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A Convolution Theorem for the Two Dimensional Fractional Fourier Transform in Generalized Sense

机译:广义意义上的二维分数傅里叶变换的卷积定理

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The two dimensional fractional Fourier transform (FrFT), which is a generalization of the Fourier transform, has many applications in several areas including signal processing and optics. Signal processing and pattern recognition algorithms make extensive use of convolution. In pattern recognition, convolution is an important tool because of its translation invariance properties. Also convolution is a powerful way of characterizing the input-output relationship of time invariant linear system. In this paper the convolution theorem for two dimensional fractional Fourier transform in the generalized sense is proved.
机译:这两维分数傅里叶变换(FRFT)是傅里叶变换的概括,在包括信号处理和光学的几个区域中具有许多应用。信号处理和模式识别算法大量使用卷积。在模式识别中,由于其转换不变性属性,卷积是一个重要的工具。卷积也是表征时间不变线性系统的输入输出关系的强大方法。在本文中,证明了在广义意义上的二维分数傅里叶变换的卷积定理。

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