Title :
Distributed estimation and quantization
Author_Institution :
Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI, USA
fDate :
7/1/1993 12:00:00 AM
Abstract :
An algorithm is developed for the design of a nonlinear, n-sensor, distributed estimation system subject to communication and computation constraints. The algorithm uses only bivariate probability distributions and yields locally optimal estimators that satisfy the required system constraints. It is shown that the algorithm is a generalization of the classical Lloyd-Max results
Keywords :
constraint theory; estimation theory; information theory; probability; sensor fusion; bivariate probability distributions; classical Lloyd-Max results; communication constraints; computation constraints; distributed estimation system; locally optimal estimators; nonlinear n-sensor system; quantization; Algorithm design and analysis; Communication channels; Drives; Feedback; Force sensors; Information theory; Probability distribution; Quantization; Sensor fusion; Sensor systems;
Journal_Title :
Information Theory, IEEE Transactions on
