Engineering Probability

Fall 2019

To understand basic probability theory and statistical analysis and be able to apply them to modeling typical computer and electrical engineering problems such as noisy signals, decisions in the presence of uncertainty, pattern recognition, network traffic, and digital communications.

Signals & Systems

Fall 2014, Spring 2015, Fall 2016, Spring 2019

Time and frequency-domain representation of continuous- and discrete-time signals and systems. Response of linear, time-invariant systems. Convolution, Fourier series, Fourier transform, Laplace transform and z-transform. Applications in communication, feedback control, and signal processing.

Information Theory & High-dimensional Statistics

Fall 2017, Fall 2018

Information theory was invented by Claude E. Shannon as a mathematical theory for communication but has subsequently found a broad range of applications.This course covers the core concepts of information theory, including entropy and mutual information, and their applications to high-dimensional statistics, data analytics, and machine learning.

Wireless Data Communications

Spring 2017

This course covers the basic concepts for designing the key physical layer component of modern wireless communication systems. These components include source coding, channel coding, wireless channel models, fading process, sources of diversity (time, frequency, space), and multi-antenna systems.

Digital Communications

Fall 2010, Fall 2011, Spring 2015, Spring 2016

The hallmark of a digital communications is the decomposition of message transmission to first representing the message using bits (information theory) and then communicating those bits reliably over an unreliable communications medium (signaling).

Digital Signal Processing

Fall 2013, Fall 2014

A detailed examination of basic digital signal processing operations including sampling/reconstruction of continuous time signals, Fourier and Z-transforms are given. The Fourier and Z-transforms will be used to analyze the stability of systems, to find the system transfer function, and to design digital filters

MIMO Communications

Spring 2011, Spring 2012

This course covers the basic concepts of multi-antenna communication in wireless communication systems. It covers topics on single-user channels, multiuser channels, as well as multiuser networks. Gains of multi-antenna systems are described and various theoretical and practical aspects are discussed.

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