Module Title:   Signal Processing

Module Credit:   20

Module Code:   CM-0429D

Academic Year:   2015/6

Teaching Period:   Semester 1

Module Occurrence:   A

Module Level:   FHEQ Level 7

Module Type:   Standard module

Provider:   Computer Science

Related Department/Subject Area:   SCIM (Dept of Computer Science)

Principal Co-ordinator:   Dr J.M.Noras

Additional Tutor(s):   Prof R.A. Abd-Alhameed.

Prerequisite(s):   None

Corequisite(s):   None

To provide detailed knowledge of the nature of signals and their response in discrete-time electronic systems and the mathematical methods of the advanced real-time digital processing.

Learning Teaching & Assessment Strategy:
Concepts, principles & theories explored in formal lectures, practiced in tutorials and demonstrated in laboratory classes.
Practical skills developed in laboratory sessions.
Cognitive and personal skills developed in open-ended problem solving and design exercises, tackled by working in small groups supported by members of academic staff.
Oral feedback is given during labs and seminars. The classroom tests and coursework (50%) will assess your grasp of the knowledge base of the module; and a formal examination (50%) will assess the learning outcomes expressed in the descriptor.
Supplementary assessment: repair deficiencies

Lectures:   36.00          Directed Study:   54.00           
Seminars/Tutorials:   18.00          Other:   72.00           
Laboratory/Practical:   18.00          Formal Exams:   2.00          Total:   200.00

On successful completion of this module you will be able to...

* critically review and analyse the principles of signal theory in relation to the behaviour of electrical and electronic circuits.

On successful completion of this module you will be able to...

* evaluate the theory underpinning discrete-time systems, and the design techniques for real-time digital signal processing systems.

On successful completion of this module you will be able to...

* demonstrate skills relating to scientific method, systematic problem solving and creative problem solving.

  Classroom test   25%
  Classroom test
  Coursework   25%
  Examination - closed book 2.00 50%
  Examination - closed book 2 hours

Outline Syllabus:
Description and classification of signals in the time and frequency domains.
Correlation as a method of signal identification; orthogonal and orthonormal functions. Fourier series for periodic functions, Parseval`s theorem, energy density spectra, Gibb`s phenomenon, convolution, central limit theorem, system impulse response.
Discrete Fourier Transform: sampling, time and bandwidth limitations.
Random signals; probability density, time and ensemble averages, statistical dependence, relationship to signal power, autocorrelation and cross-correlation, Wiener-Kintchine relationship, power density.
General concepts of linear and non-linear systems.
Overview of the field of applications of DSP.
Realisation of digital linear systems: FIR and IIR systems, z-transforms and digital filter design, FIR and IIR Filters, introduction to matched filters and adaptive filters.
The Fast Fourier transform: computational complexity of the DFT, implementations of the FFT and computational savings. Spectrum estimation and analysis, windowing, the periodogram.
DSP hardware: DSP architecture, floating point and fixed-point implementation, DSP algorithms (DCT, Walsh, wavelet).
Implementation with hardware/software development systems, interfacing to MATLAB for practical testing.

Version No:  1