Series in Electrical and Computer Engineering – serie

Striking a nice balance between mathematical rigor and engineering-oriented applications, this second edition covers the bedrock parts of classical control theory — the Routh-Hurwitz theorem and applications, Nyquist diagrams, Bode plots, root locus plots, and the design of controllers (phase-lag, phase-lead, lag-lead, and PID). It also covers three more advanced topics — non-linear control, modern control, and discrete-time control.This invaluable book makes effective use of MATLAB® as a tool in design and analysis. Containing 75 solved problems and 200 figures, this edition will be useful for junior and senior level university students in engineering who have a good knowledge of complex variables and linear algebra.

The 3rd edition strikes a nice balance between mathematical rigor and engineering oriented applications, helping students to understand the mathematical and engineering aspects of control theory.The book makes effective use of the tools provided by MATLAB® (and includes material about using the tools provided by the Python® programming language) in the design and analysis of control systems without allowing the computer-based tools to substitute for knowledge of control theory. The examples in the text are carefully designed to develop the student's intuition — in both mathematics and engineering.With over 90 solved homework problems and about 200 figures, this invaluable title will benefit junior and senior level university students in engineering.

This important book introduces the concept of intrusion detection, discusses various approaches for intrusion detection systems (IDS), and presents the architecture and implementation of IDS. It emphasizes on the prediction and learning algorithms for intrusion detection and highlights techniques for intrusion detection of wired computer networks and wireless sensor networks. The performance comparison of various IDS via simulation will also be included.

Electrical, communication, transportation, computer, and neural networks are special kinds of nets. Designing these networks demands sophisticated mathematical models for their analysis. This book is the first to present a unified, comprehensive, and up-to-date treatment of net theory. It brings together elements of abstract graph theory and circuit analysis to network problems.

Striking a careful balance between mathematical rigor and engineering-oriented applications, this textbook aims to maximize the readers' understanding of both the mathematical and engineering aspects of control theory.The bedrock elements of classical control theory are comprehensively covered: the Routh-Hurwitz theorem and applications, Nyquist diagrams, Bode plots, root locus plots, the design of controllers (phase-lag, phase-lead, lag-lead, and PID), and three further advanced topics: non-linear control, modern control and discrete-time control.A Mathematical Introduction to Control Theory will be an invaluable book for junior and senior level university students in engineering, particularly electrical engineering. Students with a good knowledge of algebra and complex variables will also find many interesting applications in this volume.

A mobile agent system could be attacked by malicious agents, platforms and third parties. Mobile agents simply offer greater opportunities for abuse and misuse, which broadens the scale of threats significantly. In addition, since mobile agents have some unique characteristics such as their mobility, security problems have become more complicated in these systems. These security problems have become a bottleneck in the development and maintenance of mobile agent systems, especially in security sensitive applications such as electronic commerce. This book introduces the concept and structure of mobile agent systems and discusses various attacks and countermeasures. The emphasis is on the formal modeling and analysis of secure mobile agent systems and their applications.

This book covers neural networks with special emphasis on advanced learning methodologies and applications. It includes practical issues of weight initializations, stalling of learning, and escape from a local minima, which have not been covered by many existing books in this area. Additionally, the book highlights the important feature selection problem, which baffles many neural networks practitioners because of the difficulties handling large datasets. It also contains several interesting IT, engineering and bioinformatics applications.