Performance of Continuous Wavelet Transform over Fourier Transform in Features Resolutions

This study presents a comparative analysis of two image enhancement techniques, Continuous Wavelet Transform (CWT) and Fast Fourier Transform (FFT), in the context of improving the clarity of high-quality 3D seismic data obtained from the Tano Basin in West Africa, Ghana. The research focuses on a comparative analysis of image clarity in seismic attribute analysis to facilitate the identification of reservoir features within the subsurface structures. The findings of the study indicate that CWT has a significant advantage over FFT in terms of image quality and identifying subsurface structures. The results demonstrate the superior performance of CWT in providing a better representation, making it more effective for seismic attribute analysis. The study highlights the importance of choosing the appropriate image enhancement technique based on the specific application needs and the broader context of the study. While CWT provides high-quality images and superior performance in identifying subsurface structures, the selection between these methods should be made judiciously, taking into account the objectives of the study and the characteristics of the signals being analyzed. The research provides valuable insights into the decision-making process for selecting image enhancement techniques in seismic data analysis, helping researchers and practitioners make informed choices that cater to the unique requirements of their studies. Ultimately, this study contributes to the advancement of the field of subsurface imaging and geological feature identification.

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.

基于双窗全相位FFT的变流器阻抗高精度辨识新方法

为了提高变流器阻抗辨识精度,提出将布莱克曼双窗全相位快速傅里叶变换算法应用于并网变流器输出阻抗高精度辨识之中。首先,建立了dq坐标系下的三相并网变流器的dq阻抗模型;其次,基于原理分析论证了所提方法具有优良的频谱泄漏抑制性能以及较强的抗噪能力,特别适合于在施加小扰动信号背景下非线性特性较强的并网变流器输出阻抗的高精度辨识,并给出变流器阻抗辨识流程;最后,通过仿真试验,验证了方法的优越性。基于布莱克曼双窗全相位快速傅里叶变换的阻抗辨识方法,相比传统方法能以更高的精度辨识出变流器输出阻抗。

Cardiac arrhythmias detection in an ECG beat signal using fast fourier transform and artificial neural network

Cardiac Arrhythmias shows a condition of abnor-mal electrical activity in the heart which is a threat to humans. This paper presents a method to analyze electrocardiogram (ECG) signal, extract the fea-tures, for the classification of heart beats according to different arrhythmias. Data were obtained from 40 records of the MIT-BIH arrhythmia database (only one lead). Cardiac arrhythmias which are found are Tachycardia, Bradycardia, Supraventricular Tachycardia, Incomplete Bundle Branch Block, Bundle Branch Block, Ventricular Tachycardia. A learning dataset for the neural network was obtained from a twenty records set which were manually classified using MIT-BIH Arrhythmia Database Directory and docu- mentation, taking advantage of the professional experience of a cardiologist. Fast Fourier transforms are used to identify the peaks in the ECG signal and then Neural Networks are applied to identify the diseases. Levenberg Marquardt Back-Propagation algorithm is used to train the network. The results obtained have better efficiency then the previously proposed methods.

可扩展架构的超大点数FFT处理器设计

面向合成孔径雷达、遥感、电子对抗等领域研究了一款高性能的超大点数快速傅里叶变换(FFT)处理器。文中提出了一种可扩展架构,即针对不同的应用场景可以动态实时调整FFT算法的基数以及处理点数;存储器划分为16个存储模块,可以通过产生无冲突地址进行访问,输出与输入数据帧可以共享同一存储器,具备高效存储器特征。FFT运算采用并行流水线排布,当采用高基算法时,可高并行度访问存储器,实现并行计算,从而获得明显的实时性优势。FFT各级运算采用循环移位寄存器产生地址,以保证蝶算单元输入数据的抽取间隔,并在最后一级输出时进行循环移位寄存器反转操作产生地址,实现输入输出共享存储器。所提设计方法规整、高效、适用范围广泛,便于现场可编程逻辑器件以及集成电路实施,并且也将持续受益于存储器工艺的提升。

