Software Toolkit For Designing An Artificial Neural Network.
Basically, there are two kinds of artificial neural network (ANN), which can be classified into supervised and unsupervised. Commonly, supervised neural networks are trained or weights adjusted, so that a particular input leads to a specific target output. Generally, the supervised training methods...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | en |
| Published: |
2004
|
| Subjects: | |
| Online Access: | http://eprints.usm.my/9799/1/Software_Toolkit_for_Designing_and_Artificial_Neural_Network_%28PPKKimia%29_2004.pdf http://eprints.usm.my/9799/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1834437108479033344 |
|---|---|
| author | Ahmad, M. A. Saleh, J Mohamad |
| author_facet | Ahmad, M. A. Saleh, J Mohamad |
| author_sort | Ahmad, M. A. |
| building | Hamzah Sendut Library |
| collection | Institutional Repository |
| content_provider | Universiti Sains Malaysia |
| content_source | USM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Basically, there are two kinds of artificial neural network (ANN), which can be classified into supervised and unsupervised. Commonly, supervised neural networks are trained or weights adjusted, so that a particular input leads to a specific target output. Generally, the supervised training methods are commonly used in solving most problems. An ANN can be designed, trained, validated and tested by means of the Neural Network Toolbox in Matlab.
|
| format | Conference or Workshop Item |
| id | my.usm.eprints.9799 |
| institution | Universiti Sains Malaysia |
| language | en |
| publishDate | 2004 |
| record_format | eprints |
| spelling | my.usm.eprints.9799 http://eprints.usm.my/9799/ Software Toolkit For Designing An Artificial Neural Network. Ahmad, M. A. Saleh, J Mohamad TK1-9971 Electrical engineering. Electronics. Nuclear engineering Basically, there are two kinds of artificial neural network (ANN), which can be classified into supervised and unsupervised. Commonly, supervised neural networks are trained or weights adjusted, so that a particular input leads to a specific target output. Generally, the supervised training methods are commonly used in solving most problems. An ANN can be designed, trained, validated and tested by means of the Neural Network Toolbox in Matlab. 2004 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.usm.my/9799/1/Software_Toolkit_for_Designing_and_Artificial_Neural_Network_%28PPKKimia%29_2004.pdf Ahmad, M. A. and Saleh, J Mohamad (2004) Software Toolkit For Designing An Artificial Neural Network. In: 1st National Postgraduate Colloquium, 2004, School of Chemical Engineering, USM . |
| spellingShingle | TK1-9971 Electrical engineering. Electronics. Nuclear engineering Ahmad, M. A. Saleh, J Mohamad Software Toolkit For Designing An Artificial Neural Network. |
| title | Software Toolkit For Designing An Artificial Neural Network. |
| title_full | Software Toolkit For Designing An Artificial Neural Network. |
| title_fullStr | Software Toolkit For Designing An Artificial Neural Network. |
| title_full_unstemmed | Software Toolkit For Designing An Artificial Neural Network. |
| title_short | Software Toolkit For Designing An Artificial Neural Network. |
| title_sort | software toolkit for designing an artificial neural network. |
| topic | TK1-9971 Electrical engineering. Electronics. Nuclear engineering |
| url | http://eprints.usm.my/9799/1/Software_Toolkit_for_Designing_and_Artificial_Neural_Network_%28PPKKimia%29_2004.pdf http://eprints.usm.my/9799/ |
| url_provider | http://eprints.usm.my/ |