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The course is assessed entirely by coursework. The coursework involves the design and implementation of a signal processing project application and the explanation of how it works. The course is not centred on a mathematical description of digital signal processing but rather on algorithms. Mathematics is used to support and to explain the algorithm rather than as an end in itself. Each unit is presented firstly in terms of the physical concepts, using models and graphical representations as far as possible. Secondly, the unit is presented in terms of computer code in a modern programming language which provides a basic implementation of the concepts, supported where necessary by a mathematical description.

Networked computer work-stations each with graphics and sound replay provide a productive working environment.

  • UCL DSP Course - Overview.
  • Getting into Digital Signal Processing: A Basic Introduction.
  • If You're a Student!
  • Gods Whole Armor.
  • Serving Boys Through Readers Advisory (ALA Readers Advisory).
  • A Beginner's Guide to Digital Signal Processing (DSP).

Each student will be given their own account on the Departmental computer system and may use the computer facilities outside class time. Recommended Texts.

About this book

Lynn, W. Fuerst, B. Unit 1. Unit 2. Programming environment. Mathematical environment. Exercise 1. Organization: The first 7 chapters cover core theories that electrical and computer engineers should know and understand about digital signal processing. Chapters are optional, and may be presented in any order.

Each chapter is self-contained and provides interesting applications of DSP and an opportunity for students to apply the theoretical groundwork of the first 7 chapters. Chapter 8 discusses the realization and implementation of DSP. Chapter 9 introduces digital audio and operations. Chapter 10 introduces two-dimensional DSP. Chapter 11 introduces wavelets. When programming examples are required, they are written in C or a C-like syntax. End-of-chapter problem sets: To encourage students develop an intuitive sense of DSP systems, concept-oriented problems that require written explanations are included in addition to the standard design and analysis problems that require a numeric answer, a plot, or a design.

Additional Resources: Four appendices provide background information to support the core of the text. Table of Contents 1. The analog circuit analysis A digital filter replacement 1. Summation Formulas for Geometric Series C. Matrix Algebra C. Share a link to All Resources.

Digital Signal Processing

A typical piece of 'signal processing' might be to remove high-frequency electrical noise from a nearby electric motor. The circuit would probably be a Low-Pass Filter in this case. They had the advantage of being reliable and cheap to make in large quantities. Analogue signal processing was kept to a minimum because electronic components were expensive, unreliable and required skilled design engineers to make it work.

Let's look at this in more detail. Component tolerances are a major headache for the analogue hardware designer. Very specific values of resistors or capacitors might be needed to realize a particular specification, but only certain preferred values are manufactured. This might mean resorting to variable components at greatly increased cost plus the need for setting up adjustments after production. Component ageing is less of a problem nowadays thanks to new materials, but it can still be significant. For example, a resistor might have had a certain resistance value when it left the factory, but years later it may have changed enough to take the circuit outside its original specification or even to cause complete failure.

Electrical noise or Interference induced in the analogue circuit can sometimes be removed by additional circuitry if it can be distinguished from the wanted signal.

Introduction to Digital Signal Processing by Roman Kuc

More often than not, the electronics cannot tell the difference between noise and signal. Your brain can sort it all out, but even the most sophisticated analogue processing system cannot. The best you can hope for is to reduce overall noise to an acceptable level. Complex hardware design is needed for even simple processing tasks. Even if all you want to do is implement a low-pass filter, that is, remove all frequency components above a certain value from the signal, you will find it no easy task. Given a precise performance specification, there are a large number of possible techniques, each of which has an even larger number of possible circuit implementations.

The tolerance problems come in to play, and if that wasn't enough, the layout and design of the printed circuit board PCB it's all built on may add 'stray' capacitance effects leading to instability in a high-frequency design. Design compromises are inevitable.

Difficulties in debugging , modifying, or updating an analogue hardware design cause the product to be expensive at the outset, with much wastage of effort later. Mistakes in the circuit design lead to the physical replacement of components and remaking of PCBs. Updates later on will often involve similar physical changes, so much so that usually it is not worth bothering and the whole system is designed again from scratch. By now you could be forgiven for thinking that designing and making any new electronic system is fraught with such difficulty, that it's a miracle any 'high-tech' products are manufactured at all.

Fortunately, salvation is at hand with the invention of the computer and Discrete-Time or Digital Signal Processing. In the 's work by a telegraph engineer called Harry Nyquist formed the basis of what we now call digital signal processing, although even he based his ideas on much earlier work by others.

In order to realize the benefits of DSP, we must move from the Continuous-Time processing that we have been using up to now, to Discrete-Time processing. What is meant by 'Discrete-Time'?