基于FFT和Masking的实时语音通话降噪算法

针对语音通话质量的提升问题,提出一种基于快速傅里叶变换(Fast Fourier Transform,FFT)和Masking技术的实时语音通话降噪算法。首先,提出一个实时语音通话降噪的基本框架,并研究了帧分割、窗函数处理及FFT的数学原理。其次,阐述了基于人耳听觉特性的Masking方法及其在频域中的应用。最后,通过逆快速傅里叶变换(Inverse Fast Fourier Transform,IFFT)将信号转换回时域,并进行实验分析。实验结果表明,该降噪算法可以有效改善语音的清晰度和整体感知质量。

Combining Cubic Spline Interpolation and Fast Fourier Transform to Extend Measuring Range of Reflectometry

The reflectometry is a common method used to measure the thickness of thin films. Using a conventional method,its measurable range is limited due to the low resolution of the current spectrometer embedded in the reflectometer.We present a simple method, using cubic spline interpolation to resample the spectrum with a high resolution,to extend the measurable transparent film thickness. A large measuring range up to 385 m in optical thickness is achieved with the commonly used system. The numerical calculation and experimental results demonstrate that using the FFT method combined with cubic spline interpolation resampling in reflectrometry, a simple,easy-to-operate, economic measuring system can be achieved with high measuring accuracy and replicability.

Fast Fourier Transform of Multi-Assets Options under Economic Recession Induced Uncertainties

A Fast Fourier transform approach has been presented by Carr & Madan (2009) on a single underlying asset. In this current research paper, we present fast Fourier transform algorithm for the valuation of Multi-asset Options under Economic Recession Induced Uncertainties. The issue of multi-dimension in both finite and infinite case of Options is part of the focus of this research. The notion of economic recession was incorporated. An intuition behind the introduction of recession induced volatility uncertainty is revealed by huge volatility variation during the period of economic recession compared to the period of recession-free. Nigeria economic recession outbreak in 2016 and its effects on the uncertainty of the payoffs of Nigeria Stocks Exchange (NSE) among other investments was among the motivating factors for proposing economic recession induced volatility in options pricing. The application of the proposed Fast Fourier Transform algorithm in handling multi-assets options was shown. A new result on options pricing was achieved and capable of yielding efficient option prices during and out of recession. Numerical results were presented on assets in 3-dimensions as an illustration taking Black Scholes prices as a bench mark for method effectiveness comparison. The key findings of this research paper among other crucial contributions could be seen in computational procedure of options valuation in multi-dimensions and uncertainties in options payoffs under the exposure of economic recession.

Enhanced Wideband Frequency Estimation via FFT: Leveraging Polynomial Interpolation and Array Indexing

Accurate frequency estimation in a wideband digital receiver using the FFT algorithm encounters challenges, such as spectral leakage resulting from the FFT’s assumption of signal periodicity. High-resolution FFTs pose computational demands, and estimating non-integer multiples of frequency resolution proves exceptionally challenging. This paper introduces two novel methods for enhanced frequency precision: polynomial interpolation and array indexing, comparing their results with super-resolution and scalloping loss. Simulation results demonstrate the effectiveness of the proposed methods in contemporary radar systems, with array indexing providing the best frequency estimation despite utilizing maximum hardware resources. The paper demonstrates a trade-off between accurate frequency estimation and hardware resources when comparing polynomial interpolation and array indexing.

An Accurate Numerical Solution for the Modified Equal Width Wave Equation Using the Fourier Pseudo-Spectral Method

In this study, the numerical solution for the Modified Equal Width Wave (MEW) equation is presented using Fourier spectral method that use to discretize the space variable and Leap-frog method scheme for time dependence. Test problems including the single soliton wave motion, interaction of two solitary waves and interaction of three solitary waves will use to validate the proposed method. The three invariants of the motion are evaluated to determine the conservation properties of the generated scheme. Finally, a Maxwellian initial condition pulse is then studied. The L2 and L∞ error norms are computed to study the accuracy and the simplicity of the presented method.

