Modelling of direction-dependent dynamic processes: A comparison of Wiener models and neural networks
UNSPECIFIED (2002) Modelling of direction-dependent dynamic processes: A comparison of Wiener models and neural networks. In: 19th IEEE Instrumentation and Measurement Technology Conference (IMTC/2002), MAY 21-23, 2002, ANCHORAGE, AK.Full text not available from this repository.
The modelling of direction-dependent processes using Wiener and neural network models is compared for several different processes and for three different types of input signal - a pseudo-random binary signal (prbs), art inverse-repeat pseudo-random binary signal (irprbs) and a multisine (sum of harmonics) signal. Experimental results on an electronic nose are presented to illustrate the applicability of the techniques discussed.
|Item Type:||Conference Item (UNSPECIFIED)|
|Series Name:||IEEE INSTRUMENTATION & MEASUREMENT TECHNOLOGY CONFERENCE, PROCEEDINGS|
|Journal or Publication Title:||IMTC 2002: PROCEEDINGS OF THE 19TH IEEE INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE, VOLS 1 & 2|
|Number of Pages:||6|
|Page Range:||pp. 215-220|
|Title of Event:||19th IEEE Instrumentation and Measurement Technology Conference (IMTC/2002)|
|Location of Event:||ANCHORAGE, AK|
|Date(s) of Event:||MAY 21-23, 2002|
Actions (login required)