Fall 2006, Fall 2007, Fall 2008, Fall 2009, Fall 2010, Fall 2011, Fall 2012
This course provides the fundamental theory of the basic building blocks that exist in all communication systems. Textbook: B. P Lathi and Z. Ding, Modern Digital and Analog Communication Systems, 4th Edition, Oxford University Press, 2009.
Spring 2007, Spring 2008, Spring 2009, Spring 2011, Spring 2012
The principal objective of this course is to develop in each student an understanding of the fundamental principles behind mobile wireless communications. Textbook:T. S. Rappaport, Wireless Communications --- Principles and Practice, Prentice Hall, 2nd edition, 2001.
Spring 2010, Spring 2011, Spring 2012
Information fusion involves combining information from multiple sources or sensors to achieve inferences not possible using a single sensor or source. This course provides an introductory treatment of the fundamentals of statistical inference in a distributed framework. Applications range from military applications such as battle management, target tracking, automated threat assessment, to nonmilitary applications including environmental monitoring, medical diagnosis, monitoring of complex machines and robotics. In these applications, observations are processed in a distributed manner and, either inferences are made at the distributed processors or processed data (compressed observations) are conveyed to a fusion center that makes a global decision. Topics to be covered include:
This course introduces basic principles of probability, random variables and random processes to deal with stochastic systems involving random processes and noise through mathematical analysis and computer simulations. Textbook: H. Stark and J. W. Woods, Probability and Random Processes with Applications to Signal Processing, 3rd Edition, Prentice Hall, 2002.