DocumentCode :
3594455
Title :
The iterative identification method for hammerstein nonlinear channel
Author :
Rui Su ; Bin Wang ; Shigang Liu
fYear :
2014
Firstpage :
67
Lastpage :
72
Abstract :
This paper is concerned with the iteration identification algorithm for Hammerstein model with complex-valued input for the fact that the existing algorithms are not valid for complex input. Based on the stochastic gradient algorithm, the extended stochastic gradient algorithm is proposed by defining new cost function for complex input. The extended hierarchical multi-innovation stochastic gradient algorithm is proposed by introducing multi-innovation identification theory and hierarchical principle to the extended stochastic gradient algorithm. Experimental simulations show that the extended hierarchical multi-innovation stochastic gradient algorithm has better performance than the extended stochastic gradient algorithm at the expense of computational complexity.
Keywords :
gradient methods; identification; iterative methods; stochastic processes; wireless channels; Hammerstein nonlinear channel; complex-valued input; computational complexity; cost function; extended hierarchical multiinnovation stochastic gradient algorithm; iterative identification method; multiinnovation identification theory; Hammerstein Model; Hierarchical; Iterative Identification; Multi-Innovation; Stochastic Gradient Algorithm;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Wireless Communications, Networking and Mobile Computing (WiCOM 2014), 10th International Conference on
Print_ISBN :
978-1-84919-845-5
Type :
conf
DOI :
10.1049/ic.2014.0075
Filename :
7129603
Link To Document :
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