Digital Signal Processing: principles, devices and applications
Recent progress in the design and production of digital signal processing (DSP) devices has provided significant new opportunities to workers in the already extensive field of signal processing. It is now possible to contemplate the use of DSP techniques in costsensitive wide bandwidth applications, thereby making more effective use of the large body of available signal processing knowledge. Digital signal processing, long the province of telecommunications is, in both research and applications contexts, of growing importance in fields of medical signal analysis, industrial control (particularly robotics), in the analysis and synthesis of speech and in both audio and video entertainment systems. The growing demand for engineering skills in these areas has led to the writing of this book and the presentation of the material of the book at an lEEsponsored Vacation School at the University of Leicester. This book is different from others in the field in that it not only presents the fundamentals of DSP ranging from data conversion to ztransforms and spectral analysis, extending this into the areas of digital filtering and control, but also gives significant detail of the new devices themselves and how to use them. In addition to presenting the basic theory and describing the devices and how to design with them, the material is consolidated by extensive use of real examples in specific case studies. The book is directed at readers with first degree level training in engineering, physical sciences or mathematics and with some understanding of electronics, and is appropriate for design engineers in industry, users of DSP devices in scientific research and in all technical development areas associated with the processing of signals for display, storage, transmission or control.
Inspec keywords: digital control; signal processing; digital filters; statespace methods; microcontrollers; digital communication; speech processing; Kalman filters; systolic arrays
Other keywords: discrete signal; Ztransform; DSP chip; speech processing; microcontroller; IIR filter design; Fourier series; FIR filter design; state space control; Kalman filter; signal processing; digital filter; digital control; systolic array; digital communication system
Subjects: Microprocessor chips; Digital signal processing; Control engineering computing; Telecommunication applications; Microprocessors and microcomputers; Signal processing and detection; Computer networks and techniques
 Book DOI: 10.1049/PBCE042E
 Chapter DOI: 10.1049/PBCE042E
 ISBN: 9780863412103
 eISBN: 9781849193436
 Page count: 424
 Format: PDF

Front Matter
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1 Introduction  Engineering and Signal Processing
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The first part of the book contains the essential fundamentals of the theoretical bases of DSP. However most of the book is devoted to the practicalities of designing hardware and software systems for implementing the desired signal processing tasks and to demonstrating the properties of the new families of DSP chips which have enhanced progress so much recently. A book of this nature, which has a significant technological content, will inevitably tend to go out of date as time goes on. However the material has been written so that the fundamentals of the design and processing methods involved can be seen independently of the technology and thereby retain their value indefinitely.

2 Devices overview
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This survey of the development of the modern digital signal processor has concentrated on the mainstream DSP developments which have given us incredibly powerful and lowcost arithmetic processors. The view presented here is that the modern DSP is not historically derived from the conventional general purpose von Neumann processor, but from a separate 'species' of digital signal processors. Any similarities to the general purpose processor are of quite recent origin, driven by market forces and only skin deep. The DSP should in no way be seen as an enhanced performance general purpose microprocessor. The concentration on filtering, FFT and similar applications has meant that electronic engineers, rather than computer scientists have con trolled DSP development so that software developments have often lagged behind the von Neumann machines. Nevertheless, mainstream DSP development seems to be in the process of implementing the lessons learned from other computing activities.

3 Discrete signals and systems
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A discrete signal is one which is defined only at isolated discrete points in time, its value at other times being either unknown or assumed to be zero. A discrete signal thus contains only discontinuities and is best described analytically as a set of impulses. Most discrete signals are defined at equally spaced points in time but examples exist of unequal spacing which can successfully be processed. This book considers only equally spaced discrete signals. The amplitude of a discrete signal is normally considered to be an infinitely resolved function as with a continuous signal but the digital signal is a discrete signal which is an important exception to this and is classified separately.

