Описание: Of all the electro magnetic susceptibility problems found during test and in the field, ESD is one of the toughest to overcome.
Автор: Charvaka Duvvury,Harald Gossner Название: System Level ESD Co?€“Design ISBN: 1118861906 ISBN-13(EAN): 9781118861905 Издательство: Wiley Рейтинг: Цена: 15832 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An effective and cost efficient protection of electronic system against ESD stress pulses specified by IEC 61000-4-2 is paramount for any system design.
Автор: Bafleur, Marise Название: ESD Protection Methodologies ISBN: 1785481223 ISBN-13(EAN): 9781785481222 Издательство: Elsevier Science Рейтинг: Цена: 11706 р. Наличие на складе: Поставка под заказ.
Описание: Failures caused by electrostatic discharges (ESD) constitute a major problem concerning the reliability and robustness of integrated circuits and electronic systems. This book summarizes the many diverse methodologies aimed at ESD protection and shows, through a number of concrete studies, that the best approach in terms of robustness and cost-effectiveness consists of implementing a global strategy of ESD protection. ESD Protection Methodologies begins by exploring the various normalized test techniques that are used to qualify ESD robustness as well as characterization and defect localization methods aimed at implementing corrective measures. Due to the increasing complexity of integrated circuits, it is important to be able to provide a simulation in which the implemented ESD protection strategy provides the desired protection, while not harming the performance levels of the circuit. Therefore, the main features and difficulties related to the different types of simulation, finite element, SPICE-type and behavioral, are then studied. To conclude, several case studies are presented which provide real-life examples of the approaches explained in the previous chapters and validate a number of the strategies from component to system level. .
Описание: The technology of neural networks has attracted much attention in recent years. Their ability to learn nonlinear relationships is widely appreciated and is utilized in many different types of applications; modelling of dynamic systems, signal processing, and control system design being some of the most common. The theory of neural computing has matured considerably over the last decade and many problems of neural network design, training and evaluation have been resolved. This book provides a comprehensive introduction to the most popular class of neural network, the multilayer perceptron, and shows how it can be used for system identification and control. It aims to provide the reader with a sufficient theoretical background to understand the characteristics of different methods, to be aware of the pit-falls and to make proper decisions in all situations. The subjects treated include: System identification: multilayer perceptrons; how to conduct informative experiments; model structure selection; training methods; model validation; pruning algorithms. Control: direct inverse, internal model, feedforward, optimal and predictive control; feedback linearization and instantaneous-linearization-based controllers. Case studies: prediction of sunspot activity; modelling of a hydraulic actuator; control of a pneumatic servomechanism; water-level control in a conical tank. The book is very application-oriented and gives detailed and pragmatic recommendations that guide the user through the plethora of methods suggested in the literature. Furthermore, it attempts to introduce sound working procedures that can lead to efficient neural network solutions. This will make the book invaluable to the practitioner and as a textbook in courses with a significant hands-on component.
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