performance criterion: computational complexity. The algorithms are developed within a single framework, termed the compressed-error-cancellation framework, where data are sent via a sequence of messages: the first message contains the original data; each subsequent message contains a source-coded description of the channel distortions introduced on the message preceding it. Coding for Channels with Feedback provides an easily understood and flexible framework for deriving low-complexity, practical solutions to a wide variety of feedback communication problems. It is shown that the compressed-error-cancellation framework leads to coding schemes with the lowest possible asymptotic order of growth of computations and can be applied to discrete memoryless channels, finite state channels, channels with memory, unknown channels, and multiple-access channels, all with complete noiseless feedback, as well as to channels with partial and noisy feedback. This framework leads to coding strategies that have linear complexity and are capacity achieving, and illustrates the intimate connection between source coding theory and channel coding theory. Coding for Channels with Feedback is an excellent reference for researchers and communication engineers in the field of information theory, and can be used for advanced courses on the topic.

As computer power grows and data collection technologies advance, a plethora of data is generated in almost every field where computers are used. The com- puter generated data should be analyzed by computers; without the aid of computing technologies, it is certain that huge amounts of data collected will not ever be examined, let alone be used to our advantages. Even with today's advanced computer technologies (e. g. , machine learning and data mining sys- tems), discovering knowledge from data can still be fiendishly hard due to the characteristics of the computer generated data. Taking its simplest form, raw data are represented in feature-values. The size of a dataset can be measUJ*ed in two dimensions, number of features (N) and number of instances (P). Both Nand P can be enormously large. This enormity may cause serious problems to many data mining systems. Feature selection is one of the long existing methods that deal with these problems. Its objective is to select a minimal subset of features according to some reasonable criteria so that the original task can be achieved equally well, if not better. By choosing a minimal subset offeatures, irrelevant and redundant features are removed according to the criterion. When N is reduced, the data space shrinks and in a sense, the data set is now a better representative of the whole data population. If necessary, the reduction of N can also give rise to the reduction of P by eliminating duplicates.

Asymptotic Combinatorial Coding Theory is devoted to the investigation of the combinatorial properties of transmission systems using discrete signals. The book presents results of interest to specialists in combinatorics seeking to apply combinatorial methods to problems of combinatorial coding theory. Asymptotic Combinatorial Coding Theory serves as an excellent reference for resarchers in discrete mathematics, combinatorics, and combinatorial coding theory, and may be used as a text for advanced courses on the subject.

Security is the science and technology of secure communications and resource protection from security violation such as unauthorized access and modification. Putting proper security in place gives us many advantages. It lets us exchange confidential information and keep it confidential. We can be sure that a piece of information received has not been changed. Nobody can deny sending or receiving a piece of information. We can control which piece of information can be accessed, and by whom. We can know when a piece of information was accessed, and by whom. Networks and databases are guarded against unauthorized access. We have seen the rapid development of the Internet and also increasing security requirements in information networks, databases, systems, and other information resources. This comprehensive book responds to increasing security needs in the marketplace, and covers networking security and standards. There are three types of readers who are interested in security: non-technical readers, general technical readers who do not implement security, and technical readers who actually implement security. This book serves all three by providing a comprehensive explanation of fundamental issues of networking security, concept and principle of security standards, and a description of some emerging security technologies. The approach is to answer the following questions: 1. What are common security problems and how can we address them? 2. What are the algorithms, standards, and technologies that can solve common security problems? 3.

Systematic Design of Analog IP Blocks introduces a design methodology that can help to bridge the productivity gap. Two different types of designs, depending on the design challenge, have been identified: commodity IP and star IP. Each category requires a different approach to boost design productivity. Commodity IP blocks are well suited to be automated in an analog synthesis environment and provided as soft IP. The design knowledge is usually common knowledge, and reuse is high accounting for the setup time needed for the analog library. Star IP still changes as technology evolves and the design cost can only be reduced by following a systematic design approach supported by point tools to relieve the designer from error-prone, repetitive tasks, allowing him/her to focus on new ideas to push the limits of the design.

