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

http://ieeexplore.ieee.org/iel5/5/31347/01457444.pdf

Multirate digital signal processing

Fractional Fourier transform as a signal processing tool: An overview of recent developments

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.

/pdf/quantitative-characterization-of-surface-topography-using-1di6n32wn5.pdf

Quantitative characterization of surface topography using spectral analysis

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.

/pdf/recent-advances-on-active-noise-control-open-issues-and-1wg2ydx57i.pdf

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

https://www.dtc.umn.edu/s/resources/gg-se.pdf

A bibliography on nonlinear system identification

We describe a class of reduced complexity IIR cosine modulated filter banks satisfying the perfect reconstruction property. They are shown to be easy to implement, in terms of the number of filters, both on the analysis and on the synthesis sides. We provide closed-form expressions for the polyphase components of the synthesis prototype in terms of those of the analysis prototype. We also derive an expression for the frame ratio for this class of filter banks.

A class of M-channel reduced complexity IIR cosine modulated filter banks

In this paper study on date windows has been presented which enables to select a window optimally for a desired application in digital signal processing. Various window parameters for a number of windows have been compared. The effect of quantization of window-samples on these parameters have been determined which show that the window-sample word-length of 8 bits is adequate to closely approximate the unquantized window. The windowing in frequency domain has been considered end compared with the time domain implementation for spectral estimation (using FFT) applications. It is seen that the former, in general, is simpler for implementation and provides a better computational accuracy.

Selection of data windows for digital signal processing

In this paper, we propose a method for designing a class of M-channel, causal, stable, perfect reconstruction, infinite impulse response (IIR), and parallel uniform discrete Fourier transform (DFT) filter banks. It is based on a previously proposed structure by Martinez et al. [1] for IIR digital filter design for sampling rate reduction. The proposed filter bank has a modular structure and is therefore very well suited for VLSI implementation. Moreover, the current structure is more efficient in terms of computational complexity than the most general IIR DFT filter bank, and this results in a reduced computational complexity by more than 50% in both the critically sampled and oversampled cases. In the polyphase oversampled DFT filter bank case, we get flexible stop-band attenuation, which is also taken care of in the proposed algorithm.

Design of M-Channel IIR Uniform DFT Filter Banks Using Recursive Digital Filters

Fast Hartley transform implementation on DSP chips

For a multiband signal, the minimum sampling rate required for an arbitrary sampling method, which allows perfect reconstruction, is NB, where N is the number of bands and B is the maximum bandwidth. It has been proposed in the literature that, if the carrier frequency information of a multiband signal is not known apriori, then we require a minimum sampling rate of 2NB for perfect reconstruction. Modulated wideband converter (MWC) is a recently introduced blind sampling method. Unlike the traditional sampling methods, where the continuous-time signal can be expressed in terms of samples using simple Whittaker-Shannon interpolation, there is no closed-form expression relating the samples generated by MWC and the continuous-time signal. In order to reconstruct the signal, we require compressive sensing (CS) algorithm. The CS algorithm, simultaneous orthogonal matching pursuit (SOMP) used in the reconstruction stage requires a minimum rate of 4N B log(M/2N), which is nearly twice the theoretical rate. In this paper, we propose a new greedy algorithm, which exploits the clustered sparse structure of the multiband signals to sample at near-theoretical rates. The simulation results supporting the better performance of our algorithm are also presented.

K.M.M. Prabhu

Papers

A class of M-channel reduced complexity IIR cosine modulated filter banks

Selection of data windows for digital signal processing

Design of M-Channel IIR Uniform DFT Filter Banks Using Recursive Digital Filters

Fast Hartley transform implementation on DSP chips

A new approach to near-theoretical sampling rate for modulated wideband converter