• Korean Journal of Optics and Photonics
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• v.30 no.2
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• pp.48-58
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• 2019

We investigate the signal-to-noise ratios (SNRs) of time-domain (i.e. pulsed illumination) and frequency-domain (i.e. chirped illumination) photoacoustic signals measured by a spherically focused ultrasound transducer for spherical absorbers. The simulation results show that the time-domain photoacoustic SNR is higher than that of frequency-domain photoacoustic signals, as reported in the previous literature. We understand the reason for this SNR gap between the two measurement modes by analyzing photoacoustic-signal spectra, considering the incident beam energy controlled by the maximum permissible exposure. As the result of this approach, we find that filtering off the DC term in the chirped signal's spectrum improves frequency-domain photoacoustic SNRs by up to approximately 5 dB. In particular, it is observed that photoacoustic SNRs are highly sensitive to an upper-frequency value of frequency filtering functions, and the optimal upper-frequency values maximizing the SNR are different in time- and frequency-domain photoacoustic measurements.

• Communications for Statistical Applications and Methods
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• v.24 no.1
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• pp.1-13
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• 2017

This manuscript summarized advances in bootstrap methods for long-range dependent time series data. The stationary linear long-memory process is briefly described, which is a target process for bootstrap methodologies on time-domain and frequency-domain in this review. We illustrate time-domain bootstrap under long-range dependence, moving or non-overlapping block bootstraps, and the autoregressive-sieve bootstrap. In particular, block bootstrap methodologies need an adjustment factor for the distribution estimation of the sample mean in contrast to applications to weak dependent time processes. However, the autoregressive-sieve bootstrap does not need any other modification for application to long-memory. The frequency domain bootstrap for Whittle estimation is provided using parametric spectral density estimates because there is no current nonparametric spectral density estimation method using a kernel function for the linear long-range dependent time process.

• Current Optics and Photonics
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• v.2 no.3
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• pp.250-260
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• 2018

A pressure wave created by the photoacoustic effect is affected by the medium and by laser parameters. The effect of these parameters on the generated pressure wave can be seen by solving the photoacoustic wave equation. These solutions which are examined in the time domain and the frequency domain should be considered by researchers in acoustic sensor design. In particular, frequency domain analysis contains significant information for designing the sensor. The most important part of this information is the determination of the operating frequency of the sensor. In this work, the laser parameters to excite the medium, and the acoustic signal parameters created by the medium are analyzed. For the first time, we have obtained solutions for situations which have no frequency domain solutions in the literature. The main focal point in this work is that the frequency domain solutions of the acoustic wave equation are performed and the effects of the frequency analysis of the related parameters are shown comparatively from the viewpoint of using them in acoustic sensor designs.

• The Journal of the Acoustical Society of Korea
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• v.29 no.1
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• pp.41-47
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• 2010

The pitch alteration technique for voice conversion is classified in time domain, frequency domain and hybrid domain. The Hybrid domain method has a merit of clearness and natural-ness of pitch altered speech but has the major drawback of long processing time. In this paper, we proposed a new method that can reduce the processing time of pitch alteration in time-frequency hybrid domain. We omitted the bit-reversing process of FFT and IFFT in changing the processing domain. Therefore we can reduce the processing time by 86.26% to the conventional method with same quality.

• Ocean Systems Engineering
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• v.4 no.2
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• pp.99-115
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• 2014

When caissons are mounted on a floating transportation barge and towed by a tug boat in waves, motion of the floating dock creates inertia and gravity-induced slip forces on the caisson. If its magnitude exceeds the corresponding friction force between the two surfaces, a slip may occur, which can lead to an unwanted accident. In oblique waves, both pitch and roll motions occur simultaneously and their coupling effects for slip and friction forces become more complicated. With the presence of strong winds, the slip force can appreciably be increased to make the situation worse. In this regard, the safety of the transportation process of a caisson mounted on a floating dock for various wind-wave conditions is investigated. The analysis is done by both frequency-domain approach and time-domain approach, and their differences as well as pros and cons are discussed. It is seen that the time-domain approach is more direct and accurate and can include nonlinear contributions as well as viscous effects, which are typically neglected in the linear frequency-domain approach.

