Module Information

Module Identifier
CS10510
Module Title
Further Mathematics for Computer Science
2013/2014
Co-ordinator
Semester
Semester 1
Mutually Exclusive
Mutually Exclusive
Pre-Requisite
C in AS level Mathematics or equivalent
Other Staff

Course Delivery

Delivery Type Delivery length / details
Lecture 20 hours
Practical 6 x 1 hour workshops

Assessment

Assessment Type Assessment length / details Proportion
Semester Assessment Written problem based assignment on techniques introduced in the module.  20%
Semester Exam 2 Hours   Written Exam  80%
Supplementary Exam 2 Hours   Written Exam  Resubmission of failed/non-submitted coursework components of ones of equivalent value.  100%

Learning Outcomes

On successful completion of this module students should be able to:

1. In the area of Number Representation perform tasks such as:
Carry out calculations in 2's complement and excess-n representations; Calculate precision and accuracy of floating point representations; Give examples of unexpected results of comparison that occur with floating point representations, and suggest programming alternatives.

2. In the area of Geometry perform tasks such as:
Relate concepts from 2 and 3-dimensional coordinate geometry to vector algebra; perform computations using vectors and matrices to implement elementary algorithms used in computer graphics and robotics

3. In the area of Counting Techniques perform tasks such as:
Use sum and product rules, inclusion exclusion and the pigeonhole principle to answer questions about data and communications resources.

4. In the area of Probability and Statistics perform tasks such as:
Describe the concept of variability and its manifestation in statistical diagrams; Describe the concepts involved in the statistical modelling of randomness.

5. In the area of Induction carry out proof by induction and complete induction over N.

6. In the area of Calculus perform tasks such as:
Calculate the gradient of a curve and locate maxima, minima and turning points of a function; Calculate indefinite and definite integrals and find the area under a curve.

Aims

This module aims to provide students with the skills needed for successful completion of Part II courses on: Graphics (geometry), Communications (information theory and coding, network planning, network management), Robotics (kinematics), Artificial Intelligence (learning), Vision (functions and their gradients), Image processing (vectors and matrices) and Quantitative Methods (metrics).

Brief description

This module provides a range of skills needed for successful study in graphics, communications, algorithm analysis, vision, robotics and artificial intelligence.

Content

This module aims to provide students with the skills needed for successful completion of Part II courses on: Graphics (geometry), Communications (information theory and coding, network planning, network management), Robotics (kinematics), Artificial Intelligence (learning), Vision (functions and their gradients), Image processing (vectors and matrices) and Quantitative Methods (metrics).

1.Number representation: (4 lectures)

Calculations in 2's complement and excess-n representations; precision and accuracy of floating point representations; examples of zero-divisions and unexpected results of comparison that occur because a floating point representation comprises a finite set of representatives of real intervals; programming alternatives; cancellation and guard digits.

2.Geometry: (4 lectures)

2 and 3-dimensional coordinate geometry; basic trigonometrical functions and identities, relating angles in different quadrants; vector and matrix algebra; elementary algorithms in computer graphics and robotics.

3.Counting Techniques: (4 lectures)

Sum and product rules, inclusion exclusion and the pigeonhole principle; application of counting techniques to problems in data structures and communications. Summarising data. Shapes of distributions. Binomial experiments and large sample behaviour. The Poisson distribution as a model for randomness. Quick and graphical tests for the Poisson distribution. Waiting times and the exponential distribution. Basic ideas of significance and goodness of fit.

4.Induction: (4 lectures)

What is induction? Proof by induction over N; the Principle of Complete Induction.

5.Calculus: (4 lectures)

Gradient of a curve; maxima, minima and turning points of a function; indefinite and definite integrals; area under a curve.

Module Skills

Skills Type Skills details
Application of Number Inherent to subject.
Communication In assignment and exam.
Improving own Learning and Performance Mastering Mathematical skills which facilitate learning in many other areas of Computer Science and Software Engineering. Peer marking.
Information Technology
Personal Development and Career planning
Problem solving Inherent to subject.
Research skills
Subject Specific Skills
Team work

Recommended Text
Croft, Tony (1997.) Foundation maths /Anthony Croft, Robert Davison. 2nd ed. Addison Wesley Primo search James, Glyn. (2001.) Modern engineering mathematics /Glyn James ... [et al.]. 3rd ed. Prentice Hall Primo search Rosen, Kenneth H. (1999.) Discrete mathematics and its applications /Kenneth H. Rosen. 4th ed. WCB/McGraw-Hill Primo search

Notes

This module is at CQFW Level 4