面向5G终端基带处理的高量化信噪比FFT加速器设计

针对第5代移动通信系统(5G)终端基带处理芯片的设计要求,本文提出一种基于新型块浮点(BFP)技术的快速傅里叶变换(FFT)加速器。为了降低FFT计算过程中的量化误差,本文实现了一种逐级迭代、动态调整共享指数的块浮点技术,并在此基础上,引入“银行家舍入规则”处理BFP尾数缩放过程中的舍入误差,进一步提高该加速器的整体精度。此外,为了实现5G基带连续FFT处理需求,本文还实现了一种无地址冲突的顺序访存机制。实验结果表明,该加速器从128点至4096点FFT处理的量化信噪比(SQNR)都超过75 dB,比未采用块浮点的方案高8~15 dB;与其他较优秀的设计相比,在高点数(2048点、4096点)上也有3 dB的优势。本文FFT加速器在TSMC 28 nm工艺库下综合显示,总面积为0.193 mm^(2),最高支持600 MHz时钟频率,计算4096点FFT平均功耗为16.3 mW。

大点数FFT的工程案例

快速傅里叶变换(FFT)是“数字信号处理”课程中的重要知识点,该算法工程应用非常广泛。但FFT算法的推导过程比较复杂,学生不太容易深刻领会并灵活运用。以某型多频连续波雷达的数据处理为例,介绍如何利用16K缓存的芯片来实现128K点的FFT运算,通过实际工程案例来加深学生对FFT算法的理解,提高学生解决工程问题的能力。

多路并行流水线型基2^(2)FFT算法实现

FFT算法作为OFDM系统的核心算子占用其系统处理的大多数时间,为提高OFDM系统数据传输速度,提出了一种改进的多路并行流水线型基2^(2)FFT实现架构。在实现过程中着重对旋转因子的存储进行片上缓存优化,减少了乘法运算次数从而减小整体运算复杂度;设计的数据整合模块用于控制时序,从而保证P路并行流水型架构正确实现,数据运算吞吐率成P倍提高。RTL仿真结果表明,与同类架构相比,提出的架构在硬件开销适中的同时使得性能分别提升了1.27%、2.04%、50.88%,并且具有FFT点数可扩展的特点,可满足随着通信标准的不断提高,FFT点数逐渐增大的实际应用需求。

一种高速2-D滑动FFT的设计实现

文章介绍了采用2-D快速傅里叶变换(fast Fourier transform,FFT)算法的滑动窗FFT的基本特性原理和硬件实现过程,完成了窗长256点、步长16点的2-D滑动窗FFT的专用集成电路(application specific integrated circuit,ASIC)设计。传统FFT算法受序列完整性的制约,时滞较大,无法满足某些高实时性信号分析领域的处理速度要求。该文采用滑动FFT算法,克服了传统FFT对序列完整性的依赖,设计的滑动FFT处理器使用2-D FFT压缩新序列计算时间,以基16蝶形运算器为核心,采用系数复用和高基Booth方法优化系数编码技术压缩乘法器的数量,减少电路面积。所设计的2-D滑动FFT完成单次滑动窗长的计算时间比传统算法节约了16.1%,变换结果与MATLAB的运算结果相比,信噪比(signal-to-noise ratio,SNR)大于130 dB。在TSMC 28 nm的工艺下,工作主频为600 MHz,面积为1980μm×2060μm。

基于STM32的辨音识别系统的设计与应用

声音识别技术能够用于多种环境参数检测,本文采用STM32的DSP技术,对全向拾音器采集到环境声音进行快速傅里叶变换(FFT),获取待测声音的主频率和次频率,通过液晶屏显示采集信号的强度和主要频率分量。该设备能够有效对环境声音的主要参赛进行检测,在噪声检测和一般设备运行故障检测具有较高的适用性。

