二维滑动矩形窗傅氏变换的快速递推算法

该文利用相邻滑动窗数据之间的关系以及傅氏变换的平移性质,提出一种二维滑动矩形窗傅氏变换的快速递推算法。文中分析了该快速递推算法的复杂度和传统直接计算法的复杂度,证明了新的快速递推法可以大大降低计算复杂性,尤其是在图像尺寸和窗口尺寸较大的场合中。该算法可以改善滑窗傅氏变换或Gabor变换的计算效率。     

离散傅里叶变换的频谱分析方法的研究

频谱分析方式有着多样性的特征,就现阶段来看,测频方式是多种多样的,有cross算法、DFT算法、prony算法、最小二乘法、卡尔曼滤波算法等等,但是这些算法都存在各种各样的不足,其中,DFT算法的应用范围是最为广泛的,在高次谐波以及非整次谐波含量较少的情况下,该种算法的精度是十分理想的,该种算法应用了循环与递归算法,计算速度快,抗干扰性强,能够消除整次谐波对分析过程的不良影响。使用加窗法与滤波法也能够避免出现插值方向错误的问题,本文主要分析基于离散傅里叶变换的频谱分析新方法。     

关于滑动DFT算法中的频谱泄漏问题的探讨

针对滑动DFT算法中的频谱泄漏效应的处理问题,提出用频域加窗的办法,避免了时域加窗中窗与输入信号的N次相乘,破坏滑动DFT实时计算的简捷性、可靠性,保证了滑动DFT算法的实现与优化。在硬件实现上,用3个结构简单的谐振器,将其谐振频率分别调到3个相邻的DFT频率单元,即可实现此处理过程。     

用于成像跟踪的估值算法

TSVIP模型是一种用于成像跟踪的图像演变模型。本文提出了对该模型的递推算法及硬件方案,并对原模型作了推广。进而针对图像阻塞问题,提出了将递推算法与卡尔曼滤波方法相结合的综合算法。理论分析与模拟实验的结果证实了上述设想是可行的。     

滑动DFT算法在功率谱估计中的应用

基于滑动DFT算法推导出一种改进的周期图功率谱估计方法,并在软件系统界面中应用。根据传统的功率谱估计方法和滑动DFT算法推导出改进的功率谱估计算法,通过滑动D丌算法计算出DFY值,计算DFT时通过加窗减少了频谱泄漏．然后通过周期图法计算出最终的功率谱值,在Matlab中绘制出功率谱进行验证,用C＋＋语言对该算法进行实现...     

加窗离散傅里叶变换性能分析和比对

离散傅里叶变换（DFT）是数字信号处理的常用方法,但通过加窗对信号进行时域截短会使频谱分析出现误差。不同窗函数对信号频谱产生的影响不同,对5种常用窗函数的特性进行了比较和适用性分析,通过仿真实验证明了针对不同信号特点和处理要求,应选择合适的窗函数,以减小频谱泄漏和栅栏效应对信号分析的影响。     

用于高动态GPS抗干扰的微分约束递推算法

针对GPS接收机的抗干扰问题,以自适应阵列天线为研究对象,提出了一种高动态GPS接收机的自适应抗干扰递推算法。算法是基于功率倒置方法,并在干扰方向加微分约束,经推导得出一种微分递推算法。仿真结果表明,相比一般的导航抗干扰算法,此算法不仅可在干扰方向上加宽零陷宽度,且由于采用递推,其收敛速度有显著提高     

AR谱估计的一种自适应算法

本文给出Householder变换的一种实时递推算法及其收敛性证明,并用此算法进行AR自适应谱估计。仿真计算表明,此算法具有计算结果准确、可以实时判阶和快速跟踪性好等特点。     

前向神经网络中的递推学习算法

针对前向神经网络这一广泛应用的信息处理方法,分析了其模型、工作原理及作用,研究了几种递推学习算法,包括严格递推算法、随机逼近算法以及基于统计的算法,给出了几种算法的原理及权值调整方法,通过仿真比较了几种算法的性能,分析了步幅系数对收敛性的影响。     

灰度图像的二维Otsu曲线阈值分割法

Otsu法是一个常用的阈值分割方法.为了利用图像的区域信息,本文在二维Otsu法的基础上提出了曲线阈值型Otsu法,传统的二维Otsu法可以看成是该方法的一个特例.实验结果表明,对于含噪图像,它能够获得优于传统二维Otsu法的分割效果.为了减少计算量,提高分割速度,给出了一种递归算法和一种小波变换与递归算法相结合的快速算法.该递推算法只需遍历二维直方图的主对角线和一条次主对角线,与传统Otsu法的递推算法相比,搜索空间由L×L个点减少到2L-1个点.     

