𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Knowledge modelling in signal parameter evaluation

✍ Scribed by Grzegorz Smołalski


Publisher
Elsevier Science
Year
2009
Tongue
English
Weight
880 KB
Volume
42
Category
Article
ISSN
0263-2241

No coin nor oath required. For personal study only.


📜 SIMILAR VOLUMES


Parameter identification for conceptual
✍ Sarah M. Dunn; Chris Soulsby; Allan Lilly 📂 Article 📅 2003 🏛 John Wiley and Sons 🌐 English ⚖ 226 KB

## Abstract Improved methods for identification of conceptual parameter values are necessary if hydrological models are to be applied to catchments other than those to which they have been specifically calibrated. A technique has been devised to calculate conceptual parameter sets of a semi‐distrib

Evaluating parameters in models for flow
✍ L.W. Shemilt; S.C. Mehta 📂 Article 📅 1971 🏛 Elsevier Science 🌐 English ⚖ 168 KB

Shorter Communications generated and their distances travelled from the bubble. The data of Table 1 show that the ratio of the translational vortex velocity U, to the bubble rise velocity U is about constant being approximately 0-2.

An error parameter in TLM diffusion mode
✍ Xiang Gui; Paul W. Webb; Donard de Cogan 📂 Article 📅 1992 🏛 John Wiley and Sons 🌐 English ⚖ 753 KB

This paper reports the results of a study of an error parameter, m, which has been proposed as a measure for determining the effects on accuracy of the basic assumptions upon which TLM modelling of diffusion and heat flow has been founded. The nature of the m parameter is studied in detail by using

Laguerre Functions in Signal Analysis an
✍ Preston R. Clement 📂 Article 📅 1982 🏛 Elsevier Science 🌐 English ⚖ 508 KB

For the approximation of real functions in L2(0,w) that are frequently encountered in signal analysis and parameter identification, analytical and computer studies suggest the use of Laguerre functions. Such functions can form at least locally optimal or near-optimal sets. The results are shown for