Periodic phenomena are oscillating signals found in many naturally-occurring time series. A periodogram can be used to measure the intensities of oscillations at different frequencies over an entire time series but sometimes we are interested in measuring how periodicity intensity at a specific frequency varies throughout the time series. This can be done by calculating periodicity intensity within a window then sliding and recalculating the intensity for the window, giving an indication of how periodicity intensity at a specific frequency changes throughout the series. We illustrate three applications of this the first of which is movements of a herd of new-born calves where we show how intensity of the 24h periodicity increases and...
Summary: To test the hypotheses that (i) electroencephalograms (EEGs) are largely made up of oscill...
International audienceIn condition monitoring a part of the information necessary for decision-makin...
Time series analysis is a fundamental task in various application domains, and deep learning approac...
Periodic phenomena are oscillating signals found in many naturally-occurring time series. A periodo...
Periodic phenomena are oscillating signals found in many naturally occurring time series. A periodog...
Periodic phenomena or oscillating signals can be found frequently in nature and recent research has ...
Develop a framework for identifying meaningful periodicities (i.e., repeating patterns) and the stre...
This paper introduces a new way to analyse and visualize quantified-self or lifelog data captured f...
Periodically occurring accumulations of events or measured values are present in many time-dependent...
Periodicity is at the core of the recognition of many actions. This paper takes the following steps ...
Many recent papers have documented periodicities in returns, return volatility, bid–ask spreads and ...
abstract: Periodicities (repeating patterns) are observed in many human behaviors. Their strength ma...
Periodicities (repeating patterns) are observed in many human behaviors. Their strength may capture ...
xix, 121 leaves : ill. ; 30 cm.PolyU Library Call No.: [THS] LG51 .H577P EIE 2007 ZhangTime series m...
We address the problem of observing periodic changes in the behaviour of a large population, by anal...
Summary: To test the hypotheses that (i) electroencephalograms (EEGs) are largely made up of oscill...
International audienceIn condition monitoring a part of the information necessary for decision-makin...
Time series analysis is a fundamental task in various application domains, and deep learning approac...
Periodic phenomena are oscillating signals found in many naturally-occurring time series. A periodo...
Periodic phenomena are oscillating signals found in many naturally occurring time series. A periodog...
Periodic phenomena or oscillating signals can be found frequently in nature and recent research has ...
Develop a framework for identifying meaningful periodicities (i.e., repeating patterns) and the stre...
This paper introduces a new way to analyse and visualize quantified-self or lifelog data captured f...
Periodically occurring accumulations of events or measured values are present in many time-dependent...
Periodicity is at the core of the recognition of many actions. This paper takes the following steps ...
Many recent papers have documented periodicities in returns, return volatility, bid–ask spreads and ...
abstract: Periodicities (repeating patterns) are observed in many human behaviors. Their strength ma...
Periodicities (repeating patterns) are observed in many human behaviors. Their strength may capture ...
xix, 121 leaves : ill. ; 30 cm.PolyU Library Call No.: [THS] LG51 .H577P EIE 2007 ZhangTime series m...
We address the problem of observing periodic changes in the behaviour of a large population, by anal...
Summary: To test the hypotheses that (i) electroencephalograms (EEGs) are largely made up of oscill...
International audienceIn condition monitoring a part of the information necessary for decision-makin...
Time series analysis is a fundamental task in various application domains, and deep learning approac...