Sciweavers
Explore
Publications
Books
Software
Tutorials
Presentations
Lectures Notes
Datasets
Labs
Conferences
Community
Upcoming
Conferences
Top Ranked Papers
Most Viewed Conferences
Conferences by Acronym
Conferences by Subject
Conferences by Year
Tools
Sci2ools
International Keyboard
Graphical Social Symbols
CSS3 Style Generator
OCR
Web Page to Image
Web Page to PDF
Merge PDF
Split PDF
Latex Equation Editor
Extract Images from PDF
Convert JPEG to PS
Convert Latex to Word
Convert Word to PDF
Image Converter
PDF Converter
Community
Sciweavers
About
Terms of Use
Privacy Policy
Cookies
Free Online Productivity Tools
i2Speak
i2Symbol
i2OCR
iTex2Img
iWeb2Print
iWeb2Shot
i2Type
iPdf2Split
iPdf2Merge
i2Bopomofo
i2Arabic
i2Style
i2Image
i2PDF
iLatex2Rtf
Sci2ools
51
click to vote
DSP
2011
favorite
Email
discuss
report
279
views
Emerging Technology
»
more
DSP 2011
»
Identification methods for Hammerstein nonlinear systems
13 years 5 months ago
Download
www.ece.ualberta.ca
Feng Ding, Peter Xiaoping Liu, Guangjun Liu
Real-time Traffic
DSP 2011
|
Emerging Technology
|
claim paper
Related Content
»
Identification of MIMO Hammerstein models using least squares support vector machines
»
Refined instrumental variable methods for identifying hammerstein models operating in clos...
»
On the Identification of Hammerstein Systems Having Saturationlike Functions with Positive...
»
Semiparametric identification of Hammerstein systems using input reconstruction and a sing...
»
Identification and compensation of WienerHammerstein systems with feedback
»
Convex relaxation approach to the identification of the WienerHammerstein model
»
Identification of Hammerstein Systems with Quantized Observations
»
HammersteinWiener system estimator initialization
»
Computational Algorithms for Wavelet Identification of Nonlinearities in Hammerstein Syste...
more »
Post Info
More Details (n/a)
Added
14 May 2011
Updated
14 May 2011
Type
Journal
Year
2011
Where
DSP
Authors
Feng Ding, Peter Xiaoping Liu, Guangjun Liu
Comments
(0)
Researcher Info
Emerging Technology Study Group
Computer Vision