Title :
Asymptotically optimal quantizers for detection of i.i.d
Author :
Benitz, Gerald R. ; Bucklew, James A.
Author_Institution :
Dept. of Electr. & Comput Eng., Wisconsin Univ., Madison, WI, USA
fDate :
3/1/1989 12:00:00 AM
Abstract :
The asymptotic probability of error for quantization in maximum-likelihood tests is analyzed. The authors assume quantizers with large numbers of levels generated from a companding function. A theorem that relates the companding function to the asymptotic probability of error is proved. The companding function is then optimized
Keywords :
error statistics; information theory; probability; signal detection; alpha entropy; asymptotic probability of error; companding function; error probability; independent identically distributed data; maximum-likelihood tests; optimal quantizers; quantization; signal detection; Computer errors; Degradation; Distortion measurement; Error probability; Estimation theory; Maximum likelihood detection; Maximum likelihood estimation; Quantization; Size measurement; Testing;
Journal_Title :
Information Theory, IEEE Transactions on
