Bücher der Reihe Advanced Series in Electrical & Computer Engineering

The third edition presents a unified, up-to-date and detailed account of broadband matching theory and its applications to the design of broadband matching networks and amplifiers.

This 2nd edition provides an in-depth, up-to-date, unified, and comprehensive treatment of the fundamentals of the theory of active networks and its applications to feedback amplifier design.

The intuitive diagrammatic nature of graphs makes them useful in modelling systems in engineering problems. This text gives an account of material related to such applications, including minimal cost flows and rectangular dissection and layouts. A major theme is electrical network theory.

Reports the Linear Parameter Varying (LPV) system identification. This book contains twelve chapters, focusing on the LPV identification methods for both discrete-time and continuous-time models, using different approaches such as optimization methods for input/output LPV models Identification, set membership methods, and more.

This is intended to serve as the text book of a one semester university course for graduate or senior undergraduate students in the physical sciences, electrical engineering and other related disciplines. It may also be used as a reference book for those who are working in the field.

This compendium contains 10 chapters written by world renowned researchers with expertise in semantic computing, genome sequence analysis, biomolecular interaction, time-series microarray analysis, and machine learning algorithms.The salient feature of this book is that it highlights eight types of computational techniques to tackle different biomedical applications. These techniques include unsupervised learning algorithms, principal component analysis, fuzzy integral, graph-based ensemble clustering method, semantic analysis, interolog approach, molecular simulations and enzyme kinetics.The unique volume will be a useful reference material and an inspirational read for advanced undergraduate and graduate students, computer scientists, computational biologists, bioinformatics and biomedical professionals.

 This textbook gives a fresh approach to an introductory course in signal processing. Its unique feature is to alternate chapters on continuous-time (analog) and discrete-time (digital) signal processing concepts in a parallel and synchronized manner. This presentation style helps readers to realize and understand the close relationships between continuous and discrete time signal processing, and lays a solid foundation for the study of practical applications such as the analysis and design of analog and digital filters.The compendium provides motivation and necessary mathematical rigor. It generalizes the Fourier transform to Laplace and Z transforms, applies these transforms to linear system analysis, covers the time and frequency-domain analysis of differential and difference equations, and presents practical applications of these techniques to convince readers of their usefulness. MATLAB® examples are provided throughout, and over 100 pages of solved homework problems are included in the appendix.

With the increasing availability of omics data and mounting evidence of the usefulness of computational approaches to tackle multi-level data problems in bioinformatics and biomedical research in this post-genomics era, computational biology has been playing an increasingly important role in paving the way as basis for patient-centric healthcare.Two such areas are: (i) implementing AI algorithms supported by biomedical data would deliver significant benefits/improvements towards the goals of precision medicine (ii) blockchain technology will enable medical doctors to securely and privately build personal healthcare records, and identify the right therapeutic treatments and predict the progression of the diseases.A follow-up in the publication of our book Computation Methods with Applications in Bioinformatics Analysis (2017), topics in this volume include: clinical bioinformatics, omics-based data analysis, Artificial Intelligence (AI), blockchain, big data analytics, drug discovery, RNA-seq analysis, tensor decomposition and Boolean network.

Today's integrated silicon circuits and systems for wireless communications are of a huge complexity.This unique compendium covers all the steps (from the system-level to the transistor-level) necessary to design, model, verify, implement, and test a silicon system. It bridges the gap between the system-world and the transistor-world (between communication, system, circuit, device, and test engineers).It is extremely important nowadays (and will be more important in the future) for communication, system, and circuit engineers to understand the physical implications of system and circuit solutions based on hardware/software co-design as well as for device and test engineers to cope with the system and circuit requirements in terms of power, speed, and data throughput.