scholarly journals Corrigendum to ‘A multiscale time-space approach to analyze and categorize the precipitation fluctuation based on the wavelet transform and information theory concept’ [Hydrology Research 49 (3), 724–743. https://doi.org/10.2166/nh.2018.143]

2018 ◽  
Vol 50 (1) ◽  
pp. 416-416
Author(s):  
Kiyoumars Roushangar ◽  
Vahid Nourani ◽  
Farhad Alizadeh
Keyword(s):  
Information Theory ◽  
Wavelet Transform ◽  
Time Space ◽  
Space Approach

scholarly journals Duration Perception Versus Perception Duration: A Proposed Model for the Consciously Experienced Moment

2019 ◽  
Vol 7 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Lachlan Kent
Keyword(s):  
Information Theory ◽  
Prediction Error ◽  
Intermediate Stage ◽  
The Self ◽  
Global Integration ◽  
Candidate Model ◽  
Time Space ◽  
Proposed Model ◽  
Concrete Objects ◽  
Integrated Information Theory

Duration perception is not the same as perception duration. Time is an object of perception in its own right and is qualitatively different to exteroceptive or interoceptive perception of concrete objects or sensations originating within the self. In reviewing evidence for and against the experienced moment, White (2017, Psychol. Bull., 143, 735–756) proposed a model of global integration of information dense envelopes of integration. This is a valuable addition to the literature because it supposes that, like Tononi’s (2004, BMC Neurosci., 5, 42) Integrated Information Theory, consciousness is an integral step above perception of objects or the self. Consciousness includes the perception of abstract contents such as time, space, and magnitude, as well as post-perceptual contents drawn from memory. The present review takes this logic a step further and sketches a potential neurobiological pathway through the salience, default mode, and central executive networks that culminates in a candidate model of how duration perception and consciousness arises. Global integration is viewed as a process of Bayesian Prediction Error Minimisation according to a model put forward by Hohwy, Paton and Palmer (2016, Phenomenol. Cogn. Sci., 15, 315–335) called ‘distrusting the present’. The proposed model also expresses global integration as an intermediate stage between perception and memory that spans an approximate one second duration, an analogue of Wittmann’s (2011, Front. Integr. Neurosci., 5, 66) experienced moment.

scholarly journals Time-space characterization of droughts in the São Francisco river catchment using the Standard Precipitation Index and continuous wavelet transform

RBRH ◽  
2019 ◽  
Vol 24 ◽  
Author(s):  
Marcus Suassuna Santos ◽  
Veber Afonso Figueiredo Costa ◽  
Wilson dos Santos Fernandes ◽  
Rafael Pedrollo de Paes
Keyword(s):  
Time Series ◽  
Wavelet Transform ◽  
Continuous Wavelet Transform ◽  
Large Scale ◽  
Continuous Wavelet ◽  
River Catchment ◽  
Time Space ◽  
L Moments ◽  
Space Characterization

ABSTRACT This paper focuses on time-space characterization of drought conditions in the São Francisco River catchment, on the basis of wavelet analysis of Standardized Precipitation Index (SPI) time series. In order to improve SPI estimation, the procedures for regional analysis with L-moments were employed for defining statistically homogeneous regions. The continuous wavelet transform was then utilized for extracting time-frequency information from the resulting SPI time series in a multiresolution framework and for investigating possible teleconnections of these signals with those obtained from samples of the large-scale climate indexes ENSO and PDO. The use of regional frequency analysis with L-moments resulted in improvements in the estimation of SPI time series. It was observed that by aggregating regional information more reliable estimates of low frequency rainfall amounts were obtained. The wavelet analysis of climate indexes suggests that the more extreme dry periods in the study area are observed when the cold phase of both ENSO and the PDO coincides. While not constituting a strict cause effect relationship, it was clear that the more extreme droughts are consistently observed in this situation. However, further investigation is necessary for identifying particularities in rainfall patterns that are not associated to large-scale climate anomalies.