A major advantage of a direct digital synthesizer (DDS) is that its output frequency, phase and amplitude can be precisely and rapidly manipulated under digital processor control. Other inherent DDS attributes include the ability to tune with extremely fine frequency and phase resolution, and to rapidly `hop' between frequencies. These combined characteristics have made the technology popular in military radar and communications systems. In fact, DDS technology was previously applied almost exclusively to high-end and military applications: it was costly, power-hungry, difficult to implement, and required a discrete high speed D/A converter. Due to improved integrated circuit (IC) technologies, they now present a viable alternative to analog-based phase-locked loop (PLL) technology for generating agile analog output frequency in consumer synthesizer applications. It is easy to include different modulation capabilities in the DDS by using digital signal processing (DSP) methods, because the signal is in digital form. By programming the DDS, adaptive channel bandwidths, modulation formats, frequency hopping and data rates are easily achieved. The flexibility of the DDS makes it ideal for signal generator for software radio. The digital circuits used to implement signal-processing functions do not suffer the effects of thermal drift, aging and component variations associated with their analog counterparts. The implementation of digital functional blocks makes it possible to achieve a high degree of system integration. Recent advances in IC fabrication technology, particularly CMOS, coupled with advanced DSP algorithms and architectures are providing possible single-chip DDS solutions to complex communication and signal processing subsystems as modulators, demodulators, local oscillators, programmable clock generators, and chirp generators. The DDS addresses a variety of applications, including cable modems, measurement equipments, arbitrary waveform generators, cellular base stations and wireless local loop base stations. Direct Digital Synthesizers was written to find possible applications for radio communication systems. It will have appeal for wireless and wireline communication engineers, teachers and students.

The world of wireless communications is changing very rapidly since a few years. The introduction of digital data communication in combination with digital signal process- ing has created the foundation for the development of many new wireless applications. High-quality digital wireless networks for voice communication with global and local coverage, like the GSM and DECT system, are only faint and early examples of the wide variety of wireless applications that will become available in the remainder of this decade. The new evolutions in wireless communications set new requirements for the trans- ceivers (transmitter-receivers). Higher operating frequencies, a lower power consump- tion and a very high degree of integration, are new specifications which ask for design approaches quite different from the classical RF design techniques. The integrata- bility and power consumption reduction of the digital part will further improve with the continued downscaling of technologies. This is however completely different for the analog transceiver front-end, the part which performs the interfacing between the antenna and the digital signal processing. The analog front-end's integratability and power consumption are closely related to the physical limitations of the transceiver topology and not so much to the scaling of the used technology. Chapter 2 gives a detailed study of the level of integration in current transceiver realization and analyzes their limitations. In chapter 3 of this book the complex signal technique for the analysis and synthesis of multi-path receiver and transmitter topologies is introduced.

Multimedia is changing the design of database and information retrieval systems. The accumulation of audio, image, and video content is of little use in these systems if the content cannot be retrieved on demand, a critical requirement that has led to the development of new technologies for the analysis and indexing of media data. In turn, these technologies seek to derive information or features from a data type that can facilitate rapid retrieval, efficient compression, and logical presentation of the data. Significant work that has not been addressed, however, is the benefits of analyzing more than one data type simultaneously. Computed Synchronization for Multimedia Applications presents a new framework for the simultaneous analysis of multiple media data objects. The primary benefit of this analysis is computed synchronization, a temporal and spatial alignment of multiple media objects. Computed Synchronization for Multimedia Applications also presents several specific applications and a general structure for the solution of computed synchronization problems. The applications demonstrate the use of this structure. Two applications in particular are described in detail: the alignment of text to speech audio, and the alignment of simultaneous English language translations of ancient texts. Many additional applications are discussed as future uses of the technology. Computed Synchronization for Multimedia Applications is useful to researchers, students, and developers seeking to apply computed synchronization in many fields. It is also suitable as a reference for a graduate-level course in multimedia data retrieval.