4 Ztransforms
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In this chapter the ztransform representation of discrete signals and systems has been developed. The basic concepts have been reviewed, and the use of the transform in evaluating the frequency response has been shown. It is seen that the ztransform method of solving difference equations is analogous to the Laplace transform method; i.e. both techniques first transform the equations to polynomial representations in the corresponding complex variable and then invert them to obtain a closedform solution.

5 Fourier series and the discrete Fourier transform
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This chapter introduces the real and complex Fourier series. The Fourier integral is developed as a method for extracting spectral information from signals in the continuous time domain. The Fourier transform is developed and leads to the discrete Fourier transform. Important properties of the discrete Fourier transform and issues in its practical usage are explained. The discrete Fourier transform is related to the ztransform and other uses for it are highlighted.

6 The FFT and other methods of discrete Fourier analysis
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This chapter considers the radix2 FFT algorithm where the total number of data samples is an integer factor of two and discusses its application to spectral analysis of signals.

7 Introduction to digital filters
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In this chapter, digital filter are discussed. Digital signal processing (DSP) is an established method of filtering electrical waveforms and digital images, and it is an important topic in a number of diverse fields of science and technology. The realisation of the many practical applications has been made possible by the increased availability and falling costs of sophisticated verylargescale integrated (VLSI) circuits. In particular, the ubiquitous microprocessor and associated peripheral chips provide the means of implementing relatively simple and costeffective digital filters.

8 FIR filter design methods
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Nonrecursive digital filters have a finite impulse response (FIR) sequence, and they are inherently stable. Furthermore, a digital filter with a symmetrical impulse response has a linear phase characteristic, and therefore in this case there is no phase distortion imposed by the filter. In this chapter FIR filter design will be illustrated by considering the movingaverager filter, the frequency sampling method of design, and frequencydomain filter design using window functions.

9 IIR filter design methods
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The methods presented in this chapter are suitable for the design of recursive digital filters, and they readily implement signal filtering processes in a variety of practical applications. However, other design methods exist, each generally having merits for particular situations.

10 Quantisation and rounding problems in digital filters
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It has been shown that quantisation and rounding errors sometimes have considerable effects on the performance of digital filters, and therefore it is important that these are taken into account when considering their practical implementation. In this respect, to achieve adequate precision for the signal and number representation, a good estimate of the required processor word length must be made, and, if possible, a safety factor should be used so that three or four bits are added to the estimated word length.

11 State space control
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Classical design of digital controllers involves the use of frequency domain methods and the root locus. Control is restricted to singleinput, singleoutput systems. The aim of this chapter is to introduce the state space or modern approach to design. Although singleinput, singleoutput systems will mainly be considered, modern control design can readily be extended to cover systems with several inputs and outputs. The design of state feedback controllers is presented after a brief introduction to state space models including the key ideas of controllability and observability. The selection of feedback gains in order to achieve a desired set of closedloop poles will be familiar to engineers versed with classical design methods. The implementation of state feedback control laws assumes that all the state variables are known. In practice, the state vector is estimated from the measurements or plant outputs using an observer. Observer design is therefore treated next prior to an analysis of the complete controlestimator system.

12 Kalman filters
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This chapter presents an elementary introduction to Kalman filtering, starting from the simplest of all estimation problems, namely that of estimating a time independent scalar quantity from a number of noisy measurements. From this it move on to consider the case when the quantity to be estimated is a function of time, and then generalise the results to the estimation of a time dependent vector. Finally it indicates how the resulting Kalman filter equations can be applied to an elementary but nevertheless real problem in navigation.

13 Implementation of digital control algorithms
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The application of conventional 8 and 16 bit microcomputers to control systems is now well established. Such processors have general purpose (usually Von Neumann) architectures which make them applicable to a wide range of tasks, though not remarkably efficient in any. In control applications such devices may pose problems such as inadequate speed, difficulties with numerical manipulation and relatively high cost for the completed system. This latter being due to both the programming effort and the cost of the peripheral hardware. These problems may be overcome by the design of specially tailored architectures, provided that there is a sufficient volume of production to carry the overheads inherent in this approach. Special purpose I/O processors and signal processors are examples of applications where dedicated design has been successfully applied.

