摘要 快速傅里叶变换(FFT)是目前谐波分析中常用的分析算法,加窗插值FFT算法能够改善频谱泄漏和栅栏效应,但是FFT对采样数据序列有一定的长度要求。以基2为例,针对非2整数次幂数据序列无法采用快速傅里叶变换的问题,在分析研究常规混合基FFT算法频谱分布的基础上,提出一种适用于非整数次幂的高精度混合基FFT谐波测量算法...
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Also, by using the Power scaling function, the Peak-to-Average Power Ratio (PAPR) can be determined. It is defined by the power ratio between the peak and RMS amplitude, and it indicates the power of peak components in signals compared to the mean square amplitude. PAPR=C2=|peak|2rms2...
对于矩形窗来说CG=NG=1。常用窗函数的CG,NG和栅栏损失(scallop loss)如下表所示: 一般来说根据使用目的,有三种来对可以是得到的频谱正常化:第一种, 直接从谱中读取信号值;第二种,直接在图中读取噪声功率谱;还有第三种,通过将谱线上的数值相加,定量的确定任意频率带上的功率。 一般来说第三种方法最为准确。
理论上,所有的波形数据,都可以通过不同频率和相位的正弦波或者余弦波叠加而成。所以,可以对时效数据进行FFT,找出其周期特点。 参考:https://www.kaggle.com/muonneutrino/wikipedia-traffic-data-exploration 如图所示,为各个不同语音国家访问给定的wiki页面的平均流量,可以看出,欧美国家访问量较多,且呈现出一定的周期规...
'非相干积累')gridxlabel('积累的脉冲数');ylabel('SNR - dB');function[snrout]=pulse_...
This section delineates the computational framework of FFTFormer, encompassing the comprehensive network topology of FFTFormer, the architecture of the CA_Swin module and the integration mechanism within the FFTF module, along with the formulation of the loss function. Experiments This section describes...
At this span and below, it is possible to compute the spectra for every time record with no loss of data. The spectra are computed in "real time". At larger spans, some data samples will be lost while the FFT computations are in progress. For all frequency spans, the SR770 can ...
It's like running a smoothing function over the 'real' FFT (which doesn't exist, by the way). The total energy included in all of the buckets should be the same for all windowing functions (except for the loss caused by the actual window itself). It appears to me that the B-H ...
For 8b linear output, this can be done with no loss of precision with either 3 or 4 linear sections. This means that the input value can be evaluated for which section it lies in, and then the square root fetched, in around 12 clock cycles. This is much less than the usual 150 ...