✦ LIBER ✦

A max-piecewise-linear neural network for function approximation

✍ Scribed by Chengtao Wen; Xiaoyan Ma

Book ID: 113815323
Publisher: Elsevier Science
Year: 2008
Tongue: English
Weight: 394 KB
Volume: 71
Category: Article
ISSN: 0925-2312
DOI: 10.1016/j.neucom.2007.03.001

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Piecewise linear approximation applied t

Piecewise linear approximation applied to nonlinear function of a neural network

✍ Amin, H.; Curtis, K.M.; Hayes-Gill, B.R. 📂 Article 📅 1997 🏛 The Institution of Electrical Engineers 🌐 English ⚖ 556 KB

Neural Networks: A General Framework for

Neural Networks: A General Framework for Non-Linear Function Approximation

✍ Manfred M Fischer 📂 Article 📅 2006 🏛 John Wiley and Sons 🌐 English ⚖ 177 KB

Automatic training of a min-max neural n

Automatic training of a min-max neural network for function approximation by using a second feed forward network

✍ R. K. Brouwer 📂 Article 📅 2004 🏛 Springer 🌐 English ⚖ 298 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

An orthogonal neural network for functio

An orthogonal neural network for function approximation

✍ Shiow-Shung Yang; Ching-Shiow Tseng 📂 Article 📅 1996 🏛 IEEE 🌐 English ⚖ 614 KB

A unified approach for neural network-li

A unified approach for neural network-like approximation of non-linear functionals

✍ Tianping Chen 📂 Article 📅 1998 🏛 Elsevier Science 🌐 English ⚖ 56 KB

In this paper, we give a universal approach to approximation of non-linear functionals and so called myopic input-output maps by neural network-like architectures. Strong theorems on equi-uniform approximation to functionals in abstract spaces are given. As applications, theorems on identification o