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Author

K.M.M. Prabhu

Other affiliations: Indian Institutes of Technology
Bio: K.M.M. Prabhu is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topic(s): Fast Fourier transform & Discrete Hartley transform. The author has an hindex of 15, co-authored 96 publication(s) receiving 925 citation(s). Previous affiliations of K.M.M. Prabhu include Indian Institutes of Technology.
Papers
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Journal ArticleDOI
Abstract: One of the major challenges of on-site partial discharge (PD) measurements is the recovery of PD signals from a noisy environment. The different sources of noise include thermal or resistor noise added by the measuring circuit, and high-frequency sinusoidal signals that electromagnetically couple from radio broadcasts and/or carrier wave communications. Sophisticated methods are required to detect PD signals correctly. Fortunately, advances in analog-to-digital conversion (ADC) technology, and recent developments in digital signal processing (DSP) enable easy extraction of PD signals. This paper deals with the denoising of PD signals caused by corona discharges. Several techniques are investigated and employed on simulated as well as real PD data.

134 citations


Journal ArticleDOI
V. Ashok Narayanan1, K.M.M. Prabhu2Institutions (2)
TL;DR: It is hoped that this implementation and fixed-point error analysis will lead to a better understanding of the issues involved in finite register length implementation of the discrete fractional Fourier transform and will help the signal processing community make better use of the transform.
Abstract: The fractional Fourier transform is a time–frequency distribution and an extension of the classical Fourier transform. There are several known applications of the fractional Fourier transform in the areas of signal processing, especially in signal restoration and noise removal. This paper provides an introduction to the fractional Fourier transform and its applications. These applications demand the implementation of the discrete fractional Fourier transform on a digital signal processor (DSP). The details of the implementation of the discrete fractional Fourier transform on ADSP-2192 are provided. The effect of finite register length on implementation of discrete fractional Fourier transform matrix is discussed in some detail. This is followed by the details of the implementation and a theoretical model for the fixed-point errors involved in the implementation of this algorithm. It is hoped that this implementation and fixed-point error analysis will lead to a better understanding of the issues involved in finite register length implementation of the discrete fractional Fourier transform and will help the signal processing community make better use of the transform.

120 citations


Book
21 Oct 2013
Abstract: 1. Fourier analysis techniques for signal processing -- 2. Pitfalls in the computation of DFT -- 3. Review of window functions -- 4. Performance comparison of data windows -- 5. Discrete-time windows and their figures of merit -- 6. Time-domain and frequency-domain implementations of windows -- 7. FIR filter design using windows -- 8. Application of windows in spectral analysis -- 9. Applications of windows.

101 citations


Journal ArticleDOI
E.P. Reddy1, Debi Prasad Das2, K.M.M. Prabhu1Institutions (2)
TL;DR: The concept of reutilizing a part of the computations performed for the first sample while computing the next sample, for a block length of two samples, is exploited here to implement the fast and exact versions of the FSLMS and VFXLMS algorithms which are computationally efficient.
Abstract: This correspondence attempts to derive the exact implementation of two nonlinear active noise control (ANC) algorithms, viz. FSLMS and VFXLMS. The concept of reutilizing a part of the computations performed for the first sample while computing the next sample, for a block length of two samples, is exploited here to implement the fast and exact versions of the FSLMS and VFXLMS algorithms which are computationally efficient. Detailed computational complexity analysis for both addition and multiplication requirements is presented to show the advantage of the proposed algorithms. Appropriate simulation experiments are carried out to compare the performance equivalence of the proposed fast algorithms with their original versions.

46 citations


Journal ArticleDOI
TL;DR: A threshold-based procedure to estimate sparse channels in an orthogonal frequency division multiplexing (OFDM) system is proposed, derived by maximising the probability of correct detection between significant and zero-valued taps estimated by the least squares estimator.
Abstract: A threshold-based procedure to estimate sparse channels in an orthogonal frequency division multiplexing (OFDM) system is proposed. An optimal threshold is derived by maximising the probability of correct detection between significant and zero-valued taps estimated by the least squares (LS) estimator. Improved LS estimates are obtained by pruning the LS estimates with the statistically derived threshold.

