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MS/PhD CURRICULA


INTELLIGENT SYSTEMS, ROBOTICS, and CONTROL



Curriculum Advisor

Dr. Gert Lanckriet

(858) 534-6976

EBUI 5604

 

This information sciences-based field is concerned with the design of human-interactive intelligent systems that can sense the world (defined as some specified domain of interest); represent or model the world; detect and identify states and events in the world; reason about and make decisions about the world; and/or act on the world, perhaps all in real-time. A sense of the type of systems and applications encountered in this discipline can be obtained by viewing the projects shown at the website http://swiftlet.ucsd.edu.

The development of such sophisticated systems is necessarily an interdiscipinary activity. To sense and succinctly represent events in the world requires knowledge of signal processing, computer vision, information theory, coding theory, and data-basing; to detect and reason about states of the world utilizes concepts from statistical detection theory, hypothesis testing, pattern recognition, time series analysis, and artificial intelligence; to make good decisions about highly complex systems requires knowledge of traditional mathematical optimization theory and contemporary near-optimal approaches such as evolutionary computation; and to act upon the world requires familiarity with concepts of control theory and robotics. Very often learning and adaptation are required as either critical aspects of the world are poorly known at the outset, and must be refined on-line, or the world is non-stationary and our system must constantly adapt to it as it evolves. In addition to the theoretical information and computer science aspects, many important hardware and software issues must be addressed in order to obtain an effective fusion of a complicated suite of sensors, computers, and problem dynamics into one integrated system.

Faculty affiliated with the ISRC subarea are involved in virtually all aspects of the field, including applications to intelligent communications systems; advanced human-computer interfacing; statistical signal- and image-processing; intelligent tracking and guidance systems; biomedical system identification and control; and control of teleoperated and autonomous multiagent robotic systems.

 

Course Requirements

·  Core Courses (sixteen units):

 

ECE 250

Random Processes

ECE 251AN

Digital Signal Processing I

ECE 271A

Statistical Learning I

ECE 275A

Parameter Estimation I

 

·  Twelve additional units selected from the following:

 

ECE 251BN-CN

Digital Signal Processing II, Filter Banks and Wavelets

ECE 252A-B

Speech Compression and Recognition

ECE 253A

Fundamentals of Digital Image Processing

ECE 255AN

Information Theory

ECE 255BN

Source Coding I

ECE 271B

Statistical Learning II

ECE 272A

Stochastic Processes in Dynamic Systems

ECE 273

Convex Optimization and Applications

ECE 275B

Parameter Estimation II

ECE 285

Special Topic: Pattern Recognition (Offered Alternate Years)

CSE 250A

Artificial Intelligence I

CSE 252A

Computer Vision I

MAE 280A

Linear Control Design

MAE 281A

Nonlinear Systems

 

·  Technical Electives (twenty units):

 

These must be chosen among graduate (200-Level) ECE, CSE, MAE, Mathematics, Cognitive Science, Bioengineering, Physics, Econonomics, and SIO courses to complete a total of 48 units.

Students may select up to twelve units at the 100-level courses to satisfy the technical elective requirement.

Students may count no more than eight units of ECE 299 towards their technical elective requirement.

ALL elective courses MUST be approved by the student's graduate adviser.

ECE 501 Teaching: May only be taken as part of the ECE Academic Career Preparation Program, which requires the consent and approval of the faculty advisor and departmental committee


 

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