ELE 584 (or STA 584) 3 credits
Pattern Recognition is a multi-disciplinary field which borrows from Electrical Engineering, Applied Mathematics, Physics, Biology and Philosophy. The word "pattern" implies operation on images, such as in optical character recognition which was perhaps the most important early application. However the "patterns" more generally correspond to information that allows for accurate discrimination among classes of objects.
Simplistically stated, a set of (potentially noisy) measurements carry information about the type, or class, of object which was measured. Accurately determining the class based on the measurements is the goal. This is why pattern recognition is also often referred to as pattern classification or simply classification.
Pattern recognition or classification methods are currently employed in a great variety of practical problems - sonar and radar, image processing, OCR such as zip code sorting, speech recognition, digital cameras, computer-aided medical diagnosis, etc. This course will involve projects that deal with such real-world examples. Some computer programming will be required.
Construction of robust classification rules and analysis of their performance requires a solid understanding of statistical decision theory and hypothesis testing ideas, multivariate statistics and the concept of statistical significance. ELE 509, or introductory probability and statistics, is a prerequisite for this study.
Course Instructor:
Ashwin Sarma received the bachelor's and master's degrees in E.E. from Cornell University and the Ph.D. in E.E. from the University of Rhode Island. Dr. Sarma has been actively engaged in statistical signal processing research at the Naval Undersea Warfare Center first in New London CT and later in Newport RI. His areas of interest include acoustic channel modeling, adaptive CFAR detection, pattern recognition, array signal processing and Kalman Filtering for contact tracking and self-localization.
Course Time: Wednesday evenings currently from 6:30 - 9:15 pm
Location: Kelley Hall, room 102
For further info contact ashwin.sarma@navy.mil (401 832 8651).