DocumentCode
388532
Title
Artificial intelligence applied to spectrum estimation
Author
Gaby, James H. ; Hayes, Monson H.
Author_Institution
Georgia Institute of Technology, Atlanta, Georgia
Volume
9
fYear
1984
fDate
30742
Firstpage
546
Lastpage
549
Abstract
Many techniques are available for the estimation of the power spectrum of a stationary random process. While power spectrum estimation is a problem which falls within the domain of signal processing, the problem of inferring information falls within the domain of artificial intelligence (AI). With a wide variety of different types of power spectrum estimation techniques to choose from, an equally wide range of differing spectral estimates may be produced. Each estimate, however, may be used to infer information about the time series. By defining an appropriate knowledge base, a system is being developed to infer information from power spectrum estimates. This system combines the estimates produced by a variety of current spectrum estimation techniques in order to formulate a composite spectral estimate.
Keywords
Artificial intelligence; Corporate acquisitions; Data mining; Power engineering and energy; Prototypes; Random processes; Signal generators; Signal processing; Spectral analysis; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '84.
Type
conf
DOI
10.1109/ICASSP.1984.1172313
Filename
1172313
Link To Document