K.M.M. Prabhu

Bio: K.M.M. Prabhu 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 15, co-authored 96 publications receiving 925 citations. Previous affiliations of K.M.M. Prabhu include Indian Institutes of Technology.

Block filtered-s least mean square algorithm for active control of non-linear noise systems

Abstract: In this study, the authors propose a block formulation of an algorithm, called the block-filtered-s LMS (BFSLMS) algorithm, for active control of non-linear noise processes for a multichannel setup. A reduced structure of the fast Fourier transform (FFT)-based BFSLMS-M (FBFSLMS-M) algorithm has also been studied. From this, the multichannel block filtered-x LMS (FBFXLMS-M) algorithm has been derived as a special case. The simulation results show that these algorithms have a matching performance with the already existing algorithms, with a relatively low computational complexity. A reduced structure delayless FBFSLMS algorithm for the multichannel case has also been developed which has a lesser computational complexity than its time-domain counterpart. Apart from this, it has no delay which, in general, is inherent in the block adaptive algorithms.

Space-frequency block coding in OFDM systems

Abstract: An effective technique to improve wireless communication performance is transmit diversity. In this work, transmitter diversity using a new combination of space-time block codes (STBCs) concatenated with orthogonal frequency division multiplexing (OFDM) system in high-speed wireless data communication is investigated. Simulation results demonstrate that this scheme can achieve a significant performance increase for efficient data transmission over slow and fast fading environments, compared to conventional OFDM. Performance of proposed scheme has been compared to an STBC-OFDM scheme and it is evident that SFBC is more robust than STBC-OFDM system in a fast fading environment.

New radix-3 FHT algorithm

Abstract: An efficient radix-3 fast Hartley transform (FHT) algorithm is introduced. The usual decomposition formula for a radix-3 FHT case is modified, resulting in less computations. It is useful in cases where the sequence length is closer to a power of 3 than a power of 2.

Multirate digital signal processing

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

Quantitative characterization of surface topography using spectral analysis

Abstract: Roughness determines many functional properties of surfaces, such as adhesion, friction, and (thermal and electrical) contact conductance. Recent analytical models and simulations enable quantitative prediction of these properties from knowledge of the power spectral density (PSD) of the surface topography. The utility of the PSD is that it contains statistical information that is unbiased by the particular scan size and pixel resolution chosen by the researcher. In this article, we first review the mathematical definition of the PSD, including the one- and two-dimensional cases, and common variations of each. We then discuss strategies for reconstructing an accurate PSD of a surface using topography measurements at different size scales. Finally, we discuss detecting and mitigating artifacts at the smallest scales, and computing upper/lower bounds on functional properties obtained from models. We accompany our discussion with virtual measurements on computer-generated surfaces. This discussion summarizes how to analyze topography measurements to reconstruct a reliable PSD. Analytical models demonstrate the potential for tuning functional properties by rationally tailoring surface topography - however, this potential can only be achieved through the accurate, quantitative reconstruction of the power spectral density of real-world surfaces.

Recent Advances on Active Noise Control: Open Issues and Innovative Applications

Abstract: The problem of acoustic noise is becoming increasingly serious with the growing use of industrial and medical equipment, appliances, and consumer electronics. Active noise control (ANC), based on the principle of superposition, was developed in the early 20th century to help reduce noise. However, ANC is still not widely used owing to the effectiveness of control algorithms, and to the physical and economical constraints of practical applications. In this paper, we briefly introduce some fundamental ANC algorithms and theoretical analyses, and focus on recent advances on signal processing algorithms, implementation techniques, challenges for innovative applications, and open issues for further research and development of ANC systems.