Practical Statistical Signal Processing using MATLAB With Radar, Sonar, Communications, Speech & Imaging Applications at Applied Technology Institute
The design of this 3-day signal processing systems for radar, sonar, communications, speech, imaging and other applications is based on state-of-the-art computer algorithms. These algorithms encompass a wide variety of important tasks such as computer data generation, parameter estimation, filtering, interpolation, detection, spectral analysis, beamforming, classification, and tracking. Until now these algorithms could only be learned by reading the latest technical journals. This course will take the mystery out of these designs by introducing the algorithms with a minimum of mathematics and illustrating the key ideas via numerous examples using the MATLAB programming language. Designed for engineers, scientists, and other professionals who wish to study the practice of statistical signal processing without the headaches, this course will make extensive use of hands-on MATLAB implementations and demonstrations. Attendees will receive a suite of software source code and are encouraged to bring their own laptops to follow along with the demonstrations. In addition to copies of all slides and several papers, each participant will receive the books "Fundamentals of Statistical Signal Processing: Estimation Theory, Vol. I" and "Fundamentals of Statistical Signal Processing: Detection Theory, Vol. II" by instructor Dr. Kay. The accompanying problem solutions manuals will also be distributed. A suite of MATLAB m-files will be distributed in source format for direct use or modification by the user.
Instructor: Dr. Steven Kay is a Professor of Electrical Engineering at the University of Rhode Island and the President of Signal Processing Systems, a consulting firm to industry and the government. He has over 25 years of research and development experience in designing optimal statistical signal processing algorithms for radar, sonar, speech, image, communications, vibration, and financial data analysis. Much of his work has been published in over 100 technical papers and the three textbooks, "Modern Spectral Estimation: Theory and Application", "Fundamentals of Statistical Signal Processing: Estimation Theory", and "Fundamentals of Statistical Signal Processing: Detection Theory". Dr. Kay is a Fellow of the IEEE.
What You Will Learn: