Neural Computing: An Introduction to the Principles with Application Examples (4 Modules)

Synopsis

Video-based distance learning course in neural computing, a technology that simulates the neural behaviour of living things so that a computer can learn to differentiate or model, without formal analysis and detailed programming.
1: Basic concepts of neural networks and their application; background concepts; applications in marketing (predicting soft drink sales), process control, polymer manufacture, financial forecasting, property valuation, improving hospital treatment, mail sorting, food inspection, and industrial inspection.
2: Describes the operation and application of supervised neural networks and provides a phased description of supervised networks, introducing more complexity and classification power at each phase of the description. Covers: revision of the artificial neural network (ANN) model; single-layer perceptron; learning methods - Widrow-Hoff LMS; abilities and limitations - non-separability (EOR problem); concepts of hyperplanes; error terms; activation funcitons; multilayer perceptrons; role of hidden layers; backpropagation and generalised delta learning rules and variations; learning factors; choosing correct size of network and input data considerations; generalisation; network pruning; radial basis networks.
3: Introduces unsupervised, self-organised and adapting networks, using computer-generated animation. Covers: basic concepts of pattern classificaiton; vector notation; measurement, feature and decision spaces; differences between supervised and unsupervised learning and the use of distance measures to relate the similarity of patterns; the Kohonen feature map; applications.
4: Four case studies using neural networks and unsupervised networks: speech detection and noise elimination - an automatic communication ‘squelch’ system, using multi-layer perceptron for speech detection and noise elimination; machine condition monitoring; predicting commodity markets; visualisation of world poverty.

Language

English

Country

Great Britain

Medium

Video; Videocassette. VHS. col. 4 x 30 min.

Year of production

1996

Availability

Sale; 2000 sale: £100.00 (+VAT +p&p) each module 2000 sale: £350.00 (+VAT +p&p) full course

Documentation

Supporting notes with each video explain the technology and present examples of applications.

Uses

Directors and managers for assessing the technology’s potential; practising engineers and scientists; engineering and technical staff; higher education courses.

Subjects

Information technology

Keywords

computer science; neural networks

Credits

Producer

Graham Long

Writer

Graham Long; Neil Allinson

Contributor

David Cullen

Sections

Title

Introduction of neural networks

Synopsis

1: Basic concepts of neural networks and their application; background concepts; applications in marketing (predicting soft drink sales), process control, polymer manufacture, financial forecasting, property valuation, improving hospital treatment, mail s

Title

Supervised networks

Synopsis

2: Describes the operation and application of supervised neural networks and provides a phased description of supervised networks, introducing more complexity and classification power at each phase of the description. Covers: revision of the artificial ne

Title

Unsupervised networks

Synopsis

3: Introduces unsupervised, self-organised and adapting networks, using computer-generated animation. Covers: basic concepts of pattern classificaiton; vector notation; measurement, feature and decision spaces; differences between supervised and unsupervi

Title

Case studies

Synopsis

4: Four case studies using neural networks and unsupervised networks: speech detection and noise elimination - an automatic communication 'squelch' system, using multi-layer perceptron for speech detection and noise elimination; machine condition monitori

Sponsor

Name

Institution of Electrical Engineers

Distributor

Name

Marketing Dept

Web

http://www.iee.org.uk External site opens in new window

Phone

01438 767290

Fax

01438 742840

Address

Michael Faraday House
Six Hills Way
Stevenage, Herts SG1 2AY

Name

University of York, York Electronics Centre

Web

http://www.yec.york.ac.uk/yec External site opens in new window

Phone

01904 432323

Fax

01904 432333

Address

Department of Electronics
Heslington
York
YO1 5DD