Parallel implementations of backpropagation neural networks on transputers: a study of training set parallelism
This book presents a systematic approach to parallel implementation of feedforward neural networks on an array of transputers. The emphasis is on backpropagation learning and training set parallelism. Using systematic analysis, a theoretical model has been developed for the parallel implementation....
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Singapore
World Scientific Pub. Co.
c1996
|
| Series: | Progress in neural processing
3 |
| Subjects: | |
| Online Access: | FHN01 Volltext |
| Summary: | This book presents a systematic approach to parallel implementation of feedforward neural networks on an array of transputers. The emphasis is on backpropagation learning and training set parallelism. Using systematic analysis, a theoretical model has been developed for the parallel implementation. The model is used to find the optimal mapping to minimize the training time for large backpropagation neural networks. The model has been validated experimentally on several well known benchmark problems. Use of genetic algorithms for optimizing the performance of the parallel implementations is described. Guidelines for efficient parallel implementations are highlighted |
| Physical Description: | xviii, 202 p. ill |
| ISBN: | 9789812814968 |
Staff View
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| 520 | |a This book presents a systematic approach to parallel implementation of feedforward neural networks on an array of transputers. The emphasis is on backpropagation learning and training set parallelism. Using systematic analysis, a theoretical model has been developed for the parallel implementation. The model is used to find the optimal mapping to minimize the training time for large backpropagation neural networks. The model has been validated experimentally on several well known benchmark problems. Use of genetic algorithms for optimizing the performance of the parallel implementations is described. Guidelines for efficient parallel implementations are highlighted | ||
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| id | DE-604.BV044636440 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:57:49Z |
| institution | BVB |
| isbn | 9789812814968 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030034412 |
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| physical | xviii, 202 p. ill |
| psigel | ZDB-124-WOP ZDB-124-WOP FHN_PDA_WOP |
| publishDate | 1996 |
| publishDateSearch | 1996 |
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| publisher | World Scientific Pub. Co. |
| record_format | marc |
| series2 | Progress in neural processing |
| spelling | Saratchandran, P. Verfasser aut Parallel implementations of backpropagation neural networks on transputers a study of training set parallelism P. Saratchandran, N. Sundararajan, Shou King Foo Singapore World Scientific Pub. Co. c1996 xviii, 202 p. ill txt rdacontent c rdamedia cr rdacarrier Progress in neural processing 3 This book presents a systematic approach to parallel implementation of feedforward neural networks on an array of transputers. The emphasis is on backpropagation learning and training set parallelism. Using systematic analysis, a theoretical model has been developed for the parallel implementation. The model is used to find the optimal mapping to minimize the training time for large backpropagation neural networks. The model has been validated experimentally on several well known benchmark problems. Use of genetic algorithms for optimizing the performance of the parallel implementations is described. Guidelines for efficient parallel implementations are highlighted Parallel processing (Electronic computers) Neural networks (Computer science) Back propagation (Artificial intelligence) Transputers Sundararajan, Narasimhan Sonstige oth Foo, Shou King Sonstige oth Erscheint auch als Druck-Ausgabe 9789810226541 Erscheint auch als Druck-Ausgabe 9810226543 http://www.worldscientific.com/worldscibooks/10.1142/3094#t=toc Verlag URL des Erstveroeffentlichers Volltext |
| spellingShingle | Saratchandran, P. Parallel implementations of backpropagation neural networks on transputers a study of training set parallelism Parallel processing (Electronic computers) Neural networks (Computer science) Back propagation (Artificial intelligence) Transputers |
| title | Parallel implementations of backpropagation neural networks on transputers a study of training set parallelism |
| title_auth | Parallel implementations of backpropagation neural networks on transputers a study of training set parallelism |
| title_exact_search | Parallel implementations of backpropagation neural networks on transputers a study of training set parallelism |
| title_full | Parallel implementations of backpropagation neural networks on transputers a study of training set parallelism P. Saratchandran, N. Sundararajan, Shou King Foo |
| title_fullStr | Parallel implementations of backpropagation neural networks on transputers a study of training set parallelism P. Saratchandran, N. Sundararajan, Shou King Foo |
| title_full_unstemmed | Parallel implementations of backpropagation neural networks on transputers a study of training set parallelism P. Saratchandran, N. Sundararajan, Shou King Foo |
| title_short | Parallel implementations of backpropagation neural networks on transputers |
| title_sort | parallel implementations of backpropagation neural networks on transputers a study of training set parallelism |
| title_sub | a study of training set parallelism |
| topic | Parallel processing (Electronic computers) Neural networks (Computer science) Back propagation (Artificial intelligence) Transputers |
| topic_facet | Parallel processing (Electronic computers) Neural networks (Computer science) Back propagation (Artificial intelligence) Transputers |
| url | http://www.worldscientific.com/worldscibooks/10.1142/3094#t=toc |
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