Title :
Center reduction algorithm for the modified probabilistic neural network equalizer
Author :
Young, James P. ; Zaknich, Anthony ; Attkiouzel, Y.
Author_Institution :
Dept. of Electr. & Electron. Eng., Western Australia Univ., Nedlands, WA, Australia
Abstract :
The applicability of the modified probabilistic neural network to channel equalization can be severely limited by the size of the network. The size of the network grows exponentially with the order of the channel and the dimension of the input vectors. As a result, the standard network is practical only for low order channels with small input alphabet size. An algorithm is proposed to alleviate such an undesirable constraint by finding a much smaller network representation with a similar decision surface
Keywords :
digital communication; equalisers; learning (artificial intelligence); neural nets; telecommunication channels; telecommunication computing; center reduction algorithm; channel equalization; clustering; digital communication; equalizer; learning; probabilistic neural network; probability; Adaptive filters; Bayesian methods; Bit error rate; Convergence; Digital communication; Digital filters; Equalizers; Neural networks; Nonlinear filters; Recurrent neural networks;
Conference_Titel :
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-7044-9
DOI :
10.1109/IJCNN.2001.938465
