Conventional Fast Fourier Transform Method Research Articles

Optimizing vertical ground heat exchanger modelling through GPU-accelerated computation strategies

Enhancing Vertical Ground Heat Exchanger (VGHE) modelling for efficient Vertical Ground-Coupled Heat Pump (VGCHP) systems, renowned for their eco-friendly operation, has garnered significant attention. Optimally designing and sustaining the long-term efficiency of VGCHP systems necessitates rigorous, protracted VGHE modelling, a process fraught with computational intensity. To surmount this challenge, this contribution introduces an accelerated VGHE modelling paradigm grounded in Graphics Processing Unit (GPU) processing. This entails employing the Finite Line Source (FLS) model based on Fast Fourier Transform (FFT). To ameliorate computational demands, the processing capabilities of both Central Processing Units (CPUs) and GPUs are harnessed, leveraging CPU- and GPU-based FFT and inverse FFT (IFFT). Hybrid and non-hybrid processing modes are explored, differentiating between CPU- and GPU-based FFT in non-hybrid scenarios, while hybrid approaches combine both for distinct simulation periods. By scrutinizing two processing systems with varying specifications, diverse CPU- and GPU-based FFT combinations are assessed. Findings unequivocally underscore the superiority of CPU-based FFT for initial years, succeeded by GPU-based FFT for ensuing years, in terms of computational efficiency. The efficacy of the hybrid computation approach is demonstrated through a reduction of total computational time in 20-year VGCHP operation simulations by up to 33.5 % compared to conventional CPU-based FFT methods.

Enhanced ISAR imaging method using back‐projection and SVA algorithm

ABSTRACTWe present an inverse synthetic aperture radar image enhancement technique that combines the plane‐wave approximation‐based back‐projection (BP) algorithm and the spatially variant apodization (SVA) method. The SVA technique is applied to reduce the sidelobe levels while retaining the cross‐range resolution. To demonstrate the performance of our algorithm, we compare the conventional fast Fourier transform (FFT)‐based algorithm, the combined FFT and SVA method, the BP algorithm, and the proposed method (combined BP and SVA method). The cross‐range resolution and peak to sidelobe ratio (PSLR) are selected as performance measures. Our algorithm has better resolution than the conventional combined FFT and SVA method, while the combined FFT and SVA method has better PSLR than our method. We validate our algorithm via a numerical simulation and measurements conducted in a compact range. © 2015 Wiley Periodicals, Inc. Microwave Opt Technol Lett 57:993–997, 2015

Calibration of optical tweezers based on an autoregressive model.

The power spectrum density (PSD) has long been explored for calibrating optical tweezers stiffness. Fast Fourier Transform (FFT) based spectral estimator is typically used. This approach requires a relatively longer data acquisition time to achieve adequate spectral resolution. In this paper, an autoregressive (AR) model is proposed to obtain the Spectrum Density using a limited number of samples. According to our method, the arithmetic model has been established with burg arithmetic, and the final prediction error criterion has been used to select the most appropriate order of the AR model, the power spectrum density has been estimated based the AR model. Then, the optical tweezers stiffness has been determined with the simple calculation from the power spectrum. Since only a small number of samples are used, the data acquisition time is significantly reduced and real-time stiffness calibration becomes feasible. To test this calibration method, we study the variation of the trap stiffness as a function of the parameters of the data length and the trapping depth. Both of the simulation and experiment results have showed that the presented method returns precise results and outperforms the conventional FFT method when using a limited number of samples.

A fast acquisition method of DSSS signals using differential decoding and fast Fourier transform

In low earth orbit (LEO) satellite or missile communication scenarios, signals may experience extremely large Doppler shifts and have short visual time. Thus, direct sequence spread spectrum (DSSS) systems should be able to achieve acquisition in a very short time in spite of large Doppler frequencies. However, the traditional methods cannot solve it well. This work describes a new method that uses a differential decoding technique for Doppler mitigation and a batch process of FFT (fast Fourier transform) and IFFT (invert FFT) for the purpose of parallel code phase search by frequency domain correlation. After the code phase is estimated, another FFT process is carried out to search the Doppler frequency. Since both code phase and Doppler frequency domains are searched in parallel, this architecture can provide acquisition fifty times faster than conventional FFT methods. The performance in terms of the probability of detection and false alarm are also analyzed and simulated, showing that a signal-to-noise ratio (SNR) loss of 3 dB is introduced by the differential decoding. The proposed method is an efficient way to shorten the acquisition time with slightly hardware increasing.

高速フーリエ変換法を用いたセレーションの評価

Fast Fourier Transform (FFT) method was applied in order to evaluate a repeated load drop (serration) observed in the load-time curves in the tensile test. 5083 aluminum alloy plates were tested in tension at temperatures between 203 K and 333 K using an Instron type tensile test machine. Changes in repeated load drops with the deformation temperature were characterized by a conventional method (mean amplitude ΔLm and number N of load drops) and FFT method (maximum amplitude Cmax and peak frequency fp derived from the Fourier spectrum). Cmax and fp were compared with ΔLm and N, respectively. The comparison showed the reasonable agreement between fp and N, as well as that of Cmax and ΔLm. In evaluation of the serration using FFT method, there was no artificial reading error and reliable analysis could be carried out in a short time. Therefore it suggests that FFT method is suitable for the investigation of the serration.