14 Comparison of DSP devices in control systems applications
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The use of digital signal processors as controllers offers a number of potential advantages. In particular DSPs incorporate a high degree of parallelism enabling the use of digital control in some very demanding applications. Areas such as robot control, turbogenerators and flight control systems immediately suggest themselves. In this context it is relevant to note that traditional 8bit microprocessors can execute a 2nd order controller algorithm (including “housekeeping”) in about 30 ms while more modern devices are capable of the same computation in 1ms. DSP devices can, by contrast, achieve times as short as 400ns.

15 Digital communication systems
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This chapter discusses the different coding technique to allow transmission of information. In digital communications systems the data to be transmitted are represented by a finite set of discrete values. Since the majority of digital electronic equipment utilises the binary number system because of the ease with which the 0 and 1 states can be generated and manipulated, the majority of systems are confined to just two values. This chapter is restricted to such binary systems and in keeping with modern usage the term bit denotes a binary digit.

16 Simulation of DSP devices and systems
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As DSP devices become more complex, they are finding their way into much larger, system level applications requiring interprocessor communications and realtime multitasking operating systems; as lower performance devices become cheaper their use in medium to low cost, high performance industrial control applications is increasing. In most DSP applications, sophisticated tool sets for system design and development are almost essential to allow DSP users to get high performance products to the market place in the shortest possible time. Simulation tools are becoming an increasingly important part of the tool set, improving productivity at both the system design stage and in the development of software.

17 Review of architectures
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This survey of DSP architectures shows how difficult it would be to recommend one processor for all tasks. If economic considerations were included, a choice would become even more difficult. However, increasingly powerful general purpose digital signal processors are being supplemented not only by low cost versions, but by specialised architectures. The optimum processing environment is certainly worth looking for.

18 DSP chips  a comparison
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The most widely used type of digital signal processor is the stored program monolithic processor, used for general purpose signal processing and other applications requiring fast arithmetic. These three DSPs have some features in common, such as fast, synchronous serial ports, special addressing modes and onchip memory.

19 Microcontrollers
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Microcontrollers originated from the concept of the microprocessor system, typified by separate chiplevel processor, memory and I/O devices. The resulting devices combine many typical microprocessor system needs within a single device. Microcontrollers were aimed at I/O intensive, yet algorithmically simple, real time applications. Recent microcontrollers have been designed with considerable hardware enhancement, particularly with respect to arithmetic capabilities and peripheral autonomy, and a new generation of DSPs, the so called digital signal controllers (DSCs) has been introduced. Next generation DSCs are likely to offer peripheral handling, bit manipulation and interrupt implementation comparable to stateoftheart microcontrollers. Microcontrollers will continue to be available across a broad span of capability and cost, as many applications will not need fast signal processing capability.

20 Systolic arrays for high performance digital signal processing
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In this chapter attention has been focused mainly on research undertaken by the author and his colleagues. Considerable effort has also been devoted in many other laboratories worldwide on research on VLSI array processor architectures which are pipelined at the bit level and suitable for high performance DSP chip design. Quite a number of these architectures have been used as the basis of chip designs. Further information on these designs are available from a number of sources.

21 Throughput, speed and cost considerations
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An example has been described of the coding of a speech recognition algorithm onto a floating point digital signal processor by means of a high level language compiler. It has been shown that this can considerably reduce the engineering effort required, compared with that for a fixed point DSP using assembly language. It must be concluded however, that it is necessary to use assembly coding for computationally intensive routines if realtime performance is to be achieved. When devices are used in production volumes, the extra cost of floating point over fixed point devices will not be justified by the savings in engineering costs. However, if the cost of engineering effort involved in programming the DSP is significant, when compared with the total cost of the DSP devices, then the extra cost for a floating point device can be justified by the saving of incremental engineering costs. This is particularly the case if further modifications of the algorithm may be required.