无监督域适应迁移学习在旋转机械故障诊断中的应用

故障诊断在旋转机械领域具有重要的意义,而深度学习和迁移学习的发展为提高故障诊断的准确性和鲁棒性提供了新的途径。针对旋转机械故障诊断问题,提出了一种基于深度对抗神经网络(domain-adversarial neural network, DANN)和多核最大平均差异(multiple kernel maximum mean discrepancy, MK-MMD)的无监督域适应迁移学习方法。首先,收集了源工况和目标工况下的振动信号数据并通过快速傅里叶变换(fast Fourier transform, FFT)转化为频域信号。然后,构建了一个ResNeXt-50特征提取器,并使用DANN和MK-MMD方法进行特征映射和域适应,从而实现源工况到目标工况的迁移学习。试验结果表明,该方法能提高对故障特征的识别精度,且在不同工况下的迁移试验中具有更好的鲁棒性。

基于Nuttall自卷积窗的改进FFT谱分析方法

建立性能优良的窗函数是提高频谱分析准确度的关键。本文用Nuttall窗进行时域卷积运算构建Nuttall自卷积窗,具有旁瓣性能随卷积次数增加而迅速提升的优点;提出基于Nuttall自卷积窗的改进FFT谱分析方法,采用最小二乘法推导离散频谱插值多项式,建立谐波参数准确求解算法;通过仿真实验验证Nuttall自卷积窗及改进FFT谱分析方法的有效性和准确性。

基于FFT和神经网络的非整数次谐波检测方法

运用人工神经网络模型进行整数次谐波检测可达到较高的检测精度,但这种线性神经元模型不适合非整数次谐波的检测。为精确检测非整数次谐波, 文中提出了一种改进进的线性人工神经元模型,并将加汉宁窗的FFT 算法和改进的线性人工神经元模型结合起来,提出了一种用于非整数次谐波检测的新方法。该方法首先对采样信号用加汉宁窗的FFT 算法进行预处理,得到了谐波个数和精度不高的谐波次数;其次根据谐波个数设定神经元的个数,根据预处理后得到的谐波次数设定神经网络谐波次数迭代的初始值;最后对改进后的人工神经网络进行训练,便可实现非整数次谐波的精确检测。仿真实例表明,该方法能将频率相近的非整数次谐波分离,可有效地提高谐波参数的检测精度,为谐波治理提供良好的依据。

用于正弦波频率估计的修正I-Rife算法

对正弦波信号的频率估计是雷达领域常见的问题。当真实频率接近量化频点时,I-Rife算法的频移因子的计算会产生较大误差,为提高频率估计的精度,本文通过分析Rife及I-Rife算法的性能及误差产生的原因,利用频谱细化的方法,提出了一种修正I-Rife算法,即用峰值频点左右各0.5点处的频谱幅值来替代频谱峰值点的幅值和次大值频点处的幅值进行插值计算,对频率偏移值进行更为准确的估计,在计算量与I-Rife算法几乎相同的情况下,有效地提高了频率的估计精度。仿真结果表明,改进后的I-Rife算法整体性能优于I-Rife算法,且估计的均方根误差更接近于克拉美-罗下界。

凯塞窗插值FFT的电力谐波分析与应用

采用矩形窗、三角窗等基本窗函数和广义余弦窗函数对信号加权可减少非整数周期截断造成的频谱泄漏和栅栏效应的影响,但其效果受到窗函数固定旁瓣性能的制约。通过分析凯塞(Kaiser)窗函数的主瓣与旁瓣衰减可自由选择的特性,提出基于Kaiser窗插值快速傅里叶变换(fast Fourier transform,FFT)的电力谐波分析方法,建立奇次、偶次谐波求解的数学模型和实用的插值修正公式,推导信号基波与各次谐波频率、幅值、初相角的计算式。仿真和实测结果表明,Kaiser窗插值FFT方法设计实现灵活、抑制频谱泄漏效果好,据此研制的三相多功能谐波电能表的基波有功误差≤0.2%,基波无功误差≤1%,2～21次谐波分析满足GB/T14549—1993的A类谐波测量仪器要求。