DocumentCode
387844
Title
Periodicity estimation by hypothesis-directed search
Author
Amuedo, John
Author_Institution
M.I.T. Artificial Intelligence Laboratory, Cambridge, Mass.
Volume
10
fYear
1985
fDate
31138
Firstpage
395
Lastpage
398
Abstract
Some methods are described for estimating the fundamental periodicity of additively combined quasi-periodic signals. These methods operate from measurements of the instantaneous amplitudes and frequencies of important sinusoidal components of the input signal. The methods share a similar computational structure, in which each component is allowed to assert a number of hypotheses as to possible fundamental periodicities to which it is related. Hypotheses from different components are combined in such a way as to reinforce common periodicities shared by several components. The methods discussed seem well suited to signals whose fundamental frequencies may be high, and vary over a wide range.
Keywords
Artificial intelligence; Frequency estimation; Frequency measurement; Humans; Laboratories; Multiple signal classification; Music; Signal analysis; Signal resolution; Speech analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '85.
Type
conf
DOI
10.1109/ICASSP.1985.1168414
Filename
1168414
Link To Document