• Earthquakes and Structures
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• v.3 no.2
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• pp.97-115
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• 2012

The energy-transmitting boundary, which is used in the well-known finite element method (FEM) program FLUSH, is quite efficient for the earthquake response analysis of buildings considering soil-structure interaction. However, it is applicable only in the frequency domain. The author proposed methods for transforming frequency dependent impedance into the time domain, and studied the time domain transform of the boundary. In this paper, first, the estimation methods for both the halfspace condition under the bottom of the soil model and the pseudo three-dimensional effect were studied with the time domain transmitting boundary. Next, response behavior when using the boundary was studied in detail using a practical soil and building model. The response accuracy was compared with those using viscous boundary, and the boundary that considers the excavation force. Through these studies, the accuracy and efficiency of the proposed time domain transmitting boundary were confirmed.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.180-185
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• 2008

A new method for relative error continuous and discrete time model order reduction is proposed. The reduction technique is based on two recently developed methods, namely frequency domain balanced truncation within a frequency bound and inner-outer factorization techniques. The proposed method is of interest for practical model order reduction because in this context it shows to keep the accuracy of the approximation as high as possible without sacrificing the computational efficiency. Numerical results show the accuracy and efficiency enhancement of the method.

• Journal of Biomedical Engineering Research
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• v.17 no.2
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• pp.155-164
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• 1996

In the clinical environment, measurements of some characteristics of the skeletal muscle are currently used to assess the severity of a neuromuscular disease or in some cases to assist in making a diagnosis. But a quantitative method of evaluation has not yet been introduced satisfactorily. In this paper, the skeletal EMG(biceps muscle, masseter muscle) analysis has been processed both in the time and in the frequency domain by designing the digital signal processing system based on pentium PC and transputer (IMS 7805). The experiment have been performed in five normal subjects, and various parameters have been statistically tested and compare4 As a results, the effective parameters obtained for the evaluation of skeletal EMG electrical activity are turn analysis, MiTi, MiTa, IEMG, PDF in the time domain, and are mean frequency, median frequency, skewness, kurtosis, muscle fatigue slope in the frequency domain. The designed H/W and S/W in this study can be used effectively for the establishment of EMG data base and for clinical research.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.348-369
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• 2024

With the advancement of Industry 4.0 and Industrial Internet of Things (IIoT), manufacturing increasingly seeks automation and intelligence. Temperature and vibration monitoring are essential for machinery health. Traditional abnormal state detection methodologies often overlook the intricate frequency characteristics inherent in vibration time series and are susceptible to erroneously reconstructing temperature abnormalities due to the highly similar waveforms. To address these limitations, we introduce synergistic, end-to-end, unsupervised Frequency-Time Domain Memory-Enhanced Autoencoders (FTD-MAE) capable of identifying abnormalities in both temperature and vibration datasets. This model is adept at accommodating time series with variable frequency complexities and mitigates the risk of overgeneralization. Initially, the frequency domain encoder processes the spectrogram generated through Short-Time Fourier Transform (STFT), while the time domain encoder interprets the raw time series. This results in two disparate sets of latent representations. Subsequently, these are subjected to a memory mechanism and a limiting function, which numerically constrain each memory term. These processed terms are then amalgamated to create two unified, novel representations that the decoder leverages to produce reconstructed samples. Furthermore, the model employs Spectral Entropy to dynamically assess the frequency complexity of the time series, which, in turn, calibrates the weightage attributed to the loss functions of the individual branches, thereby generating definitive abnormal scores. Through extensive experiments, FTD-MAE achieved an average ACC and F1 of 0.9826 and 0.9808 on the CMHS and CWRU datasets, respectively. Compared to the best representative model, the ACC increased by 0.2114 and the F1 by 0.1876.

• Steel and Composite Structures
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• v.46 no.3
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• pp.435-449
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• 2023

Time domain method and frequency domain method are commonly used in the current fatigue life calculation theory. The time domain method has complicated procedures and needs a large amount of calculation, while the frequency domain method has poor applicability to different materials and different spectrum, and improper selection of spectrum model will lead to large errors. Considering that artificial neural network has strong ability of nonlinear mapping and generalization, this paper applied this technique to random fatigue life prediction, and the effect of average stress was taken into account, thereby achieving more accurate prediction result of random fatigue life.