scholarly journals Chapter 1. Research methods

2019 ◽  
pp. 10-35
Author(s):  
Olga E. Dik ◽  
◽  
Alexander D. Nozdrachev ◽  
Keyword(s):  
Qualitative Change ◽  
Wavelet Spectrum ◽  
Physiological Signals ◽  
Wavelet Coherence ◽  
Time Interval ◽  
Wavelet Transform Modulus Maxima ◽  
Integral Distribution ◽  
Modulus Maxima ◽  
Cross Wavelet

The first chapter presents methods for analyzing nonstationary physiological signals. Among them are 1) the method of continuous wavelet analysis, which allows obtaining the local and integral distribution of the energy of the wavelet spectrum of the signal over frequencies in a certain time interval, as well as providing information on the cross-wavelet spectrum and wavelet coherence of two signals; 2) methods for assessing the multifractality of a signal by searching for the maxima of the wavelet transform modulus maxima and by analyzing fluctuations relative to the trend; 3) the method of recurrent analysis, which allows to identify the quantitative parameters of the evolution of the signal in time, 4) the method of bifurcation analysis, which allows finding the values of the system parameters at which a qualitative change in the solution of the system occurs, for example, a change in the mode of impulse activity of a neuron.

scholarly journals Multi-scale investigation on streamflow temporal variability and its connection to global climate indices for unregulated rivers in India

2021 ◽  
Author(s):  
Pavan Kumar Yeditha ◽  
Tarun Pant ◽  
Maheswaran Rathinasamy ◽  
Ankit Agarwal
Keyword(s):  
Wavelet Transform ◽  
Temporal Variability ◽  
Global Climate ◽  
Phase Relationship ◽  
Wavelet Coherence ◽  
Climate Indices ◽  
Coherence Analysis ◽  
Cross Wavelet Transform ◽  
Wavelet Coherence Analysis ◽  
Cross Wavelet

Abstract With the increasing stress on water resources for a developing country like India, it is pertinent to understand the dominant streamflow patterns for effective planning and management activities. This study investigates the spatiotemporal characterization of streamflow of six unregulated catchments in India. Firstly, Mann Kendall (MK) and Changepoint analysis were carried out to detect the presence of trends and any abrupt changes in hydroclimatic variables in the chosen streamflows. To unravel the relationships between the temporal variability of streamflow and its association with precipitation and global climate indices, namely, Niño 3.4, IOD, PDO, and NAO, continuous wavelet transform is used. Cross-wavelet transform and wavelet coherence analysis was also used to capture the coherent and phase relationships between streamflow and climate indices. The continuous wavelet transforms of streamflow data revealed that intra-annual (0.5 years), annual (1 year), and inter-annual (2–4 year) oscillations are statistically significant. Furthermore, a better understanding of the in-phase relationship between the streamflow and precipitation at intra-annual and annual time scales were well-captured using wavelet coherence analysis compared to cross wavelet transform. Furthermore, our analysis also revealed that streamflow observed an in-phase relationship with IOD and NAO, whereas a lag correlation with Niño 3.4 and PDO indices at intra-annual, annual and interannual time scales.

Study for Detection Algorithm of QRS Complex in ECG Signal

2013 ◽  
Vol 765-767 ◽  
pp. 2105-2108
Author(s):  
Xu Wen Li ◽  
Bi Wei Zhang ◽  
Qiang Wu
Keyword(s):  
Wavelet Transform ◽  
Detection Algorithm ◽  
Automatic Analysis ◽  
Detection Accuracy ◽  
Ecg Signal ◽  
Good Precision ◽  
Qrs Complex ◽  
Noise Interference ◽  
Wavelet Transform Modulus Maxima ◽  
Modulus Maxima

In ECG signals accurate detection to the position of QRS complex is a key to automatic analysis and diagnosis system. And its premise is that effectively remove all kinds of noise interference in ECG signal. Here, a method of detecting QRS based on EMD and wavelet transform was presented which is aim to improve the anti-noise performance of the detection algorithm. It is combined EMD with the theory of singularity detecting based on wavelet transform modulus maxima method. It has the high detection accuracy and good precision that can give an effective way to the automatic analysis for ECG signal.

Numerical Methods of Multifractal Analysis in Information Communication Systems and Networks

2013 ◽  
pp. 16-46
Author(s):  
Oleg I. Sheluhin ◽  
Artem V. Garmashev
Keyword(s):  
Communication Systems ◽  
Multifractal Analysis ◽  
Fractal Dimensions ◽  
Multifractal Spectrum ◽  
Telecommunication Networks ◽  
Information Communication ◽  
Novel Approach ◽  
Wavelet Transform Modulus Maxima ◽  
Modulus Maxima ◽  
Development Methods

In this chapter, the main principles of the theory of fractals and multifractals are stated. A singularity spectrum is introduced for the random telecommunication traffic, concepts of fractal dimensions and scaling functions, and methods used in their determination by means of Wavelet Transform Modulus Maxima (WTMM) are proposed. Algorithm development methods for estimating multifractal spectrum are presented. A method based on multifractal data analysis at network layer level by means of WTMM is proposed for the detection of traffic anomalies in computer and telecommunication networks. The chapter also introduces WTMM as the informative indicator to exploit the distinction of fractal dimensions on various parts of a given dataset. A novel approach based on the use of multifractal spectrum parameters is proposed for estimating queuing performance for the generalized multifractal traffic on the input of a buffering device. It is shown that the multifractal character of traffic has significant impact on queuing performance characteristics.

scholarly journals Multifractal analysis of low-latitude geomagnetic fluctuations

2009 ◽  
Vol 27 (2) ◽  
pp. 569-576 ◽  
Author(s):  
M. J. A. Bolzan ◽  
R. R. Rosa ◽  
Y. Sahai
Keyword(s):  
Solar Wind ◽  
High Latitude ◽  
Geomagnetic Field ◽  
Large Deviation ◽  
Multifractal Spectrum ◽  
Low Latitude ◽  
Physical Mechanisms ◽  
Wavelet Transform Modulus Maxima ◽  
Variability Pattern ◽  
Modulus Maxima

Abstract. The technique of large deviation multifractal spectrum has shown that the high-latitude (77.5° N, 69.2° W) geomagnetic fluctuations can be described from direct dissipation process or loading-unloading regimes of the solar wind-magnetosphere coupling. In this paper, we analyze the H-component of low-latitude (22.4° S, 43.6° W) geomagnetic field variability observed during the month of July 2000 at the Geomagnetic Observatory, Vassouras, RJ, Brazil. The variability pattern during this period is a mixture of quiet and disturbed days including the Bastille Day intense geomagnetic storm on 15 July. Due to the complexity of this data, we pursue a detailed analysis of the geomagnetic fluctuations in different time scales including a multifractal approach using the singular power spectrum deviations obtained from the wavelet transform modulus maxima (WTMM). The results suggest, as observed from high-latitude data, the occurrence of low-latitude multifractal processes driving the intermittent coupling between the solar wind-magnetosphere and geomagnetic field variations. On finer scales possible physical mechanisms in the context of nonlinear magnetosphere response are discussed.

An Improved Denoising Method in RDTS Based on Wavelet Transform Modulus Maxima

2015 ◽  
Vol 15 (2) ◽  
pp. 1061-1067 ◽  
Author(s):  
Zongliang Wang ◽  
Guangping Lv ◽  
Jun Chang ◽  
Sasa Zhang ◽  
Sha Luo ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Denoising Method ◽  
Wavelet Transform Modulus Maxima ◽  
Modulus Maxima
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