BLIND SOURCE-SEPARATION IN MIXED-SIGNAL VLSI

被引:0
作者
Valenzuela, Waldo [1 ]
Carvajal, Gonzalo [1 ]
Figueroa, Miguel [1 ]
机构
[1] Univ Concepcion, Dept Elect Engn, Concepcion, Chile
关键词
Independent components analysis; InfoMax; Kurtosis; mixed-signal VLSI; low-power CMOS; on-chip learning; adaptive silicon circuits; INDEPENDENT COMPONENT ANALYSIS; ALGORITHMS; INFOMAX;
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
This paper describes an implementation of the Kurtosis and InfoMax algorithms for an independent components analysis in mixed-signal CMOS. Our design uses on-chip calibration techniques and local adaptation to compensate for the effect of device mismatch in arithmetic blocks and analog memory cells. We use our design to perform two-input blind source-separation on mixtures of audio signals and mixtures of EEG signals. Our experiments show that the hardware implementation of InfoMax consistently separates the signals within a normalized reconstruction error of less than 10%, while the reconstruction error of Kurtosis varies between 25% and 60%, due to its higher sensitivity to device mismatch and input statistics. Each circuit has a settling time of 8 mu s, occupies a die area of 0.016-0.022 mm(2) and dissipates 15-20 mu W of power.
引用
收藏
页码:641 / 656
页数:16
相关论文
共 22 条
[1]   AN INFORMATION MAXIMIZATION APPROACH TO BLIND SEPARATION AND BLIND DECONVOLUTION [J].
BELL, AJ ;
SEJNOWSKI, TJ .
NEURAL COMPUTATION, 1995, 7 (06) :1129-1159
[2]   The ''independent components'' of natural scenes are edge filters [J].
Bell, AJ ;
Sejnowski, TJ .
VISION RESEARCH, 1997, 37 (23) :3327-3338
[3]   Infomax and maximum likelihood for blind source separation [J].
Cardoso, JF .
IEEE SIGNAL PROCESSING LETTERS, 1997, 4 (04) :112-114
[4]  
CARVAJAL G, 2008, ADV NEURAL INFORM PR, V20
[5]  
CARVAJAL G, 2000, INT C ART NEUR NETW, P963
[6]   INDEPENDENT COMPONENT ANALYSIS, A NEW CONCEPT [J].
COMON, P .
SIGNAL PROCESSING, 1994, 36 (03) :287-314
[7]   EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis [J].
Delorme, A ;
Makeig, S .
JOURNAL OF NEUROSCIENCE METHODS, 2004, 134 (01) :9-21
[8]  
DIAGONALIZATION C, 2004, IEEE T SIGNAL PROCES, V52, P1250
[9]  
Figueroa M., 2005, ADV NEURAL INFORM PR, V17
[10]  
HAIRAI Y, 2000, P IEEE INNS ENNS INT, V2, P65