Title :
Estimating random integrals from noisy observations: sampling designs and their performance
Author :
Bucklew, James A. ; Cambinis, S.
Author_Institution :
Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI, USA
fDate :
1/1/1988 12:00:00 AM
Abstract :
The problem of estimating a weighted average of a random process from noisy observations at a finite number of sampling points is considered. The performance of sampling designs with optimal or suboptimal, but easily computable, estimator coefficients is studied. Several examples and special cases are studied, including additive independent noise, nonlinear distortion with noise, and quantization noise
Keywords :
information theory; random processes; signal processing; additive independent noise; information theory; noisy observations; nonlinear distortion with noise; quantization noise; random integrals estimation; sampling designs; signal processing; Additive noise; Estimation error; H infinity control; Information theory; Integral equations; Nonlinear distortion; Quantization; Random processes; Sampling methods; Signal sampling;
Journal_Title :
Information Theory, IEEE Transactions on
