|
| | | | |
| | | |
| Stat |
Members: 3645
Articles: 2'506'133
Articles rated: 2609
26 April 2024 |
|
| | | | |
|
Article overview
| |
|
|
An introduction to artificial neural networks | | C.A.L. Bailer-Jones
; R. Gupta
; H.P. Singh
; | | Date: |
13 Feb 2001 | | Subject: | astro-ph | | Affiliation: | MPIA, Heidelberg), R. Gupta (IUCAA, Pune), H.P. Singh (Sri Venkateswara College, New Delhi | | Abstract: | Artificial neural networks are algorithms which have been developed to tackle a range of computational problems. These range from modelling brain function to making predictions of time-dependent phenomena to solving hard (NP-complete) problems. In this introduction we describe a single, yet very important, type of network known as a feedforward network. This network is a mathematical model which can be trained to learn an arbitrarily complex relationship between a data and a parameter domain, so can be used to solve interpolation and classification problems. We discuss the structure, training and interpretation of these networks, and their implementation, taking the classification of stellar spectra as an example. | | Source: | arXiv, astro-ph/0102224 | | Services: | Forum | Review | PDF | Favorites | |
|
|
No review found.
Did you like this article?
Note: answers to reviews or questions about the article must be posted in the forum section.
Authors are not allowed to review their own article. They can use the forum section.
browser Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; +claudebot@anthropic.com)
|
| |
|
|
|
|
News, job offers and information for researchers and scientists:
| |
REGISTER