✦ LIBER ✦

A note on a higher-order neural network for distortion invariant pattern recognition

✍ Scribed by Manabu Takano; Taiho Kanaoka; Josef Skrzypek; Shingo Tomita

Publisher: Elsevier Science
Year: 1994
Tongue: English
Weight: 318 KB
Volume: 15
Category: Article
ISSN: 0167-8655
DOI: 10.1016/0167-8655(94)90024-8

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

A higher-order neural network for distor

A higher-order neural network for distortion invariant pattern recognition

✍ Taiho Kanaoka; Rama Chellappa; Matsubuchi Yoshitaka; Shingo Tomita 📂 Article 📅 1992 🏛 Elsevier Science 🌐 English ⚖ 496 KB

A maximum overlap neural network for pat

A maximum overlap neural network for pattern recognition

✍ E. Domany; H. Orland 📂 Article 📅 1987 🏛 Elsevier Science 🌐 English ⚖ 194 KB

A neural network capable of learning and

A neural network capable of learning and inference for visual pattern recognition

✍ Ho J Kim; Hyun S Yang 📂 Article 📅 1994 🏛 Elsevier Science 🌐 English ⚖ 869 KB

A neural network system with an automati

A neural network system with an automatic generation mechanism for distorted patterns

✍ K. Shimohara; Y. Tokunaga; T. Uchiyama; Y. Kimura 📂 Article 📅 1988 🏛 Elsevier Science 🌐 English ⚖ 75 KB

Neural network modeling of microwave FET

Neural network modeling of microwave FETs based on third-order distortion characterization

✍ F. Giannini; P. Colantonio; G. Orengo; A. Serino 📂 Article 📅 2006 🏛 John Wiley and Sons 🌐 English ⚖ 539 KB

A new method for characterization of HEMT distortion parameters, which extracts the coefficents of a Taylor series expansion of I ds (V gs , V ds ), including all cross-terms, is developed from low-frequency harmonic measurements. The extracted parameters will be used either in a Volterra series mod

Pattern recognition strategies for molec

Pattern recognition strategies for molecular surfaces: III. Binding site prediction with a neural network

✍ Matthias Keil; Thomas E. Exner; Jürgen Brickmann 📂 Article 📅 2004 🏛 John Wiley and Sons 🌐 English ⚖ 335 KB 👁 1 views

An algorithm for the identification of possible binding sites of biomolecules, which are represented as regions of the molecular surface, is introduced. The algorithm is based on the segmentation of the molecular surface into overlapping patches as described in the first article of this series.1 The