Power converter line synchronization using a discrete Fourier transform (DFT) based on a variable sample rate

Line synchronization of grid connected power converters is a well recognized problem when the grid is weak, or derives from a remote area power supply with poor frequency regulation. Such systems can suffer significant line voltage distortion due to notches caused by power device switching and/or low frequency harmonic content, which can easily corrupt the output of a conventional zero crossing detector. This paper presents a method of filtering the incoming grid voltage using a recursive discrete Fourier transform (DFT). The filter provides a high degree of noise immunity but does produce a phase shift between the incoming grid voltage and the filtered output voltage when the DFT time window does not match the grid period. Two methods of compensating this phase shift are presented, based on tracking the drift in the phase predicted by the recursive DFT. The first method makes a deadbeat adjustment to the time window (thereby changing the sampling rate) while the second approach calculates the phase error based on the linear phase response of the DFT. These compensation algorithms can correct for discrepancies of at least 25% between the DFT time window and the system period, and can track grid frequencies with slew rates as high as 40 Hz/s with negligible phase shift (<2/spl deg/) between the grid voltage input and the filtered output waveforms.     

一种准周期信号频率的精确测量算法

分析比较了现有的一些基于ＤＦＴ类谐波分析及频率测量算法,给出一类准周期信号的时域模型,提出一种基于窗口ＤＦＴ的准周期信号频率精确算法,并对算法进行仿真。     

感知音频编码中预回声的产生机理与抑制方法

阐述了预回声的概念和产生机理,对几种抑制预回声方法的基本思想和实现手段进行了讨论,并简要介绍了它们在ＰＡＣ中的应用。     

Efficient Recursive IDFT Scheme for Complex-valued Signals in Tap-selective Maximum-likelihood Channel Estimation

This paper presents several efficient, recursive inverse discrete Fourier transform (IDFT) schemes for complex-valued input data in tap-selective maximum-likelihood channel estimation; the results of their implementation are also presented. The proposed schemes employ only real-valued arithmetic, which reduces the number of required real multiplication operations in comparison with conventional IDFT approaches; however, the number of real additions increases significantly due to the sliding window scheme. The results show that the schemes can reduce the computational complexity and enhance flexibility when only several subsets of the IDFT output bins are required.     

滑动离散傅里叶算法输出稳定性研究

受数字系统有限字长的影响,滑动离散傅里叶变换(滑动DFT)算法的频率单元存在输出不稳定的缺点。利用改进Goertzel算法的递归单元对滑动DFT算法的频率单元改造后,不仅可以直接计算起始频谱值,而且滑动DFT算法可以每隔N个输出值就对频率单元清零,并能提供准确的新谱值,保证了滑动DFT算法的频率单元可以长时间连续不断的处理输入数据,而不会出现输出不稳定现象。这种方法在连续地、实时地进行时频谱分析中具有重要的意义。     

A Modified Split-Radix FFT With Fewer Arithmetic Operations

Recent results by Van Buskirk have broken the record set by Yavne in 1968 for the lowest exact count of real additions and multiplications to compute a power-of-two discrete Fourier transform (DFT). Here, we present a simple recursive modification of the split-radix algorithm that computes the DFT with asymptotically about 6% fewer operations than Yavne, matching the count achieved by Van Buskirk's program-generation framework. We also discuss the application of our algorithm to real-data and real-symmetric (discrete cosine) transforms, where we are again able to achieve lower arithmetic counts than previously published algorithms     

Recursion in short-time signal analysis

The problem of finding a recursive structure for the evaluation of features through a ‘running’ window is investigated. A general closed form expression is found for features satisfying a direct or indirect recursion condition. It is shown that most of the commonly used features (mean value, energy, autocorrelation function, DFT, Z-transform, entropy, etc.) satisfy these analytic expressions. The recursive, step by step, feature evaluation method is compared with the conventional method where features are evaluated for positions of the observation window with a 50% overlap. These two methods are equivalent in computation time for features satisfying the direct recursion condition. However, there might be some loss of information when using the last approach. The use of indirect recursion is advantageous for small window sizes. The results are then generalised to bidimensional signal processing.     

基于小波神经网络非线性预测方法的研究

针对非线性预测问题,提出了小波神经网络算法．该算法采用权重贡献率分析法和关键神经节点法分析权重,精进模型,利用具有优良渐进性的递推预报误差法训练小波的尺度因子和平移因子,并提出了一种网络的改进算法．通过对导航设备的仿真预测,该算法优于同等规模的BP神经网络,其收敛速度快,预测精度高．     

An introduction to FFT and time domain windows

This paper includes a brief tutorial on digital spectrum analysis and FFT-related issues to form spectral estimates on digitized signals. Some review of the DFT has been presented, and some discussion on the computational advantages of the FFT calculation has also been presented. Finally, the main considerations on windowing and window characteristics have been briefly discussed.