Course Schedule - Spring Semester 2017

     

CAAM 567 002 (CRN: 24338)

SIGNAL RECOVERY

Long Title: SIGNAL RECOVERY: THEORY AND SIMULATION
Department: Computational & Applied Math
Instructor: Hand, Paul E.
Meeting: 4:00PM - 5:15PM TR DCH 1075 (9-JAN-2017 - 21-APR-2017) 
Session: Full Term
Grade Mode: Standard Letter
Course Type: Lecture
Language of Instruction: Taught in English
Method of Instruction: Face to Face
Credit Hours: 3
Course Syllabus:
Course Materials: Rice Campus Store
 
Restrictions:
Must be enrolled in one of the following Level(s):
Graduate
Section Max Enrollment: 40
Section Enrolled: 16
Enrollment data as of: 16-AUG-2022 10:27AM
 
Additional Fees: None
 
Final Exam: GR Course-Dept Schedules Exam
 
Description: This course introduces the theory and numerical algorithms for several fundamental signal recovery tasks. Topics include L1 minimization, sparse regression, compressed sensing, orthogonal matching pursuit, proximal operators, ADMM algorithms, Iterative Reweighted Least Squares. Nuclear norm minimization, matrix completion, robust Principal Component Analysis. Recommended Prerequisite(s): CAAM 378 or MATH 302 or STAT 310.