The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON COMMUNICATIONS
Transactions ID Number: 29-349
Full Name: Chia-Hsin Cheng
Position: Assistant Professor
Age: ON
Sex: Male
Address: No. 64, Wunhua Rd., Huwei, Yunlin 632, Taiwan
Country: TAIWAN
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E-mail address: chcheng@nfu.edu.tw
Other E-mails: chcheng@cyut.edu.tw
Title of the Paper: Hopfield Neural Network for UWB Multiuser Detection
Authors as they appear in the Paper: Chia-hsin Cheng, Guo-jun Wen, and Yung-fa Huang
Email addresses of all the authors: chcheng@nfu.edu.tw,d9042010@ccu.edu.tw,yfahuang@cyut.edu.tw
Number of paper pages: 10
Abstract: The Hopfield neural network (HNN) is introduced in the paper and is proposed as an effective multiuser detection in direct sequence-ultra-wideband (DS-UWB) systems. It can approximate to maximum likelihood (ML) detector by mathematical analysis. According to the HNN-based technique, the computer simulation results show that they have good performances and much lower computational complexity in a multiuser environment.
Keywords: Maximum likelihood, Neural network, Hopfield.
EXTENSION of the file: .doc
Special (Invited) Session: HNN-based Multiuser Detection in UWB Systems (The 8th WSEAS Int. Conf. on ACACOS '09)
Organizer of the Session: 613-364 (The 8th WSEAS Int. Conf. on ACACOS '09)
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