Title :
A signal analysis expert system for signal noise reduction
Author :
Heinze, Daniel T.
Author_Institution :
HRB Syst. Inc., State College, PA, USA
Abstract :
A signal-analysis expert system (SAES) has been developed to address the problem of noise-editing pulse-position modulation (PPM) signals in preparation for analysis. These signals have historically required manual noise editing, or a combination of manual and semiautomatic editing techniques. Due to the nature of the signal, standard frequency-domain noise-reduction techniques are not applicable. The objectives for SAES were to provide a substantially improved tool for automatically noise-editing the signal and to provide intelligent assistance to the signal analyst. To meet these goals, SAES uses a combination of statistical pattern recognition, image processing, and expert system technologies. The result is a tool which reduces the noise editing workload on the human analyst by approximately 80% over existing methods while retaining accuracy comparable to a human editor working manually. Implementation on a parallel-processing transputer system provides real-time processing rates
Keywords :
computerised signal processing; interference suppression; pulse position modulation; random noise; SAES; expert system; image processing; noise-editing; parallel-processing transputer system; pulse-position modulation; real-time processing rates; signal noise reduction; signal-analysis expert system; statistical pattern recognition; Expert systems; Frequency domain analysis; Humans; Image processing; Manuals; Noise reduction; Pattern recognition; Pulse modulation; Real time systems; Signal analysis;
Conference_Titel :
AI Systems in Government Conference, 1989.,Proceedings of the Annual
Conference_Location :
Washington, DC
Print_ISBN :
0-8186-1934-1
DOI :
10.1109/AISIG.1989.47310