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Bilinear time–frequency distributions, or quadratic time–frequency distributions, arise in a sub-field of signal analysis and signal processing called time–frequency signal processing, and, in the statistical analysis of time series data. Such methods are used where one needs to deal with a situation where the frequency composition of a signal may be changing over time; this sub-field used to be called time–frequency signal analysis, and is now more often called time–frequency signal processing due to the progress in using these methods to a wide range of signal-processing problems.

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  • Bilinear time–frequency distributions, or quadratic time–frequency distributions, arise in a sub-field of signal analysis and signal processing called time–frequency signal processing, and, in the statistical analysis of time series data. Such methods are used where one needs to deal with a situation where the frequency composition of a signal may be changing over time; this sub-field used to be called time–frequency signal analysis, and is now more often called time–frequency signal processing due to the progress in using these methods to a wide range of signal-processing problems. (en)
  • 科恩系列分佈(Cohen's class distribution)於1966年由L. Cohen首次提出,且其使用雙線性轉換亦是此種轉換形式中最通用的一種。在幾種常見的中,Cohen's class分佈是最強大的轉換之一。隨著近幾年來時頻分析發展,應用也越來越多元。Cohen's class分佈和短時距傅立葉變換比較起來有較高的清晰度,但也相對的有交叉項(cross-term)的問題,不過可選擇適當的遮罩函數(mask function)來將交叉項的問題降到最低。 (zh)
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  • Bilinear time–frequency distributions, or quadratic time–frequency distributions, arise in a sub-field of signal analysis and signal processing called time–frequency signal processing, and, in the statistical analysis of time series data. Such methods are used where one needs to deal with a situation where the frequency composition of a signal may be changing over time; this sub-field used to be called time–frequency signal analysis, and is now more often called time–frequency signal processing due to the progress in using these methods to a wide range of signal-processing problems. (en)
  • 科恩系列分佈(Cohen's class distribution)於1966年由L. Cohen首次提出,且其使用雙線性轉換亦是此種轉換形式中最通用的一種。在幾種常見的中,Cohen's class分佈是最強大的轉換之一。隨著近幾年來時頻分析發展,應用也越來越多元。Cohen's class分佈和短時距傅立葉變換比較起來有較高的清晰度,但也相對的有交叉項(cross-term)的問題,不過可選擇適當的遮罩函數(mask function)來將交叉項的問題降到最低。 (zh)
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  • Bilinear time–frequency distribution (en)
  • 科恩系列分佈 (zh)
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