Title :
A blind equalization algorithm based on bilinear recurrent neural network
Author :
Xiaoqin, Zhang ; Huakui, Wang ; Liyi, Zhang ; Xiong, Zhang
Author_Institution :
Coll. of Inf. Eng., Taiyuan Univ. of Technol., China
Abstract :
In this paper, we propose a new blind equalization algorithm based on bilinear recurrent neural network. In the first part, a new transmission function and cost function is designed for the neural network. In the second part, the new neural network is used to blind equalization algorithm. Results of the simulation show that our algorithm can obtains better convergence performance and lower bit error rate (BER) than traditional constant modulus algorithm (CMA).
Keywords :
blind equalisers; convergence; digital simulation; error statistics; iterative methods; recurrent neural nets; BER; CMA; bilinear recurrent neural network; blind equalization algorithm; constant modulus algorithm; convergence performance; cost function; digital simulation; iterative methods; lower bit error rate; transmission function; Bit error rate; Blind equalizers; Convergence; Cost function; Educational institutions; Electronic mail; Feedforward systems; Modems; Neural networks; Recurrent neural networks;
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
DOI :
10.1109/WCICA.2004.1341927
