Formulae for Facilitating Computations in Time Series Analyses

this study investigates the relationship between acoustic patterns in contemporary electroacoustic compositions, and listeners' real-time perceptions of their structure and affective content. Thirty-two participants varying in musical expertise (nonmusicians, classical musicians, expert computer musicians) continuously rated the affect (arousal and valence) and structure (change in sound) they perceived in four compositions of approximately three minutes duration. Time series analyses tested the hypotheses that sound intensity influences listener perceptions of structure and arousal, and spectral flatness influences perceptions of structure and valence. Results suggest that intensity strongly influences perceived change in sound, and to a lesser extent listener perceptions of arousal. Spectral flatness measures were only weakly related to listener perceptions, and valence was not strongly shaped by either acoustic measure. Differences in response by composition and musical expertise suggest that, particularly with respect to the perception of valence, individual experience (familiarity and liking), and meaningful sound associations mediate perception.

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A distributed computing system for multivariate time series analyses of multichannel neurophysiological data

Journal of Neuroscience Methods ◽

10.1016/j.jneumeth.2005.09.002 ◽

2006 ◽

Vol 152 (1-2) ◽

pp. 190-201 ◽

Cited By ~ 17

Author(s):

Andy Müller ◽

Hannes Osterhage ◽

Robert Sowa ◽

Ralph G. Andrzejak ◽

Florian Mormann ◽

...

Keyword(s):

Time Series ◽

Distributed Computing ◽

Multivariate Time Series ◽

Computing System ◽

Neurophysiological Data ◽

Time Series Analyses

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Measuring Value Change in Western Industrialized Societies: The Impact of Unemployment

American Political Science Review ◽

10.2307/1963855 ◽

1991 ◽

Vol 85 (3) ◽

pp. 905-920 ◽

Cited By ~ 77

Author(s):

Harold D. Clarke ◽

Nitish Dutt

Keyword(s):

Time Series ◽

Economic Conditions ◽

Aggregate Level ◽

Value Change ◽

Short Term ◽

Cross Sectional ◽

The Past ◽

Value Priorities ◽

Time Series Analyses ◽

The Impact

During the past two decades a four-item battery administered in biannual Euro-Barometer surveys has been used to measure changing value priorities in Western European countries. We provide evidence that the measure is seriously flawed. Pooled cross-sectional time series analyses for the 1976–86 period reveal that the Euro-Barometer postmaterialist-materialist value index and two of its components are very sensitive to short-term changes in economic conditions, and that the failure to include a statement about unemployment in the four-item values battery accounts for much of the apparent growth of postmaterialist values in several countries after 1980. The aggregate-level findings are buttressed by analyses of panel data from three countries.

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An Enquiry Into Linear Conflict Models

10.5771/9783748912088 ◽

2021 ◽

Author(s):

Klaus B. Beckmann ◽

Lennart Reimer

Keyword(s):

Time Series ◽

Monte Carlo ◽

Bounded Rationality ◽

Dynamic Models ◽

Conflict Analysis ◽

Monte Carlo Techniques ◽

Linear Dynamic ◽

Rich Variety ◽

Time Series Analyses ◽

Linear Dynamic Models

This monograph generalises, and extends, the classic dynamic models in conflict analysis (Lanchester 1916, Richardson 1919, Boulding 1962). Restrictions on parameters are relaxed to account for alliances and for peacekeeping. Incrementalist as well as stochastic versions of the model are reviewed. These extensions allow for a rich variety of patterns of dynamic conflict. Using Monte Carlo techniques as well as time series analyses based on GDELT data (for the Ethiopian-Eritreian war, 1998–2000), we also assess the empirical usefulness of the model. It turns out that linear dynamic models capture selected phases of the conflict quite well, offering a potential taxonomy for conflict dynamics. We also discuss a method for introducing a modicum of (bounded) rationality into models from this tradition.

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Analysis of Stall Precursors and Determination of Optimum Signal Processing Methods for an LM-2500 Gas Turbine

Volume 7: Education; Industrial and Cogeneration; Marine; Oil and Gas Applications ◽

10.1115/gt2008-50575 ◽

2008 ◽

Author(s):

Knox T. Millsaps ◽

Gustave C. Dahl ◽

Daniel E. Caguiat ◽

Jeffrey S. Patterson

Keyword(s):

Time Series ◽

Signal Processing ◽

Gas Turbine ◽

Rotor Speed ◽

Processing Methods ◽

Turbine Engine ◽

Pressure Signal ◽

Time Series Analyses ◽

Signal Processing Methods

This paper presents an analysis of data taken from several stall initiation events on a GE LM-2500 gas turbine engine. Specifically, the time series of three separate pressure signals located at compressor stages 3, 6, and 15 were analyzed utilizing various signal processing methods to determine the most reliable indicator of incipient stall for this engine. The spectral analyses performed showed that rotating precursor waves traveling around the annulus at approximately half of the rotor speed were the best indicators. Non-linear chaotic time series analyses were also used to predict stall, but it was not as reliable an indicator. Several algorithms were used and it was determined that stall wave perturbations can be reliably identified about 900 revolutions prior to the stall. This work indicates that a single pressure signal located at stage 3 on an LM-2500 gas turbine is sufficient to provide advance warning of more than 2 seconds prior to the fully developed stall event.

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