DocumentCode :
1847555
Title :
Improved type-based detection of analog signals
Author :
Johnson, Don H. ; Gonçalvès, Paulo A. ; Baraniuk, Richard G.
Author_Institution :
Dept. of Electr. & Comput. Eng., Rice Univ., Houston, TX, USA
Volume :
5
fYear :
1997
fDate :
21-24 Apr 1997
Firstpage :
3717
Abstract :
When applied to continuous-time observations, type-based detection strategies are limited by the necessity to crudely quantize each sample. To alleviate this problem, we smooth the types for both the training and observation data with a linear filter. This post-processing improves the detector performance significantly (error probabilities decrease by over a factor of three) without incurring a significant computational penalty. However this improvement depends on the amplitude distribution and on the quantizer´s characteristics
Keywords :
adaptive signal detection; computational complexity; continuous time systems; quantisation (signal); signal sampling; smoothing methods; adaptive signal detection; amplitude distribution; analog signals; computational complexity; continuous time observations; detector performance; error probabilities; linear filter; observation data; postprocessing; sample quantization; smoothing method; training data; type based detection; Concatenated codes; Detectors; Error probability; Information theory; Quantization; Signal detection; Spread spectrum communication; Statistical analysis; Testing; Training data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1997. ICASSP-97., 1997 IEEE International Conference on
Conference_Location :
Munich
ISSN :
1520-6149
Print_ISBN :
0-8186-7919-0
Type :
conf
DOI :
10.1109/ICASSP.1997.604676
Filename :
604676
Link To Document :
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