Novel window functions for digital filters

Window technique is one of the simplest methods to design Finite Impulse Response (FIR) filters. It uses special functions to truncate an infinite sequence to a finite one. In this paper, we propose window techniques based on integer sequences. The striking feature of the proposed work is that it overcomes all the problems posed by floating point numbers and inaccuracy, as the sequences are made of only integers. Some of these integer window sequences, yield sharp transition, while some of them result in zero ripple in passband and stopband.

Systematic methodology for the design of high performance recursive digital filters

A systematic design methodology is described for the rapid derivation of VLSI architectures for implementing high performance recursive digital filters, particularly ones based on most significant digit (msd) first arithmetic. The method has been derived by undertaking theoretical investigations of msd first multiply-accumulate algorithms and by deriving important relationships governing the dependencies between circuit latency, levels of pipe-lining and the range and number representations of filter operands. The techniques described are general and can be applied to both bit parallel and bit serial circuits, including those based on on-line arithmetic. The method is illustrated by applying it to the design of a number of highly pipelined bit parallel IIR and wave digital filter circuits. It is shown that established architectures, which were previously designed using heuristic techniques, can be derived directly from the equations described.

Hydrograph separation and development of empirical relationships using single-parameter digital filters

A reliable hydrograph separation method is necessary for surface runoff modeling and hydrological studies. This paper investigates and compares the separation characteristics of two single-parameter digital filters, which are herein referred to as the one-parameter algorithm and the conceptual method. The application of the one-parameter algorithm was found to be restricted to low and medium baseflow separations, with a maximum separation limit of 50% of the total runoff hydrograph. The one-parameter algorithm was also observed to produce unrealistic sharp peaks under the peaks of the measured hydrograph when recession constant is smaller than 0.96. On the other hand, the conceptual method is applicable even for catchments fed largely by groundwater discharge. However, a reliable estimation of recession constant is a prerequisite for applying the conceptual method for large baseflow separations. Based on the hydrograph separation results, useful empirical relationships were developed for a partially urbanized watershed to estimate total runoff and direct runoff from the measured rainfall depth. The relationships between rainfall depth and total runoff depth and rainfall depth and direct runoff depth were found to be well represented by linear equations. The empirical relationships were then applied to estimate the long-term contribution of baseflow and surface runoff to total runoff at the study site. Baseflow was found to contribute about 58–61% of the annual total runoff.

Digital signal processing

Signal Processing (SP) is a subject of central importance in engineering and the applied sciences. Signals are information-bearing functions, and SP deals with the analysis and processing of signals (by dedicated systems) to extract or modify information. Signal processing is necessary because signals normally contain information that is not readily usable or understandable, or which might be disturbed by unwanted sources such as noise. Although many signals are non-electrical, it is common to convert them into electrical signals for processing. Most natural signals (such as acoustic and biomedical signals) are continuous functions of time, with these signals being referred to as analog signals. Prior to the onset of digital computers, Analog Signal Processing (ASP) and analog systems were the only tool to deal with analog signals. Although ASP and analog systems are still widely used, Digital Signal Processing (DSP) and digital systems are attracting more attention, due in large part to the significant advantages of digital systems over the analog counterparts. These advantages include superiority in performance,s peed, reliability, efficiency of storage, size and cost. In addition, DSP can solve problems that cannot be solved using ASP, like the spectral analysis of multicomonent signals, adaptive filtering, and operations at very low frequencies. Following the recent developments in engineering which occurred in the 1980's and 1990's, DSP became one of the world's fastest growing industries. Since that time DSP has not only impacted on traditional areas of electrical engineering, but has had far reaching effects on other domains that deal with information such as economics, meteorology, seismology, bioengineering, oceanology, communications, astronomy, radar engineering, control engineering and various other applications. This book is based on the Lecture Notes of Associate Professor Zahir M. Hussain at RMIT University (Melbourne, 2001-2009), the research of Dr. Amin Z. Sadik (at QUT & RMIT, 2005-2008), and the Note of Professor Peter O'Shea at Queensland University of Technology. Part I of the book addresses the representation of analog and digital signals and systems in the time domain and in the frequency domain. The core topics covered are convolution, transforms (Fourier, Laplace, Z. Discrete-time Fourier, and Discrete Fourier), filters, and random signal analysis. There is also a treatment of some important applications of DSP, including signal detection in noise, radar range estimation, banking and financial applications, and audio effects production. Design and implementation of digital systems (such as integrators, differentiators, resonators and oscillators are also considered, along with the design of conventional digital filters. Part I is suitable for an elementary course in DSP. Part II (which is suitable for an advanced signal processing course), considers selected signal processing systems and techniques. Core topics covered are the Hilbert transformer, binary signal transmission, phase-locked loops, sigma-delta modulation, noise shaping, quantization, adaptive filters, and non-stationary signal analysis. Part III presents some selected advanced DSP topics. We hope that this book will contribute to the advancement of engineering education and that it will serve as a general reference book on digital signal processing.

High performance VLSI architecture for Wave Digital Filtering

The application of fine grain pipelining techniques in the design of high performance Wave Digital Filters (WDFs) is described. It is shown that significant increases in the sampling rate of bit parallel circuits can be achieved using most significant bit (msb) first arithmetic. A novel VLSI architecture for implementing two-port adaptor circuits is described which embodies these ideas. The circuit in question is highly regular, uses msb first arithmetic and is implemented using simple carry-save adders. © 1992 Kluwer Academic Publishers.

Pipelined two-port adaptor for wave digital filtering

The application of fine-grain pipelining techniques in the design of high-performance wave digital filters (WDFs) is described. The problems of latency in feedback loops can be significantly reduced if computations are organized most significant, as opposed to least significant, bit first and if the results are fed back as soon as they are formed. The result is that chips can be designed which offer significantly higher sampling rates than otherwise can be obtained using conventional methods. How these concepts can be extended to the more challenging problem of WDFs is discussed. It is shown that significant increases in the sampling rate of bit-parallel circuits can be achieved using most significant bit first arithmetic.

Análise e implementação de filtros e controladores num sistema de processamento digital de sinal

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Automação e Electrónica Industrial