Symmetrical fft technique and its applications to earthquake engineering

Katukura, Hiroshi; Ohno, Susumu; Izumi, Masanori

doi:10.1002/eqe.4290180510

Cited by 11 publications

(3 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To further confirm the quality of generated data, we use the Fast Fourier Transform (FFT) to obtain its frequency domain [47] and the real data (Fig. 3).…”

Section: B Frequency Domain Analysismentioning

confidence: 99%

Augmenting Seismic Data Using Generative Adversarial Network for Low-Cost MEMS Sensors

Wu¹,

Shin

Ahn

et al. 2021

IEEE Access

View full text Add to dashboard Cite

The performance of a deep learning (DL) model depends on sufficient training datasets and is related to the algorithm structure. Seismological research based on DL suffers from the lack of seismic data recorded by low-cost micro-electro-mechanical systems (MEMS) sensors whose data is usually polluted by different types of noise. Therefore, increasing seismic datasets is necessary for intelligently generating seismic data through data-augmentation techniques. However, it is difficult to characterize and measure the evolution process of seismic sequences, making the feature extraction and data generation of seismic sequences still a significant challenge. By combining the framework of Generative Adversarial Network (GAN) with long short-term memory (LSTM), attention mechanism and neural network (NN), a novel deep generation model (DGM) named EQGAN is developed to overcome the challenges, which can automatically capture the different time histories and dimension characteristics of seismic sequences, meanwhile stably generating high-quality seismic data. The reality of generated data is qualitatively clarified through the analysis of frequency domain and data autocorrelation distribution. Based on the High-throughput Screening (HTS) Theory, the quantitative evaluation index of statistical metrics is designed, and the generation performance of different machine learning models (standard GAN, LSTM, NN) is compared to prove the stability and effectiveness of EQGAN. The experimental results denote that the EQGAN has excellent stability and performance (up to 81%, much higher than that of other generation models), which provides a suitable data expansion approach for the field of seismological research.

show abstract

“…To further confirm the quality of generated data, we use the Fast Fourier Transform (FFT) to obtain its frequency domain [47] and the real data (Fig. 3).…”

Section: B Frequency Domain Analysismentioning

confidence: 99%

Augmenting Seismic Data Using Generative Adversarial Network for Low-Cost MEMS Sensors

Wu¹,

Shin

Ahn

et al. 2021

IEEE Access

View full text Add to dashboard Cite

show abstract

“…, (Katukura et al 1989) where G( ) ω and G c ( ) ω respectively denote the Fourier transform of g(t) and g c (t), and U( ) ω is the unit step function defined as: …”

Section: (T) and B(t)mentioning

confidence: 99%

Comment on Group Velocity Measurement of Surfac Waves by Wavelet Transform

Okamoto¹

2007

Terr. Atmos. Ocean. Sci.

View full text Add to dashboard Cite

ABSTRACT1 Department of Geophysics, Graduate School of Science, Kyoto University, Sakyo, Kyoto, Japan * Corresponding author address: Prof. Taishi Okamoto, Department of Geophysics, Graduate School of Science, Kyoto University, Sakyo, Kyoto, Japan; E-mail: dollar@kugi.kyoto-u.ac.jp doi: 10.3319/ TAO.2007.18.4.681(T) Yamada and Yomogida (1997) applied the discrete wavelet transform (DWT) to group velocity measurements for the first time. Although their study is one of the pioneering works in application of DWT to seismological analysis, their method gives an inaccurate value as a group velocity in some cases and requires modification. In this report, we point out the problem and propose a modified DWT method for overcoming the problem. In our method, DWT is carried out not for an analysed signal itself but for its complex envelope (Farnbach 1975). A computation algorithm for DWT coefficients for our method is given and shown to be almost the same as that by Yamada and Ohkitani (1991). The influence of the difference between the conventional method and our method on identification of group arrival times of a wave is also shown by a numerical experiment. If analysts want to identify group arrival times using DWT, our method must be adopted instead of the conventional method.

show abstract

“…the time and frequency domains. The fundamentals have been developed by Papoulis (1962); and, subsequently, Katukura et al (1989), Katukura and Hayashi (1991), and others have theoretically and practically studied these fundamentals, which include application to seismic-motion records.…”

Section: Introductionmentioning

confidence: 99%

Synthesis of Earthquake-Like Sound Using Seismic Ground-Motion Records

Hirai¹,

Fukuwa²

2014

Bulletin of the Seismological Society of America

View full text Add to dashboard Cite

Listening to a sound representing ground motion is valuable to intuitively understand an earthquake, compared with conventional methods such as observing waveforms, Fourier spectra, and response spectra. In this study, we propose a new method for generating sound representing an earthquake, which has several differences in comparison with existing methods. In our new method, an earthquake-like sound is generated by modifying the frequency information of a generating function based on the symmetric Fourier analysis theory. Applying the method to existing seismograms illustrates three features of the sound generated by this method: the sound has the same duration as the seismogram, the sound pitch corresponds to the instantaneous frequency of the seismogram, and the sound volume corresponds to the envelope amplitude of the seismogram. Furthermore, we constructed a web-based earthquake-like sound generating system called Naion. Other applications will be implemented in the future.

show abstract

Symmetrical fft technique and its applications to earthquake engineering

Cited by 11 publications

References 5 publications

Augmenting Seismic Data Using Generative Adversarial Network for Low-Cost MEMS Sensors

Augmenting Seismic Data Using Generative Adversarial Network for Low-Cost MEMS Sensors

Comment on Group Velocity Measurement of Surfac Waves by Wavelet Transform

Synthesis of Earthquake-Like Sound Using Seismic Ground-Motion Records

Contact Info

Product

Resources

About