Ultra-wideband beamforming by using a complex-valued spatio-temporal neural network

被引：0
|
作者：
Suksmono, AB
Hirose, A
机构：
[1] Inst Teknol Bandung, Dept Elect Engn, Bandung, Indonesia
[2] Univ Tokyo, Dept Elect & Elect Engn, Tokyo, Japan
来源：
NEURAL INFORMATION PROCESSING | 2004年 / 3316卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We propose an ultra-wideband (UWB) beamforming technique by using a spatio-temporal complex-valued multilayer neural network (ST-CVMLNN). The complex-valued backpropagation through time (CV-BM) is employed as a learning algorithm. The system is evaluated with an ultra-wideband monocycle signal. Preliminary simulation results in suppression of UWB; interferer and in steering for desired UWB signal, demonstrating the applicability of the proposed system.
引用
收藏
页码：104 / 109
页数：6
相关论文
共 50 条
  • [21] Mask-based Beamforming Using Complex-valued Neural Network for Recognition of Spatial Target Speech
    Hayakawa, Daichi
    Kagoshima, Takehiko
    Fujimura, Hiroshi
    2021 ASIA-PACIFIC SIGNAL AND INFORMATION PROCESSING ASSOCIATION ANNUAL SUMMIT AND CONFERENCE (APSIPA ASC), 2021, : 23 - 29
  • [22] Ultra-Wideband Spatio-Temporal Channel Sounding with Use of an OFDM Signal in the Presence of Narrowband Interference
    Sugizaki, Daisuke
    Iwakiri, Naohiko
    Kobayashi, Takehiko
    2010 4TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND COMMUNICATION SYSTEMS (ICSPCS), 2010,
  • [23] Adaptive Beamforming using Complex-valued Radial Basis Function Neural Networks
    Savitha, R.
    Vigneswaran, S.
    Suresh, S.
    Sundararajan, N.
    TENCON 2009 - 2009 IEEE REGION 10 CONFERENCE, VOLS 1-4, 2009, : 1133 - +
  • [24] Fast and robust adaptive beamforming method based on complex-valued RBF neural network
    Li, Yuqing
    Yang, Xiaopeng
    Liu, Feifeng
    JOURNAL OF ENGINEERING-JOE, 2019, 2019 (19): : 5917 - 5921
  • [25] MOTION LEARNING USING SPATIO-TEMPORAL NEURAL NETWORK
    Yusoff, Nooraini
    Kabir-Ahmad, Farzana
    Jemili, Mohamad-Farif
    JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGY-MALAYSIA, 2020, 19 (02): : 207 - 223
  • [26] Surface classification using ANN and complex-valued neural network
    Prashanth, A
    Kalra, PK
    Vyas, NS
    ICONIP'02: PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON NEURAL INFORMATION PROCESSING: COMPUTATIONAL INTELLIGENCE FOR THE E-AGE, 2002, : 1094 - 1098
  • [27] Channel equalization using complex-valued recurrent neural network
    Wang, XQ
    Lin, H
    Lu, JM
    Yahagi, T
    2001 INTERNATIONAL CONFERENCES ON INFO-TECH AND INFO-NET PROCEEDINGS, CONFERENCE A-G: INFO-TECH & INFO-NET: A KEY TO BETTER LIFE, 2001, : C498 - C503
  • [28] Comparison of complex-valued neural network and fuzzy clustering complex-valued neural network for load-flow analysis
    Ceylan, Murat
    Cetinkaya, Nurettin
    Ceylan, Rahime
    Ozbay, Yuksel
    ARTIFICIAL INTELLIGENCE AND NEURAL NETWORKS, 2006, 3949 : 92 - 99
  • [29] Direction-of-Arrival Estimation of Ultra-Wideband Signals in Narrowband Interference Environment Based on Power Inversion and Complex-Valued Neural Networks
    Kikuta, Kazutaka
    Hirose, Akira
    NEURAL PROCESSING LETTERS, 2018, 47 (03) : 921 - 933
  • [30] Direction-of-Arrival Estimation of Ultra-Wideband Signals in Narrowband Interference Environment Based on Power Inversion and Complex-Valued Neural Networks
    Kazutaka Kikuta
    Akira Hirose
    Neural Processing Letters, 2018, 47 : 921 - 933
12345