ASIC Design of Floating-Point FFT Processor

An application specific integrated circuit (ASIC) design of a 1024 points floating-point fast Fourier transform(FFT) processor is presented. It can satisfy the requirement of high accuracy FFT result in related fields. Several novel design techniques for floating-point adder and multiplier are introduced in detail to enhance the speed of the system. At the same time, the power consumption is decreased. The hardware area is effectively reduced as an improved butterfly processor is developed. There is a substantial increase in the performance of the design since a pipelined architecture is adopted, and very large scale integrated (VLSI) is easy to realize due to the regularity. A result of validation using field programmable gate array (FPGA) is shown at the end. When the system clock is set to 50 MHz, 204.8 μs is needed to complete the operation of FFT computation.

NOVEL HIGH-SPEED FPGA-BASED FFT PROCESSOR

A novel architecture for computing the fast Fourier transform ( FFT ) on programmable devices is presented.To improve the system operation speed , a hybrid parallel FFT algorithm is used.Results indicate that the use of an 8×8parallel structure for realizing the 64-point FFT leads to a 8times higher processing speed compared with its counterparts employing other series of techniques.

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。

一种基于三谱线插值FFT的杂波抑制方法

不同于传统的MTI/MTD算法,提出了一种基于三谱线插值FFT的杂波抑制方法。该方法先对回波信号进行时域加窗处理,抑制非同步采样和周期截断带来的频谱泄漏和栅栏效应,再进行傅里叶变换,采用三谱线插值估算每个距离单元上多个频率和幅度分量,并将估算结果与杂波速度阈值进行比较。若高于阈值,即判定当前频率分量对应的幅度值为目标幅度值,并输出多普勒速度信息;否则判定未检测到目标。通过仿真及试验验证了该方法的可行性和有效性。

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.

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.

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。

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.

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。

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.

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.

A novel 3780-point FFT processor scheme for the time domain synchronous OFDM system

The 3780-point FFT is a main component of the time domain synchronous OFDM （TDS-OFDM） system and the key technology in the Chinese Digital Multimedia/TV Broadcasting-Terrestrial （DMB-T） national standard. Sinc, e 3780 is not a power of 2, the classical radix-2 or radix-4 FFT algorithm cannot be applied directly. Hence, the Winograd Fourier transform algorithm （WFTA） and the Good-Thomas prime factor algorithm （PFA） are used to implement the 3780-point FFT processor. However, the structure based on WFTA and PFA has a large computational complexity and requires many DSPs in hardware implementation. In this paper, a novel 3780-point FFT processor scheme is proposed, in which a 60x63 iterative WFTA architecture with different mapping methods is imported to replace the PFA architecture, and an optimized CoOrdinate Rotation Digital Computer （CORDIC） module is used for the twiddle factor multiplications. Compared to the traditional scheme, our proposed 3780-point FFT processor scheme reduces the number of multiplications by 45% at the cost of 1% increase in the number of additions. All DSPs are replaced by the optimized CORDIC module and ROM. Simulation results show that the proposed 3780-point FFT processing scheme satisfies the requirement of the DMB-T standard, and is an efficient architecture for the TDS-OFDM system.

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.

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。

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。

基2×2FFT的地址映射算法

FFT处理器是根据 FFT运算特点来进行设计的 ,可以充分提高处理效率 ,达到平均每周期完成一个蝶式运算的处理能力 .在这类芯片中 ,需要并行无冲突的数据访问部件来提供蝶式运算所需的多个操作数 .文中对已有的一些算法进行了比较 ,并提出基 2× 2 FFT的并行数据访问算法 ,通过使用 4个存储体 ,它可以同时完成所需的 4个数据的读取或写入操作 .该算法易于用硬件实现 ,其操作数访问地址的产生速度快于已有的算法 .

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。

考虑测量带宽影响的电磁干扰频谱FFT计算

基于快速傅里叶变换(fast Fourier transform,FFT)计算电磁干扰(electromagnetic interference,EMI)频谱时,为了得到和EMI接收机测试一致的频谱结果,必须考虑测量带宽的影响,即必须将EMI接收机测量带宽内的FFT频率分量在分析频率上进行叠加。提出了考虑测量带宽影响的EMI频谱计算方法,首先对时域信号进行FFT,然后将FFT结果加窗滤波并进行快速傅里叶反变换(inverse fast Fourier transform,IFFT),取IFFT所得波形包络线的最大值作为频谱分析结果。为了提高计算速度,给出了改进的IFFT方法。实验结果表明,所提方法准确有效、计算迅速。

基于双窗全相位FFT双谱线校正的电力谐波分析

基于快速傅里叶变换的电力谐波分析在非同步采样情况下存在频谱泄露,影响测量精度。为抑制频谱泄露对谐波分析的影响,分析对比了双窗全相位FFT与传统加窗FFT在抑制频谱泄露方面的特点,并通过计算证明了双窗全相位FFT在电力谐波分析中的独特优势。针对全相位频谱分析通常采用的时移相位差法存在计算量大、实时性差及存在相位模糊现象等不足,提出了一种基于双窗全相位FFT双谱线校正的谐波分析算法,利用基波频点附近的两条谱线幅值计算基波频率,进而推导了简洁实用的谐波幅值校正公式。该算法实现方便,且实时性优于相位差法。通过与传统加Hanning窗、Nuttall窗插值FFT的仿真对比验证了新算法具有更高精度,基于该算法的实验结果也验证了算法的有效性。

基于FFT的高精度谐波检测算法

大量非线性元件的应用给电力系统带来了大量的整数和非整数次谐波,传统的谐波检测方法快速傅立叶变换(FFT)由于存在栅栏和频谱泄漏现象,只适用于整数次谐波的分析,而不适用于非整数次谐波的检测,因此不能够实现精确的谐波分析。非整数次谐波频谱泄漏现象是因为有限长信号的傅立叶变换与理论傅立叶变换的不同而产生的。为消除频谱泄漏误差,提高检测精度,文中详细分析了FFT算法的频谱泄漏现象,在此基础上提出了改进算法。该算法通过对FFT算法做简单变换,减小了频谱泄漏误差,降低了谐波之间的相互干扰。仿真验证了该算法的高精度检测特性。该文提出的算法具有实现简单,精度高的特点,从而为电力系统中的谐波检测和分析提供了一种有效的算法。