...
首页> 外文期刊>IEE proceedings, Part K. Vision, image and signal processing >Fractional Fourier transform of the Gaussian and fractional domain signal support
【24h】

Fractional Fourier transform of the Gaussian and fractional domain signal support

机译:高斯和分数域信号支持的分数阶傅里叶变换

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

The fractional Fourier transform (FrFT) provides an important extension to conventional Fourier theory for the analysis and synthesis of linear chirp signals. It is a parameterised transform which can be used to provide extremely compact representations. The representation is maximally compressed when the transform parameter, α, is matched to the chirp rate of the input signal. Existing proofs are extended to demonstrate that the fractional Fourier transform of the Gaussian function also has Gaussian support. Furthermore, expressions are developed which allow calculation of the spread of the signal representation for a Gaussian windowed linear chirp signal in any fractional domain. Both continuous and discrete cases are considered. The fractional domains exhibiting minimum and maximum support for a given signal define the limit on joint time-frequency resolution available under the FrFT. This is equated with a restatement of the uncertainty principle for linear chirp signals and the fractional Fourier domains. The calculated values for the fractional domain support are tested empirically through comparison with the discrete transform output for a synthetic signal with known parameters. It is shown that the same expressions are appropriate for predicting the support of the ordinary Fourier transform of a Gaussian windowed linear chirp signal.
机译:分数阶傅立叶变换(FrFT)为线性线性调频信号的分析和合成提供了对传统傅立叶理论的重要扩展。它是一个参数化的转换,可用于提供非常紧凑的表示形式。当变换参数α与输入信号的线性调频率匹配时,表示将得到最大压缩。扩展了现有的证明,以证明高斯函数的分数阶傅里叶变换也具有高斯支持。此外,开发了允许在任何分数域中计算高斯加窗线性线性调频信号的信号表示的扩展的表达式。连续和离散情况都被考虑。对给定信号表现出最小和最大支持的分数域定义了在FrFT下可用的联合时频分辨率的极限。这等同于线性线性调频信号和分数阶傅里叶域的不确定性原理的重述。通过与具有已知参数的合成信号的离散变换输出进行比较,以经验方式测试分数域支持的计算值。结果表明,相同的表达式适用于预测高斯窗口线性linear信号的普通傅里叶变换的支持。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号