丈中利用双梯度算法对自然图像的基向量进行迭代学习。
The basis vectors of the natural images were obtained by using fast conjugate gradient algorithm.
计算量比较结果显示，频域抽取多维向量基FFT算法比多维分离式FFT算法计算量低。
The comparison results show that, compared with multi-dimensional separable FFT, the DIF multi-dimensional vector radix FFT algorithm has lower calculation load.
该FFT算法适合于维数为任意整数的情况，当维数为1时，算法退化为著名的频域抽取向量基2 FFT算法。
This FFT algorithm can be used with arbitrary integer dimensions. For 1-dimension, the algorithm will be simplified as the well-known DIF vector radix 2 FFT.
给出了频域抽取二维向量基快速傅里叶变换算法，针对二维频域信号采用频域抽取方法，导出了该快速算法蝶形运算的一般形式并给出了算法实现流程图。
In accordance with the requirements of high speed digital signal processing, the algorithm of radix-4 implemented with FPGA and the integrated architecture and butterfly unit are analyzed.
给出了频域抽取二维向量基快速傅里叶变换算法，针对二维频域信号采用频域抽取方法，导出了该快速算法蝶形运算的一般形式并给出了算法实现流程图。
In accordance with the requirements of high speed digital signal processing, the algorithm of radix-4 implemented with FPGA and the integrated architecture and butterfly unit are analyzed.
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