22 A case study of a DSP chip for online monitoring and control in anaesthesia
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This chapter presents a case study of computeraided instrumentation for online measurement and control in the area of critical care medicine. The system has been initially developed to test the hypothesis that acoustic resonance of the respiratory airways represents an optimal state for alveolar gas exchange. high frequency jet ventilation (HFJV) is a recognised form of mechanical ventilatory support that is used in both anaesthesia and critical care medicine. The technique differs from conventional modes of ventilatory support in both its relative tidal volume and respiratory rate. Several studies have shown that HFJV is capable of maintaining adequate gas exchange in cases where conventional methods have either failed or proved to be impractical. The main advantages of HFJV include lower peak and mean airway pressures, a reduction in pulmonary barotrauma and less disturbance to cardiovascular function.

23 A case study on digital communication systems
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In the following sections of this chapter, the application of some of these techniques are discussed. The treatment given to all of the topics, particularly those areas concerned with the propagation aspects, is necessarily brief, however more detailed information may be obtained from the various references.

24 Digital filters  a case study
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The purpose of this case study is to present a development of the stepinvariant approach to highpass digital filter design. It will be shown that the transfer function,G(z) obtained via the step invariant design method, may be made to approximate closely to the transfer function, G(z) obtained via the bilinear ztransform method. The analysis presented justifies this stepinvariant design method, and shows that it is possible to convert a time domain (stepinvariant) filter, G(z) to one that satisfies a frequency domain specification,G(z) . This is achieved by observing certain conditions and by employing a suitable gain term. The validity of the method is demonstrated using a practical example of a simple highpass filter and a digital phaseadvance network.

25 Speech processing using the TS32010  a case study
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This case study illustrates the now classical Linear Predictive Coding (LPC) method of speech compression used to reduce the bit rate in digital speech transmission systems. The chapter begins with a nonrigerous introduction to the theory of linear predictive coding. This is followed by an explanation of the realtime algorithms used to calculate the parameters required to synthesise individual pitches of voiced speech. The study ends with a description of how these algorithms are implemented on the TMS32010, the problems incurred and results obtained.

26 A case study in digital control
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The system described has shown that the use of a DSP in the role of measurement for control gives advantages over conventional systems. Increased speed, and the capability to use more complex algorithms leads to improved controller performance. Although designed specifically for a laboratory system, the necessity for improved measurement systems in industry is growing. Manufacturers are now starting to implement digital controllers, the performance of which will soon be limited by a lack of accurate information at high transfer rates. Parameters which were once deemed unmeasurable can now be constructed online and in realtime. This opens up greater possibilities for control system designers. Specialist hardware which was originally designed for communications processing will have an increasing role in control systems implementation due to the similarities in algorithm structure. Manufacturers have already seen this trend, and have begun to produce high performance devices specifically for these applications. It is now up to the systems engineer to recognise the advantages of the DSP for particular applications, and to use these to the full.

27 Implementation and performance of digital controllers
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This chapter discusses the signal processing capability of the TMS320 can be readily harnessed to implement a range of digital controllers. It has demonstrated that the powerful architecture of this DSP lends itself to implement efficiently the kind of algorithms met in discrete controllers and that a great deal of structure is possible with the system.

28 Review and outlook for the future
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In this review a brief summary is given of the current trends and new directions in the development of algorithms, architectures and devices for signal processing. This, of necessity, is a personal view point, nevertheless, with significant new developments over the horizon, the subject area of signal processing is set to grow and grow. As a final statement, the integration of fast algorithms, parallel architectures, and high performance multiprocessors, the field of parallel signal processing and its applications is one which will lead to rich rewards.

Back Matter
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