Programs and Papers on Fractional Discrete Fourier Transform
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This article provides both program implementations and detailed explanations of fractional discrete Fourier transform (FrDFT). The discrete Fourier transform (DFT) serves as a fundamental signal processing tool for analyzing and manipulating signals, with widespread applications across communication systems, image processing, and audio signal processing domains. Through studying DFT principles, readers can gain deep insights into its underlying mathematics and practical implementations, enabling flexible application to real-world problems. The article includes code demonstrations illustrating key algorithmic components such as twiddle factor computation and fractional power adjustments in FrDFT implementations. Our objective is to help readers thoroughly understand fractional DFT concepts while providing guidance for both learning and practical implementation through executable code examples and mathematical derivations.
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