Compound noise separation in digital circuits using blind source separation

被引:2
|
作者
Xu, Jingye [1 ]
Nigam, Vivek P. [1 ]
Roy, Abinash [1 ]
Chowdhury, Masud H. [1 ]
机构
[1] Univ Illinois, Dept Elect & Comp Engn, Chicago, IL 60607 USA
关键词
adaptive signal processing; blind source separation; compound noise separation; integrated circuit noise; independent component analysis;
D O I
10.1016/j.mejo.2008.01.070
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Analysis of individual noise sources in pre-nanometer circuits cannot take into account the evolving reality of multiple noise sources interacting with each other. Noise measurement made at an evaluation node will reflect the cumulative effect of all the active noise sources, while individual and relative severity of various noise sources will determine what types of remedial steps can be taken, pressing the need for development of algorithms that can analyze the contributions of different noise sources when a noise measurement is available. This paper addresses the cocktail-party problem inside integrated circuits with multiple noise sources. It presents a method to extract the time characteristics of individual noise source from the measured compound voltage in order to study the contribution and properties of each source. This extraction is facilitated by application of blind source separation technique, which is based on the assumption of statistical independence of various noise sources over time. The estimated noise sources can aid in performing timing and spectral analysis, and yield better circuit design techniques. (c) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1083 / 1092
页数:10
相关论文
共 50 条
  • [1] Compound noise analysis in digital circuits using blind source separation
    Nigam, Vivek P.
    Chowdhury, Masud H.
    Priemer, Roland
    2006 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOLS 1-11, PROCEEDINGS, 2006, : 1929 - +
  • [2] Noise Source Separation based on the Blind Source Separation
    Yang, Yang
    Li, Zuoli
    Wang, Xiuqin
    Zhang, Di
    2011 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6, 2011, : 2236 - +
  • [3] Separation of individual noise sources from compound noise measurements in digital circuits
    Nigam, Vivek P.
    Chowdhury, Masud H.
    Priemer, Roland
    2006 IEEE ASIA PACIFIC CONFERENCE ON CIRCUITS AND SYSTEMS, 2006, : 1603 - +
  • [4] Removal of EEG noise and artifact using blind source separation
    Fitzgibbon, S. P.
    Powers, D. M. W.
    Pope, K. J.
    Clark, C. R.
    JOURNAL OF CLINICAL NEUROPHYSIOLOGY, 2007, 24 (03) : 232 - 243
  • [5] Blind source separation with convolutive noise cancellation
    W. Kasprzak
    A. Cichocki
    S. Amari
    Neural Computing & Applications, 1997, 6 : 127 - 141
  • [6] Blind source separation with convolutive noise cancellation
    Kasprzak, W
    Cichocki, A
    Amari, S
    NEURAL COMPUTING & APPLICATIONS, 1997, 6 (03): : 127 - 141
  • [7] Blind Source Separation of Interfering Signals in Analog Circuits
    Li Hao
    Chen Zhiyong
    Zhang Ruixue
    Dong Yonggui
    PROCEEDINGS OF 2013 2ND INTERNATIONAL CONFERENCE ON MEASUREMENT, INFORMATION AND CONTROL (ICMIC 2013), VOLS 1 & 2, 2013, : 462 - 466
  • [8] Blind Source Separation for digital data protection
    Doukas, Nikolaos
    Karadimas, Nikolaos V.
    MATHEMATICAL METHODS, COMPUTATIONAL TECHNIQUES, NON-LINEAR SYSTEMS, INTELLIGENT SYSTEMS, 2008, : 503 - +
  • [9] Noise cancellation of ultrasonic NDE signals using blind source separation
    Qingkun Liu
    Peiwen Que
    Huawei Guo
    Shoupeng Song
    Russian Journal of Nondestructive Testing, 2006, 42 : 63 - 68
  • [10] Noise cancellation of ultrasonic NDE signals using blind source separation
    Liu, QK
    Que, PW
    Guo, HW
    Song, SP
    RUSSIAN JOURNAL OF NONDESTRUCTIVE TESTING, 2006, 42 (01) : 63 - 68