Carry out a variety of advanced statistical analyses including generalized additive models, mixed effects models, multiple imputation, machine learning, and missing data techniques using R. Each chapter starts with conceptual background information about the techniques, includes multiple examples using R to achieve results, and...
Multimedia Signal Processing is a comprehensive and accessible text to the theory and applications of digital signal processing (DSP). The applications of DSP are pervasive and include multimedia systems, cellular communication, adaptive network management, radar, pattern recognition, medical signal processing, financial data...
A new edition of the essential text and professional reference, with substantial new material on such topics as vEB trees, multithreaded algorithms, dynamic programming, and edge-based flow.
Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms...
About ten years ago we had the idea to begin a course in probability for students of electrical engineering. Prior to that electrical engineering graduate students at the Naval Postgraduate School specializing in communication, control, and signal processing were given a basic course in probability in another department and then began a course in...
The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, recognize faces or spoken speech, optimize robot behavior so that a task can be completed...
Fully updated throughout, Electric Vehicle Technology, SecondEdition , is a complete guide to the principles, design andapplications of electric vehicle technology. Including all thelatest advances, it presents clear and comprehensive coverage ofthe major aspects of electric vehicle development and offers anengineering-based evaluation of...
As in many other fields, biomedical engineers benefit from the use of computational intelligence (CI) tools to solve complex and non-linear problems. The benefits could be even greater if there were scientific literature that specifically focused on the biomedical applications of computational intelligence techniques. The first comprehensive...
Based on the author’s course at NYU, Linear Algebra and Probability for Computer Science Applicationsgives an introduction to two mathematical fields that are fundamental in many areas of computer science. The course and the text are addressed to students with a very weak mathematical background. Most of the...
Compact but comprehensive, this textbook presents the essential concepts of electronic circuit theory. As well as covering classical linear theory involving resistance, capacitance and inductance it treats practical nonlinear circuits containing components such as operational amplifiers, Zener diodes and exponential diodes. The...
This book deals with a number of mathematical topics that are of great importance in the study of classical econometrics. There is a lengthy chapter on matrix algebra, which takes the reader from the most elementary aspects to the partitioned inverses, characteristic roots and vectors, symmetric, and orthogonal and positive (semi) definite...
