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This text offers both a clear view of the abstract theory as well as a concise survey of the theory's applications to various branches of pure and applied mathematics. 1957 edition.
An important problem that arises in different disciplines of science and engineering is that of computing limits of sequences of vectors of very large dimension. Such sequences arise, for example, in the numerical solution of systems of linear and nonlinear equations by fixed-point iterative methods, and their limits are simply the required solutions to these systems. The convergence of these sequences, which is very slow in many cases, can be accelerated successfully by using suitable vector extrapolation methods. Vector Extrapolation Methods with Applications?is the first book fully dedicated to the subject of vector extrapolation methods. It is a self-contained, up-to-date, and state-of-the-art reference on the theory and practice of the most useful methods. It covers all aspects of the subject, including development of the methods, their convergence study, numerically stable algorithms for their implementation, and their various applications. It also provides complete proofs in most places. As an interesting application, the author shows how these methods give rise to rational approximation procedures for vector-valued functions in the complex plane, a subject of importance in model reduction problems among others. This book is intended for numerical analysts, applied mathematicians, and computational scientists and engineers in fields such as computational fluid dynamics, structures, and mechanical and electrical engineering, to name a few. Since it provides complete proofs in most places, it can also serve as a textbook in courses on acceleration of convergence of iterative vector processes, for example.
"Designed for a one-year course in topological vector spaces, this text is geared toward beginning graduate students of mathematics. Topics include Banach space, open mapping and closed graph theorems, local convexity, duality, equicontinuity, operators,inductive limits, and compactness and barrelled spaces. Extensive tables cover theorems and counterexamples. Rich problem sections throughout the book. 1978 edition"--
Engineers must make decisions regarding the distribution of expensive resources in a manner that will be economically beneficial. This problem can be realistically formulated and logically analyzed with optimization theory. This book shows engineers how to use optimization theory to solve complex problems. Unifies the large field of optimization with a few geometric principles. Covers functional analysis with a minimum of mathematics. Contains problems that relate to the applications in the book.
The first comprehensive, illustrated guide to vector control methods suitable for use by individuals and communities. Published at a time when large-scale control programs organized by governments are declining, the manual aims to help non-professionals understand the role of vectors in specific diseases and then select and use control methods that are appropriate, effective, affordable, and safe. Hundreds of simple, inexpensive and often ingenious techniques, developed and used in a host of different settings, are presented and described in this abundantly illustrated guide. The manual is intended to assist health workers at district and community level, in aid organizations, in refugee camps, or in resource development projects who do not have direct access to experts in entomology, yet need methods for controlling the vectors of such important diseases as malaria filariasis leishmaniasis schistosomiasis dengue and trypanosomiasis. With this audience in mind, the book combines non-specialist factual information about vectors and the diseases they cause with practical advice on control measures, whether involving the use of insecticides, environmental modifications, or the construction of simple devices from local materials. Details range from a table showing where and when the different groups of biting Diptera are active to a recipe for preparing plaster to protect homes against triatomine bugs, from step-by-step instructions for the construction of cheap insect traps, to advice on how to impregnate bed nets and curtains with suitable insecticides. The book opens with a brief description of recent changes in the approach to vector control, followed by a discussion of factors that can influence the success of control measures undertaken by individuals and communities. The core of the manual consists of eight chapters focused on each of the major vectors and groups of vectors: mosquitos and other biting Diptera; tsetse flies; triatomine bugs; bedbugs, fleas, lice, ticks, and mites; cockroaches; houseflies; cyclops; and freshwater snails. Each chapter includes pertinent facts about the vector's life cycle, behavior, and favorite habitats, the diseases it causes, and their clinical features, including opportunities for prevention, treatment, and control. Against this background, methods for control are presented in great detail. Since the use of control measures is often constrained by lack of resources as well as lack of knowledge, most methods described are simple and cheap, do not require much training or supervision, and are safe for both the user and the environment. The remaining chapters offer guidance on the principles and practice of house spraying with residual insecticides, and provide instructions for the safe use of pesticides and the emergency treatment of poisoning.
Concise undergraduate-level text by a prominent mathematician explores the relationship between algebra and geometry. An elementary course in plane geometry is the sole requirement. Includes answers to exercises. 1962 edition.
Ecology of Insect Vector Populations provides a review and appraisal of the ecology of insect vectors of disease, with particular attention to the problems of sampling adult insect vector populations. The book examines the manner in which the inter-related problems of insect ecology, behavior, and population sampling have been explored over a wide range of investigations on disease vectors. The text focuses mainly on the study of blood-sucking dipterous insects such as tse-tse flies, mosquitoes, black-flies, and midges along with the appraisal of relevant studies on house-fly and blow-fly populations. The studies of the ecology of the wingless vectors of disease or plague such as the fleas are carried out extensively. The dissertation will be of interest to medical entomologists, animal ecologists, and epidemiologists.
Prize-winning study traces the rise of the vector concept from the discovery of complex numbers through the systems of hypercomplex numbers to the final acceptance around 1910 of the modern system of vector analysis.
This is the first comprehensive introduction to Support Vector Machines (SVMs), a generation learning system based on recent advances in statistical learning theory. SVMs deliver state-of-the-art performance in real-world applications such as text categorisation, hand-written character recognition, image classification, biosequences analysis, etc., and are now established as one of the standard tools for machine learning and data mining. Students will find the book both stimulating and accessible, while practitioners will be guided smoothly through the material required for a good grasp of the theory and its applications. The concepts are introduced gradually in accessible and self-contained stages, while the presentation is rigorous and thorough. Pointers to relevant literature and web sites containing software ensure that it forms an ideal starting point for further study. Equally, the book and its associated web site will guide practitioners to updated literature, new applications, and on-line software.
A guide on the use of SVMs in pattern classification, including a rigorous performance comparison of classifiers and regressors. The book presents architectures for multiclass classification and function approximation problems, as well as evaluation criteria for classifiers and regressors. Features: Clarifies the characteristics of two-class SVMs; Discusses kernel methods for improving the generalization ability of neural networks and fuzzy systems; Contains ample illustrations and examples; Includes performance evaluation using publicly available data sets; Examines Mahalanobis kernels, empirical feature space, and the effect of model selection by cross-validation; Covers sparse SVMs, learning using privileged information, semi-supervised learning, multiple classifier systems, and multiple kernel learning; Explores incremental training based batch training and active-set training methods, and decomposition techniques for linear programming SVMs; Discusses variable selection for support vector regressors.