Maximum entropy signal restoration with linear programming

Technical Report · Sun May 01 04:00:00 EDT 1988

DOI:https://doi.org/10.2172/7043116· OSTI ID:7043116

Mastin, G A; Hanson, R J

Dantzig's bounded-variable method is used to express the maximum entropy restoration problem as a linear programming problem. This is done by approximating the nonlinear objective function with piecewise linear segments, then bounding the variables as a function of the number of segments used. The use of a linear programming approach allows equality constraints found in the traditional Lagrange multiplier method to be relaxed. A robust revised simplex algorithm is used to implement the restoration. Experimental results from 128- and 512-point signal restorations are presented.

• Research Organization: Sandia National Labs., Albuquerque, NM (USA)
• DOE Contract Number: AC04-76DP00789
• OSTI ID: 7043116
• Report Number(s): SAND-88-0451; ON: DE88011740
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS
990220* -- Computers
Computerized Models
& Computer Programs-- (1987-1989)
ALGORITHMS
COMPUTERS
CONSTRAINTS
DATA
DEC COMPUTERS
ENTROPY
EXPERIMENTAL DATA
IMAGE PROCESSING
INFORMATION
LINEAR PROGRAMMING
MATHEMATICAL LOGIC
MATHEMATICAL MODELS
MEMORY DEVICES
NONLINEAR PROBLEMS
NUMERICAL DATA
PHYSICAL PROPERTIES
PROCESSING
PROGRAMMING
SIGNAL-TO-NOISE RATIO
SIGNALS
THERMODYNAMIC PROPERTIES
USES