## Abstract Feed‐forward neural networks have been used for pattern recognition, because they have an ability to estimate __a posteriori__ probability. This paper investigates the ability to estimate the __a posteriori__ probability by using one‐dimensional Gaussian distributions, uniform distribut
✦ LIBER ✦
On the determination of probability density functions by using Neural Networks
✍ Scribed by Lluís Garrido; Aurelio Juste
- Book ID
- 108314608
- Publisher
- Elsevier Science
- Year
- 1998
- Tongue
- English
- Weight
- 550 KB
- Volume
- 115
- Category
- Article
- ISSN
- 0010-4655
No coin nor oath required. For personal study only.
📜 SIMILAR VOLUMES
Estimation of the probability density fu
✍
Seiichi Nakagawa; Yoshiyuki Ono
📂
Article
📅
1994
🏛
John Wiley and Sons
🌐
English
⚖ 678 KB
Electricity Load Profile Determination b
✍
Norhasnelly Anuar; Zuhaina Zakaria
📂
Article
📅
2012
🏛
Elsevier
⚖ 478 KB
A note on the impulse-function determina
✍
George C. Sponsler
📂
Article
📅
1958
🏛
Elsevier Science
⚖ 304 KB
Estimation of the probability density by
✍
I. L. Eliseenko
📂
Article
📅
1990
🏛
Springer US
🌐
English
⚖ 469 KB
Modelling the tap density of inorganic p
✍
Vincent Moreschi; Sylvain Lalot; Christian Courtois; Anne Leriche
📂
Article
📅
2009
🏛
Elsevier Science
🌐
English
⚖ 714 KB
In the present study, the tap relative density of five inorganic powders is modelled using neural networks. These powders are similar in shape but have different true density. A large number of mixings are prepared from three classes (coarse, medium, and fine particles) and modelled. The inputs of t
Determining the load profiles of consume
✍
Gerbec, D.; Gasperic, S.; Smon, I.; Gubina, F.
📂
Article
📅
2004
🏛
The Institution of Electrical Engineers
🌐
English
⚖ 334 KB