Adaptive, autoregressive spectral estimation for analysis of electrical signals of gastric origin

The electrical activity of the human stomach, which normally shows a frequency of about 0.05 Hz, may be studied non-invasively by either cutaneous electrogastrography (EGG) or surface magnetogastrography (MGG). Detection of changes in frequency with time may be useful to characterize gastric disorders. The fast Fourier transform (FFT) has been the most commonly used method for the automated spectral analysis of the signals obtained from the EGG or the MGG. We have used an autoregressive (AR) parametric spectrum estimator to analyse simulated signals of gastric electrical activity, and to evaluate the results of human studies using EGG and MGG. In comparison with the FFT, our results showed that the AR spectrum estimator provided more detailed qualitative information about frequency variations of short duration simulated signals than the FFT. In the human studies, the AR estimator was as good as the conventional FFT methods in detecting physiological changes in frequency and in identifying abnormal recordings. We conclude that the AR spectral estimator may provide a better qualitative analysis of frequency variations in small portions of the signal, and is as useful as the FFT to analyse human EGG or MGG studies.

Doppler angle estimation of pulsatile flows using AR modeling.

In quantitative ultrasonic flow measurements, the beam-to-flow angle (i.e., Doppler angle) is an important parameter. An autoregressive (AR) spectral analysis technique in combination with the Doppler spectrum broadening effect was previously proposed to estimate the Doppler angle. Since only a limited number of flow samples are used, real-time two-dimensional Doppler angle estimation is possible. The method was validated for laminar flows with constant velocities. In clinical applications, the flow pulsation needs to be considered. For pulsatile flows, the flow velocity is time-varying and the accuracy of Doppler angle estimation may be affected. In this paper, the AR method using only a limited number of flow samples was applied to Doppler angle estimation of pulsatile flows. The flow samples were properly selected to derive the AR coefficients and then more samples were extrapolated based on the AR model. The proposed method was verified by both simulations and in vitro experiments. A wide range of Doppler angles (from 3o degrees to 78 degrees) and different flow rates were considered. The experimental data for the Doppler angle showed that the AR method using eight flow samples had an average estimation error of 3.50 degrees compared to an average error of 7.08 degrees for the Fast Fourier Transform (FFT) method using 64 flow samples. Results indicated that the AR method not only provided accurate Doppler angle estimates, but also outperformed the conventional FFT method in pulsatile flows. This is because the short data acquisition time is less affected by the temporal velocity changes. It is concluded that real-time two-dimensional estimation of the Doppler angle is possible using the AR method in the presence of pulsatile flows. In addition, Doppler angle estimation with turbulent flows is also discussed. Results show that both the AR and FFT methods are not adequate due to the spectral broadening effects from the turbulence.

Super resolution SAR imaging via parametric spectral estimation methods

Super resolution synthetic aperture radar (SAR) image formation via sophisticated parametric spectral estimation algorithms is considered. Parametric spectral estimation methods are devised based on parametric data models and are used to estimate the model parameters. Since SAR images rather than model parameters are often used in SAR applications, we use the parameter estimates obtained with the parametric methods to simulate data matrices of large dimensions and then use the fast Fourier transform (FFT) methods on them to generate SAR images with super resolution. Experimental examples using the MSTAR and Environmental Research Institute of Michigan (ERIM) data illustrate that robust spectral estimation algorithms can generate SAR images of higher resolution than the conventional FFT methods and enhance the dominant target features.

The extended function fast Fourier transform (EF-FFT)

The periodicity assumption implicit in fast Fourier transform (FFT) techniques can be utilized through time-domain prealiasing to obtain the spectral components of infinite-duration time-domain reflectometry signals when they can be modeled, outside the observation window, with step and/or exponential functions. The technique is shown to be more accurate than both conventional windowing and the other FFT approaches described in the literature for analysis of steplike signals. The duality equation relating the extension functions introduced in the extended function FFT (EF-FFT) method to conventional window functions is derived. Using this relation, it is shown that signals with high-frequency content only within the observation window are best analyzed with EF-FFT methods and that signals with time-distributed spectral components (e.g., speech) are best analyzed with conventional FFT methods.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

On the inclusion of upper Laue layers in computational methods in high resolution transmission electron microscopy

Three different methods for computing scattering amplitudes in High Resolution Transmission Electron Microscopy (HRTEM) have been investigated as to their ability to include upper Laue layer (ULL) interaction. The conventional first-order multislice method using fast Fourier transform (FFT) and the second-order multislice method (SOM method) are shown to yield calculated intensities of first-order Laue reflections with the use of slice thicknesses smaller than the crystal periodicity along the incident electron beam direction. It is argued that the calculated intensities of ULL reflections approach the correct values in the limiting case of vanishing slice thickness and electron wavelength. The third method, the improved phasegrating method (IPG), does also in principle include ULL effects, but is severely limited as to choice of slice thickness and sampling interval. A practical way to use slice thicknesses less than the crystal periodicity along the incident beam direction is shown for both the conventional FFT method and the second-order multislice method and tested on a spinel structure. It is also shown that the IPG method does not easily allow for aslice thickness different from the crystal periodicity in the beam direction.

CALCULATION OF DIRECTIONAL WAVE SPECTRA BY THE MAXIMUM ENTROPY METHOD OF SPECTRAL ANALYSIS

Two analysis techniques for calculating directional wave spectra from measured pressure and biaxial current components were intercompared using data from the 25 October 1980 Atlantic Remote Sensing Land Ocean Experiment (ARSLOE) storm. The two methods are the conventional Fast Fourier Transform (FFT) method and a Maximum Entropy Method (MEM). The MEM is a nonlinear data adaptive method of spectral analysis which is capable of generating higher resolution spectral estimates from shorter data records than conventional FFT methods. The MEM has shown good agreement with the frequency and directional wave spectra calculated using conventional methods.