Darrell Williamson – författare

The topics of control engineering and signal processing continue to flourish and develop. In common with general scientific investigation, new ideas, concepts and interpretations emerge quite spontaneously and these are then discussed, used, discarded or subsumed into the prevailing subject paradigm. Sometimes these innovative concepts coalesce into a new sub-discipline within the broad subject tapestry ofcontrol and signal processing. This preliminary battle between old and new usually takes place at conferences, through the internet and in the journals of the discipline. After a little more maturity has been acquired by the new concepts then archival publication as a scientific or engineering monograph may occur. The applications ofsignal processing techniques have grown and grown. They now cover the wide range from the statistical properties of signals and data through to the hardware problems of communications in all its diverse aspects. Supporting this range ofapplications is a body of theory, analysis and techniques which is equally broad. Darrell Williamson has faced the difficult task of organising this material by adopting an algebraic approach. This uses general mathematical and systems ideas and results to form a firm foundation for the discrete signal processing paradigm. Although this may require some extra concentration and involvement by the student or researcher, the rewards are a clarity of presentation and deeper insight into the power of individual results. An additional benefit is that the algebraic language used is the natural language of computing tools like MATLAB and its simulation facility, SIMULINK.

This text is intended to be used by postgraduate and advanced undergraduate students in the study of discrete-time integrals. It focuses on an algebraic approach to the analysis and design of discrete-time signal processing algorithms which renders the Laplace and z-transforms redundant for this purpose. While the material on difference equations is developed slowly, from an elementary base, it is assumed that the reader has a working knowledge of complex numbers and has completed a first course in vector and matrix analysis.Various subjects and problems are discussed including: - The solution of both difference and state space equations - Provides an alternative approach to the use of Laplace and z-transformations - Linear-algebraic ideas for the analysis and design of linear signals - The Design of recursive (IIR) and nonrecursive (FIR) digital filters - The design of classical Butterworth, Chebyshev and Elliptical analog filters and the transformation of analog filters - The Discrete Fourier Transform and its implementation through the Fast Fourier Transform - Applications of least-squares analysis to the design of linear phase FIR filters, convolution (FIR and IIR) signal models, and state space signal models - Design of digital filters via discrete approximation of analog filters, digital transformation of analog filter, and digital transformation of digital filter - Finite wordlength (FWL) implementation of IIR digital filters including the basic properties of both fixed and floating point arithmetic representations, implication of arithmetic quantizations and filter structure on accuracy and speed of real-time implementation - Written with clarity and containing the latest, detailed results based on comprehensive research, this book is an important textbook for all students interested in discrete-time signals - The text supports the use of algebra-based software packages, such as MATLAB .

eScience allows scientific research to be carried out in highly distributed environments. The complex nature of the interactions in an eScience infrastructure, which often involves a range of instruments, data, models, application, people and computational facilities, suggests there is a need for data provenance and data management (DPDM). The W3C Provenance Working Group defines the provenance of a resource as a “record that describes entities and processes involved in producing and delivering or otherwise influencing that resource”. It has been widely recognised that provenance is a critical issue to enable sharing, trust, authentication and reproducibility of eScience process.Data Provenance and Data Management in eScience identifies the gaps between DPDM foundations and their practice within eScience domains including clinical trials, bioinformatics and radio astronomy. The book covers important aspects of fundamental research in DPDM including provenance representation and querying. It also explores topics that go beyond the fundamentals including applications. This book is a unique reference for DPDM with broad appeal to anyone interested in the practical issues of DPDM in eScience domains.