✦ LIBER ✦

An orthogonal neural network for function approximation

✍ Scribed by Shiow-Shung Yang; Ching-Shiow Tseng

Book ID: 111654327
Publisher: IEEE
Year: 1996
Tongue: English
Weight: 614 KB
Volume: 26
Category: Article
ISSN: 1083-4419
DOI: 10.1109/3477.537319

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Orthogonal RBF Neural Network Approximat

Orthogonal RBF Neural Network Approximation

✍ Péter András 📂 Article 📅 1999 🏛 Springer US 🌐 English ⚖ 66 KB

Properties and performance of orthogonal

Properties and performance of orthogonal neural network in function approximation

✍ Chieh F. Sher; Ching-Shiow Tseng; Chen-San Chen 📂 Article 📅 2001 🏛 John Wiley and Sons 🌐 English ⚖ 216 KB

Backpropagation neural network has been applied successfully to solving uncertain problems in many fields. However, unsolved drawbacks still exist such as the problems of local minimum, slow convergence speed, and the determination of initial weights and the number of processing elements. In this pa

Orthogonal considerations in the design

Orthogonal considerations in the design of neural networks for function approximation

✍ B. Francois 📂 Article 📅 1996 🏛 Elsevier Science 🌐 English ⚖ 604 KB

Two problems occur in the design of feedforward neural networks: the choice of the optimal architecture and the initialization. Generally, input and output data of a system (or a function) are measured and recorded. Then, experimenters wish to design a neural network to map exactly these output valu

Toward generating neural network structu

Toward generating neural network structures for function approximation

✍ Tarek M. Nabhan; Albert Y. Zomaya 📂 Article 📅 1994 🏛 Elsevier Science 🌐 English ⚖ 893 KB

Algorithm for building a neural network

Algorithm for building a neural network for function approximation

✍ Jayadeva; Deb, A.K.; Chandra, S. 📂 Article 📅 2002 🏛 The Institution of Electrical Engineers 🌐 English ⚖ 565 KB

Cubic approximation neural network for m

Cubic approximation neural network for multivariate functions

✍ Doron Stein; Arie Feuer 📂 Article 📅 1998 🏛 Elsevier Science 🌐 English ⚖ 374 KB

This paper introduces a novel neural network architecture-cubic approximation neural network (CANN), capable of local approximation of multivariate functions. It is particularly simple in concept and in structure. Its simplicity enables a quantitative evaluation of its approximation capabilities, na