chenws1972的博客

The main reason for a fourth edition of Essential MATLAB for Engineers and Scientists is to keep up with MATLAB, now in its latest version (7.7 Version 2008B). Like the previous editions, this one presents MATLAB as a problemsolving tool for professionals in science and engineering, as well as students in those fields, who have no prior knowledge of computer programming.

This text includes the following chapters and appendices: • Second Order Circuits • Resonance • Elementary Signals • The Laplace Transformation • The Inverse Laplace Transformation • Circuit Analysis with Laplace Transforms • Frequency Response and Bode Plots • Self and Mutual Inductances - Transformers • One and Two Port Networks • Three Phase Systems • Introduction to MATLAB • Differential Equations • Matrices and Determinants • Constructing Semilog Plots with Microsoft Excel • Scaling Each chapter contains numerous practical applications supplemented with detailed instructions for using MATLAB to obtain quick and accurate answers.

Product Description Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence, offering intuitive, efficient, and reliable methods for diagnosis, prediction, decision making, classification, troubleshooting, and data mining under uncertainty. "Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis" provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. Intended primarily for practitioners, this book does not require sophisticated mathematical skills or deep understanding of the underlying theory and methods nor does it discuss alternative technologies for reasoning under uncertainty. The theory and methods presented are illustrated through more than 140 examples, and exercises are included for the reader to check his/her level of understanding.The techniques and methods presented for knowledge elicitation, model construction and verification, modeling techniques and tricks, learning models from data, and analyses of models have all been developed and refined on the basis of numerous courses that the authors have held for practitioners worldwide.