Author
R. Shanmuga Sundaram
Other affiliations: Indian Institutes of Technology
Bio: R. Shanmuga Sundaram is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Fast Fourier transform & Discrete Hartley transform. The author has an hindex of 3, co-authored 6 publications receiving 17 citations. Previous affiliations of R. Shanmuga Sundaram include Indian Institutes of Technology.
Papers
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TL;DR: Boashash (1987) has proposed and showed that the evaluation of the analytic signal using the time-domain approach, and involving the Hilbert transformer, is the most efficient algorithm for real-time applications.
Abstract: The Wigner-Ville distribution (WVD) has been a powerful signal processing tool for time-frequency signal analysis. Consequently, many algorithms have been proposed in the literature for computing the WVD in real-time applications. However, Boashash (1987) has proposed and showed that the evaluation of the analytic signal using the time-domain approach, and involving the Hilbert transformer, is the most efficient algorithm for real-time applications. A fixed-point error analysis of this algorithm has been carried out. The theoretical noise-to-signal ratio (NSR) is derived and verified through simulation. The results indicate that for this algorithm, the NSR increases by 0.5 bit/stage, whereas for the other algorithms, it increases by 1 bit/stage.
6 citations
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01 Dec 1996
TL;DR: A new fast algorithm is proposed to compute pseudodiscrete Wigner-Ville distribution in real-time applications that uses the moving discrete Hartley transform to compute the Hilbert transform and implements the PDWVD in real domain.
Abstract: A new fast algorithm is proposed to compute pseudodiscrete Wigner-Ville distribution (PDWVD) in real-time applications. The proposed algorithm uses the moving discrete Hartley transform to compute the Hilbert transform and thereby implements the PDWVD in real domain. The computational complexity of the proposed algorithm is derived and compared with the existing algorithm to compute the PDWVD.
4 citations
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TL;DR: Efficient implementation of the FHT on different DSP processors is considered, instead of counting the required arithmetic operations, the necessary number of instruction cycles for an implementation of FHT is used as a measure.
3 citations
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01 Feb 1997TL;DR: The authors present a fast and numerically stable algorithm for computing the WVD and the computational complexity of the proposed algorithm is derived and compared with existing algorithms.
Abstract: The Wigner-Ville distribution (WVD) is a particularly useful technique for analysing nonstationary signals and has been studied extensively. An algorithm has been proposed for computing the WVD requiring only real operations, but involving division by sine and cosine factors. However, this causes numerical instabilities because of roundoff errors in finite length registers. The authors present a fast and numerically stable algorithm for computing the WVD. The computational complexity of the proposed algorithm is also derived and compared with existing algorithms.
2 citations
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TL;DR: A fixed-point error analysis of an efficient algorithm which uses discrete Hartley transform (DHT) to evaluate the WVD entirely in the real domain indicates that this algorithm has better noise properties when compared to the FFT-based algorithm, even though the F FT has better Noise properties than the FHT.
1 citations
Cited by
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28 Feb 2013
TL;DR: Introduction to Fourier Analysis Linear Time-Frequency Representations Quadratic Time- frequency Distributions Higher Order Time-f frequency Representations Analysis of Non-Stationary Noisy Signals Some Applications of Time- Frequency Analysis.
Abstract: The culmination of more than twenty years of research, this authoritative resource provides you with a practical understanding of time-frequency signal analysis. The book offers in-depth coverage of critical concepts and principles, along with discussions on key applications in a wide range of signal processing areas, from communications and optics, to radar and biomedicine. Supported with over 140 illustrations and more than 1,700 equations, this detailed reference explores the topics you need to understand for your work in the field, such as Fourier analysis, linear time frequency representations, quadratic time-frequency distributions, higher order time-frequency representations, and analysis of non-stationary noisy signals. This unique book also serves as an excellent text for courses in this area, featuring numerous examples and problems at the end of each chapter.
187 citations
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TL;DR: A systematic method for developing a binary version of a given transform by using the Walsh-Hadamard transform (WHT) is proposed and it is shown that the resulting BDCT corresponds to the well-known sequency-ordered WHT, whereas the BDHT can be considered as a new Hartley-ordering WHT.
Abstract: In this paper, a systematic method for developing a binary version of a given transform by using the Walsh-Hadamard transform (WHT) is proposed. The resulting transform approximates the underlying transform very well, while maintaining all the advantages and properties of WHT. The method is successfully applied for developing a binary discrete cosine transform (BDCT) and a binary discrete Hartley transform (BDHT). It is shown that the resulting BDCT corresponds to the well-known sequency-ordered WHT, whereas the BDHT can be considered as a new Hartley-ordered WHT. Specifically, the properties of the proposed Hartley-ordering are discussed and a shift-copy scheme is proposed for a simple and direct generation of the Hartley-ordering functions. For software and hardware implementation purposes, a unified structure for the computation of the WHT, BDCT, and BDHT is proposed by establishing an elegant relationship between the three transform matrices. In addition, a spiral-ordering is proposed to graphically obtain the BDHT from the BDCT and vice versa. The application of these binary transforms in image compression, encryption and spectral analysis clearly shows the ability of the BDCT (BDHT) in approximating the DCT (DHT) very well.
83 citations
01 Jan 2014
TL;DR: In this paper, the authors present a comprehensive overview of time-frequency signal analysis, including Fourier analysis, linear time frequency representations, quadratic timefrequency distributions, higher order timefrequency representations, and analysis of nonstationary noisy signals.
Abstract: The culmination of more than twenty years of research, this authoritative resource provides a practical understanding of time-frequency signal analysis. The book offers in-depth coverage of critical concepts and principles, along with discussions on key applications that are of great interest to engineers and researchers involved in a wide range of signal processing work, from communications and optics...to radar and biomedicine. Supported with over 140 illustrations and more than 1,700 equations, this detailed reference explores the topics professionals need to understand, such as Fourier analysis, linear time frequency representations, quadratic time-frequency distributions, higher order time-frequency representations, and analysis of non-stationary noisy signals. This unique book also serves as an excellent text for courses in this area, featuring numerous examples and problems at the end of each chapter. It is suitable for electrical engineers and researchers whose work involves signal processing and radar signal processing, as well as graduate students in related courses.
74 citations
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TL;DR: The WVD-based measure is shown to be correlated with subjective human evaluation, which is the premise towards an image quality assessor developed on this principle.
Abstract: This paper demonstrates the usefulness of spatial/spatial-frequency representations in image quality assessment by introducing a new image dissimilarity measure based on 2D Wigner-Ville distribution (WVD). The properties of 2D WVD are shortly reviewed, and the important issue of choosing the analytic image is emphasized. The WVD-based measure is shown to be correlated with subjective human evaluation, which is the premise towards an image quality assessor developed on this principle.
33 citations