✦ LIBER ✦

Learning in feed-forward neural networks by improving the performance

✍ Scribed by Mirta B. Gordon; Pierre Pereto; Miguel Rodriguez-Girones

Publisher: Elsevier Science
Year: 1992
Tongue: English
Weight: 390 KB
Volume: 185
Category: Article
ISSN: 0378-4371
DOI: 10.1016/0378-4371(92)90481-5

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Learning color-appearance models by mean

Learning color-appearance models by means of feed-forward neural networks

✍ P. Campadelli; C. Gangai; R. Schettini 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 525 KB

Device-independent color imaging demands a reliable color-appearance model. We present a method for faithfully approximating color-appearance models by means of feed-forward neural networks trained with the error back-propagation algorithm. In particular, we present experimental evidence that in sev

Learning in the feed-forward random neur

Learning in the feed-forward random neural network: A critical review

✍ Michael Georgiopoulos; Cong Li; Taskin Kocak 📂 Article 📅 2011 🏛 Elsevier Science 🌐 English ⚖ 959 KB

The addition of neural networks to the i

The addition of neural networks to the inner feedback path in order to improve on the use of pre-trained feed forward estimators

✍ D.A. Sanders; B.P. Haynes; G.E. Tewkesbury; I.J. Stott 📂 Article 📅 1996 🏛 Elsevier Science 🌐 English ⚖ 555 KB

A learning control architecture which uses a multi-layer feed forward neural network with error back propagation is described. The architecture includes a feed forward estimator which is pre-trained and a feedback controller which continues to learn. The properties of the architectures are investiga

Back-propagation learning in improving t

Back-propagation learning in improving the accuracy of neural network-based tourism demand forecasting

✍ Rob Law 📂 Article 📅 2000 🏛 Elsevier Science 🌐 English ⚖ 184 KB

Traditional tourism demand forecasting techniques concentrate predominantly on multivariate regression models and univariate time-series models. These single mathematical function-based forecasting techniques, although they have achieved a certain degree of success in tourism forecasting, are unable

An improved time series prediction by ap

An improved time series prediction by applying the layer-by-layer learning method to FIR neural networks

✍ Hee-Yeal Yu; Sung-Yang Bang 📂 Article 📅 1997 🏛 Elsevier Science 🌐 English ⚖ 921 KB

The FIR neural network model was recently proposed for time series prediction and gave good results. However, the learning algorithm used for the FIR network is a kind of gradient descent method and hence inherits all the well-known problems of the method. Recently a new learning algorithm called th

Reduction of the size of the learning da

Reduction of the size of the learning data in a probabilistic neural network by hierarchical clustering. Application to the discrimination of seeds by artificial vision

✍ Younes Chtioui; Dominique Bertrand; Dominique Barba 📂 Article 📅 1996 🏛 Elsevier Science 🌐 English ⚖ 798 KB

The control of seed batches is necessary before their commercialization. In the present work, we attempted to apply computer vision to this goal. A pattern recognition system formed by a color image analysis device combined with a neural network classifier was tested on a practical problem which con