Co-movement of precious metals and forecasting using scale by scale wavelet transform

2017 ◽  
Vol 04 (01) ◽  
pp. 1750007 ◽  
Author(s):  
Emrah Oral ◽  
Gazanfer Unal
Keyword(s):  
Time Series ◽  
Wavelet Transform ◽  
Moving Average ◽  
Precious Metals ◽  
Wavelet Coherence ◽  
Frequency Scale ◽  
Time Space ◽  
Daily Data ◽  
Gold Silver ◽  
Highly Correlated

In this paper, a new approach is proposed to improve forecasting performances. We analyze the co-movement of precious metals (daily data of gold, silver and platinum starting from July, 2011) using multiple wavelet coherence and determine the movement dependencies on frequency–time space. The data is split into frequencies using scale by scale continuous wavelet transform. All three time series retaining the same frequency scale are (i) selected, (ii) inversed and (ii) forecasted using multivariate model, Vector Auto Regressive Moving Average (VARMA). We conclude that the efficiency of VARMA forecasting is substantially increased because of same frequency highly correlated time series obtained by using scale by scale wavelet transform. Moreover, the direction of price shift (increasing/decreasing trend) is prospected to an adequately distinguishable degree.

scholarly journals A multiscale time-space approach to analyze and categorize the precipitation fluctuation based on the wavelet transform and information theory concept

2018 ◽  
Vol 49 (3) ◽  
pp. 724-743 ◽  
Author(s):  
Kiyoumars Roushangar ◽  
Vahid Nourani ◽  
Farhad Alizadeh
Keyword(s):  
Time Series ◽  
Wavelet Transform ◽  
Multiple Scales ◽  
Multiscale Entropy ◽  
Discrete Wavelet ◽  
Monthly Precipitation ◽  
Precipitation Time Series ◽  
Rain Gauges ◽  
Time Space ◽  
Precipitation Variation

AbstractThe present study proposed a time-space framework using discrete wavelet transform-based multiscale entropy (DWE) approach to analyze and spatially categorize the precipitation variation in Iran. To this end, historical monthly precipitation time series during 1960–2010 from 31 rain gauges were used in this study. First, wavelet-based de-noising approach was applied to diminish the effect of noise in precipitation time series which may affect the entropy values. Next, Daubechies (db) mother wavelets (db5–db10) were used to decompose the precipitation time series. Subsequently, entropy concept was applied to the sub-series to measure the uncertainty and disorderliness at multiple scales. According to the pattern of entropy across scales, each cluster was assigned an entropy signature that provided an estimation of the entropy pattern of precipitation in each cluster. Spatial categorization of rain gauges was performed using DWE values as input data to k-means and self-organizing map (SOM) clustering techniques. According to evaluation criteria, it was proved that k-means with clustering number equal to 5 with Silhouette coefficient=0.33, Davis–Bouldin=1.18 and Dunn index=1.52 performed better in determining homogenous areas. Finally, investigating spatial structure of precipitation variation revealed that the DWE had a decreasing and increasing relationship with longitude and latitude, respectively, in Iran.

Analysis of Time-Signal of an Industrial Gas Turbine Combustor Under an Unstable Condition

2016 ◽  
Author(s):  
D. Lengani ◽  
P. Zunino ◽  
F. Romoli ◽  
E. Bertolotto ◽  
S. Rizzo
Keyword(s):  
Fourier Transform ◽  
Wavelet Transform ◽  
Combustion Chamber ◽  
Gas Turbine ◽  
Limit Cycle ◽  
Limit Cycle Oscillations ◽  
Unstable Condition ◽  
Gas Turbine Combustor ◽  
Time Space ◽  
Industrial Gas Turbine

This paper analyzes the time-signals of pressure sensors mounted in an industrial gas turbine combustor under an unstable condition. The present investigation is aimed at the discussion of the sudden increase in amplitude due to the limit-cycle oscillations and of its temporal evolution. To this purpose, different post-processing tools are described and adopted: i.e. wavelet transform, cross-correlations, time-space Fourier transform and proper orthogonal decomposition (POD). The properties of the wavelet transform are used in order to identify the time of occurrence and the frequency of the limit-cycle oscillations. They occur at the second harmonic of the natural frequency of the annular combustion chamber. The amplitude of the pressure fluctuations at this characteristic frequency increases to a critical value with very large amplitude in about 0.15s that corresponds to about 26 periods of the phenomenon. Within this period, the pressure signals from two neighboring burners have a quite large and increasing degree of correlation as it is observed from the cross-correlation of the signals. The time-space Fourier transform suggests that the instability couples with a natural mode of the combustion chamber. The azimuthal wave length of such mode is half of the combustion chamber circumference (this corresponds to an azimuthal mode 2). According to this findings, the POD is used to provide an identifier for the occurrence of the limit-cycle oscillations. In fact, POD is known to isolate the deterministic fluctuations based on an energy rank. Hence, the first POD mode isolates the effect of specific frequency forcing and its energy content is retained in the first POD eigenvalue which is used as identifier.

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