Conceptual Design of Multichip Modules and Systems treats activities which take place at the conceptual and specification level of the design of complex multichip systems. These activities include the formalization of design knowledge (information modeling), tradeoff analysis, partitioning, and decision process capture. All of these functions occur prior to the traditional CAD activities of synthesis and physical design. Inherent in the design of electronic modules are tradeoffs which must be understood before feasible technology, material, process, and partitioning choices can be selected. The lack of a complete set of technology information is an especially serious problem in the packaging and interconnect field since the number of technologies, process, and materials is substantial and selecting optimums is arduous and non-trivial if one truly wants a balance in cost and performance. Numerous tradeoff and design decisions have to be made intelligently and quickly at the beginning of the design cycle before physical design work begins. These critical decisions, made within the first 10% of the total design cycle, ultimately define up to 80% of the final product cost. Conceptual Design of Multichip Modules and Systems lays the groundwork for concurrent estimation level analysis including size, routing, electrical performance, thermal performance, cost, reliability, manufacturability, and testing. It will be useful both as a reference for system designers and as a text for those wishing to gain a perspective on the nature of packaging and interconnect design, concurrent engineering, computer-aided design, and system synthesis.

Medical Image Databases covers the new technologies of biomedical imaging databases and their applications in clinical services, education, and research. Authors were selected because they are doing cutting-edge basic or technology work in relevant areas. This was done to infuse each chapter with ideas from people actively investigating and developing medical image databases rather than simply review the existing literature. The authors have analyzed the literature and have expanded on their own research. They have also addressed several common threads within their generic topics. These include system architecture, standards, information retrieval, data modeling, image visualizations, query languages, telematics, data mining, and decision supports. The new ideas and results reported in this volume suggest new and better ways to develop imaging databases and possibly lead us to the next information infrastructure in biomedicine. Medical Image Databases is suitable as a textbook for a graduate-level course on biomedical imaging or medical image databases, and as a reference for researchers and practitioners in industry.

Higher transmission speeds, larger traffic volumes and the unpredictable characteristics of new applications, coupled with new end-user functions and features and variability of bandwidth, demand new networking methods, technologies and algorithms. These new directions are explored in Control and Performance in Packet, Circuit, and ATM Networks, which includes discussions of static flow, fluid flow, dynamic flow, learning automata, neural networks, fuzzy logic and much more. These techniques are used in performance evaluation, control and optimization of communications networks. Each of the methods achieves a different goal, and understanding them helps in the evaluation of different aspects of control and performance in communication networks. The book combines queuing theory with static-flow models and static optimization methods in order to analyze the behavior of communication networks. In addition, it reviews queuing theory and static optimization methods for the study of control problems in telecommunication networks. A valuable reference that can also be used as a text for an advanced course on the subject.

Software architectures have gained wide popularity in the last decade. They generally play a fundamental role in coping with the inherent difficulties of the development of large-scale and complex software systems. Component-oriented and aspect-oriented programming enables software engineers to implement complex applications from a set of pre-defined components. Software Architectures and Component Technology collects excellent chapters on software architectures and component technologies from well-known authors, who not only explain the advantages, but also present the shortcomings of the current approaches while introducing novel solutions to overcome the shortcomings. The unique features of this book are: evaluates the current architecture design methods and component composition techniques and explains their shortcomings; presents three practical architecture design methods in detail; gives four industrial architecture design examples; presents conceptual models for distributed message-based architectures; explains techniques for refining architectures into components; presents the recent developments in component and aspect-oriented techniques; explains the status of research on Piccola, Hyper/J(R), Pluggable Composite Adapters and Composition Filters. Software Architectures and Component Technology is a suitable text for graduate level students in computer science and engineering, and as a reference for researchers and practitioners in industry.