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OpenAlex konusu

Mathematical Analysis and Transform Methods

Bu sayfa OpenAlex konu etiketine göre çalışmaları ve o konuda görünen akademisyenleri listeler. YÖKSİS temel alan / yan dal değildir.

OpenAlex 963 eser 44 yazar konusu

Çalışmalar

963 eser

  1. OpenAlex üst %1 OpenAlex 100.0%

    Preface. Acknowledgments. Introduction. Signals, Systems, and Transformations. Wigner Distributions and Linear Canonical Transforms. The Fractional Fourier Transform. Time-Order and Space-Order Representations. The Discrete Fractional Fourier Transform. Optical Signals and Systems. Phase-Space Optics. The Fractional F…

  2. OpenAlex üst %1 OpenAlex 99.9%

    An algorithm for efficient and accurate computation of the fractional Fourier transform is given. For signals with time-bandwidth product N, the presented algorithm computes the fractional transform in O(NlogN) time. A definition for the discrete fractional Fourier transform that emerges from our analysis is also disc…

  3. OpenAlex üst %1 OpenAlex 99.9%

    We propose and consolidate a definition of the discrete fractional Fourier transform that generalizes the discrete Fourier transform (DFT) in the same sense that the continuous fractional Fourier transform generalizes the continuous ordinary Fourier transform. This definition is based on a particular set of eigenvecto…

  4. OpenAlex üst %1 OpenAlex 100.0%

    A brief introduction to the fractional Fourier transform and its properties is given. Its relation to phase-space representations (time- or space-frequency representations) and the concept of fractional Fourier domains are discussed. An overview of applications which have so far received interest are given and some po…

  5. YÖKSİS SJR Q1 JCR Q1 OpenAlex üst %1 OpenAlex 100.0%

    A concise introduction to the concept of fractional Fourier transforms is followed by a discussion of their relation to chirp and wavelet transforms. The notion of fractional Fourier domains is developed in conjunction with the Wigner distribution of a signal. Convolution, filtering, and multiplexing of signals in fra…

  6. OpenAlex üst %10 OpenAlex 97.4%

    Shift and rotation invariance properties of linear time-frequency representations are investigated. It is shown that among all linear time-frequency representations, only the short-time Fourier transform (STFT) family with the Hermite-Gaussian kernels satisfies both the shift invariance and rotation invariance propert…

  7. YÖKSİS SJR Q1 JCR Q1 OpenAlex üst %10 OpenAlex 97.4%

    Shift and rotation invariance properties of linear time-frequency representations are investigated. It is shown that among all linear time-frequency representations, only the short-time Fourier transform (STFT) family with the Hermite-Gaussian kernels satisfies both the shift invariance and rotation invariance propert…

  8. SJR Q1 JCR Q1 OpenAlex üst %1 OpenAlex 99.7%

    For time-invariant degradation models and stationary signals and noise, the classical Fourier domain Wiener filter, which can be implemented in O(N log N) time, gives the minimum mean-square-error estimate of the original undistorted signal. For time-varying degradations and nonstationary processes, however, the optim…

  9. YÖKSİS SJR Q1 JCR Q2 OpenAlex üst %10 OpenAlex 97.6%

    Özet henüz yok.

  10. YÖKSİS SJR Q1 JCR Q1 OpenAlex üst %10 OpenAlex 97.3%

    Using operator theory methods together with our previously introduced unitary fractional operator, we derive explicit definitions of fractional convolution and correlation operations in a systematic and comprehensive manner. Via operator manipulations, we also provide alternative formulations of those fractional opera…

  11. YÖKSİS SJR Q1 JCR Q1 OpenAlex üst %1 OpenAlex 99.5%

    We deal with the problem of efficient and accurate digital computation of the samples of the linear canonical transform (LCT) of a function, from the samples of the original function. Two approaches are presented and compared. The first is based on decomposition of the LCT into chirp multiplication, Fourier transforma…

  12. SJR Q2 JCR Q2 OpenAlex üst %1 OpenAlex 100.0%

    Özet henüz yok.

Akademisyenler

44 akademisyen