37 citations


Cited by
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Journal ArticleDOI
S. Biyiksiz1Institutions (1)
01 Mar 1985
TL;DR: This book by Elliott and Rao is a valuable contribution to the general areas of signal processing and communications and can be used for a graduate level course in perhaps two ways.
Abstract: There has been a great deal of material in the area of discrete-time transforms that has been published in recent years. This book does an excellent job of presenting important aspects of such material in a clear manner. The book has 11 chapters and a very useful appendix. Seven of these chapters are essentially devoted to the Fourier series/transform, discrete Fourier transform, fast Fourier transform (FFT), and applications of the FFT in the area of spectral estimation. Chapters 8 through 10 deal with many other discrete-time transforms and algorithms to compute them. Of these transforms, the KarhunenLoeve, the discrete cosine, and the Walsh-Hadamard transform are perhaps the most well-known. A lucid discussion of number theoretic transforms i5 presented in Chapter 11. This reviewer feels that the authors have done a fine job of compiling the pertinent material and presenting it in a concise and clear manner. There are a number of problems at the end of each chapter, an appreciable number of which are challenging. The authors have included a comprehensive set of references at the end of the book. In brief, this book is a valuable contribution to the general areas of signal processing and communications. It can be used for a graduate level course in perhaps two ways. One would be to cover the first seven chapters in great detail. The other would be to cover the whole book by focussing on different topics in a selective manner. This book by Elliott and Rao is extremely useful to researchers/engineers who are working in the areas of signal processing and communications. It i s also an excellent reference book, and hence a valuable addition to one’s library

835 citations


Journal ArticleDOI
TL;DR: This paper is geared toward signal processing practitioners by emphasizing the practical digital realizations and applications of the FRFT, which is closely related to other mathematical transforms, such as time-frequency and linear canonical transforms.
Abstract: Fractional Fourier transform (FRFT) is a generalization of the Fourier transform, rediscovered many times over the past 100 years. In this paper, we provide an overview of recent contributions pertaining to the FRFT. Specifically, the paper is geared toward signal processing practitioners by emphasizing the practical digital realizations and applications of the FRFT. It discusses three major topics. First, the manuscripts relates the FRFT to other mathematical transforms. Second, it discusses various approaches for practical realizations of the FRFT. Third, we overview the practical applications of the FRFT. From these discussions, we can clearly state that the FRFT is closely related to other mathematical transforms, such as time-frequency and linear canonical transforms. Nevertheless, we still feel that major contributions are expected in the field of the digital realizations and its applications, especially, since many digital realizations of the FRFT still lack properties of the continuous FRFT. Overall, the FRFT is a valuable signal processing tool. Its practical applications are expected to grow significantly in years to come, given that the FRFT offers many advantages over the traditional Fourier analysis.

276 citations


Journal ArticleDOI
TL;DR: The present bibliography represents a comprehensive list of references on nonlinear system identification and its applications in signal processing, communications, and biomedical engineering.
Abstract: The present bibliography represents a comprehensive list of references on nonlinear system identification and its applications in signal processing, communications, and biomedical engineering. An attempt has been made to make this bibliography complete by listing most of the existing references up to the year 2000 and by providing a detailed classification group.

235 citations


Book
01 Jan 1998
Abstract: Advances in Imaging and Electron Physics merges two long-running serials, Advances in Electronics and Electron Physics and Advances in Optical and Electron Microscopy. The series features extended articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies, microlithography, image science, and digital image processing, electromagnetic wave propagation, electron microscopy, and the computing methods used in all these domains. * Contains contributions from leading authorities on the subject matter* Informs and updates on all the latest developments in the field of imaging and electron physics* Provides practitioners interested in microscopy, optics, image processing, mathematical morphology, electromagnetic fields, electron, and ion emission with a valuable resource* Features extended articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies, microlithography, image science, and digital image processing

216 citations


A. Jain1Institutions (1)
01 Sep 1976
TL;DR: The Karhunter-Loeve transform for a class of signals is proven to be a set of periodic sine functions and this Karhunen- Loeve series expansion can be obtained via an FFT algorithm, which could be useful in data compression and other mean-square signal processing applications.
Abstract: The Karhunen-Loeve transform for a class of signals is proven to be a set of periodic sine functions and this Karhunen-Loeve series expansion can be obtained via an FFT algorithm. This fast algorithm obtained could be useful in data compression and other mean-square signal processing applications.

206 citations


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Performance
Metrics

Author's H-index: 15

No. of papers from the Author in previous years
YearPapers
20184
20161
20141
20136
20123
20113