標題: Programmable switched-capacitor neural network for MVDR beamforming
作者: Yang, WH
Chang, PR
交大名義發表
電信工程研究所
National Chiao Tung University
Institute of Communications Engineering
公開日期: 1-一月-1996
摘要: In this paper, a real-time adaptive antenna array based on a neural network approach is presented, Since an array operating in a nonstationary environment requires a programmable synaptic weight matrix for the neural network, the switched-capacitor (SC) circuits with the capability of programmability and reconfigurability is conducted to implement the neural-based adaptive array. Moreover, the SC techniques can directly implement the neural network with less chip area and provide the ratio of SC-equivalent resistors with accuracy of 0.1 percent. Programming of the switched-capacitor values could be made by allocating each synaptic weight to a set of parallel capacitors with values in a digitally programmable capacitor array (PCA), A relatively wide range of values (5 to 10 binary bits resolution) can be realized for each synaptic weight. A simulation tool called SWITCAP is used to verify the validity and performance of the proposed implementation, Experimental results show that the computation time of solving a linear array of 5 elements is about 0.1 ns for 1 ns time constant and is independent of signal power levels.
URI: http://dx.doi.org/10.1109/48.485203
http://hdl.handle.net/11536/1548
ISSN: 0364-9059
DOI: 10.1109/48.485203
期刊: IEEE JOURNAL OF OCEANIC ENGINEERING
Volume: 21
Issue: 1
起始頁: 77
結束頁: 84
顯示於類別:期刊論文


文件中的檔案:

  1. A1996TY86900007.pdf