Source separation based processing for integrated Hall sensor arrays

Integrated arrays of Hall-type magnetic sensors are generally subject to significant crosstalk due to poor spatial selectivity of very closely spaced sensors. In this paper, we explore blind source separation as a signal processing technique to unmix a number of magnetic sources that impinge on the array. The processing consists of two stages: the first one estimates the source number and projects the observations on the signal subspace; the second stage is a source separation algorithm. Experimental results from a silicon array of Hall sensors, interfaced with a DSP, demonstrate real-time separation of two magnetic sources even under ill-conditioning of the mixing matrix.

[1]  L. Almeida,et al.  ICA of linear and nonlinear mixtures based on mutual information , 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).

[2]  Eric Moulines,et al.  A blind source separation technique using second-order statistics , 1997, IEEE Trans. Signal Process..

[3]  Radivoje Popovic,et al.  Single-chip 3-D silicon Hall sensor , 2000 .

[4]  Jutten,et al.  1 - Une solution neuromimétique au problème de séparation de sources , 1988 .

[5]  Fathi M. A. Salam,et al.  Test results of a chip for the separation of mixed and filtered signals , 1995 .

[6]  Radivoje Popovic,et al.  Hall effect devices , 1991 .

[7]  J. Gardner,et al.  Microsensors: Principles and Applications , 1994 .

[8]  E. Oja,et al.  Independent Component Analysis , 2013 .

[9]  Christian Jutten,et al.  Subspace estimation by hierarchical neural PCA: analog/digital implementation constraints , 2000, 2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353).

[10]  Gabriele D'Antona,et al.  Processing magnetic sensor array data for AC current measurement in multiconductor systems , 2001, IEEE Trans. Instrum. Meas..

[11]  S. Middelhoek,et al.  AUTOCALIBRATION OF SILICON HALL DEVICES , 1996 .

[12]  Andrzej Cichocki,et al.  Equivariant Nonstationary Source Separation , 2002 .

[13]  Eric A. Vittoz,et al.  CMOS Integration of Herault-Jutten Cells for Separation of Sources , 1989, Analog VLSI Implementation of Neural Systems.

[14]  Andrzej Cichocki,et al.  Robust estimation of principal components by using neural network learning algorithms , 1993 .

[15]  Erkki Oja,et al.  Applications of neural blind separation to signal and image processing , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[16]  Simone G. O. Fiori,et al.  Hybrid independent component analysis by adaptive LUT activation function neurons , 2002, Neural Networks.

[17]  Barak A. Pearlmutter,et al.  Blind source separation of multichannel neuromagnetic responses , 2000, Neurocomputing.

[18]  Javad Frounchi,et al.  Reference magnetic actuator for self-calibration of a very small Hall sensor array , 2002 .

[19]  Christian Jutten,et al.  Entropy Optimization - Application to Blind Source Separation , 1997, ICANN.

[20]  Christian Jutten,et al.  Detection de grandeurs primitives dans un message composite par une architecture de calcul neuromime , 1985 .

[21]  Christian Jutten,et al.  Neural Network Based Processing for Smart Sensors Arrays , 1997, ICANN.

[22]  Yannick Deville,et al.  Optimization of the asymptotic performance of time-domain convolutive source separation algorithms , 1997, ESANN.

[23]  Jean-Francois Cardoso,et al.  Blind signal separation: statistical principles , 1998, Proc. IEEE.

[24]  Christian Jutten,et al.  Blind separation of sources, part I: An adaptive algorithm based on neuromimetic architecture , 1991, Signal Process..

[25]  Shun-ichi Amari,et al.  Adaptive blind signal processing-neural network approaches , 1998, Proc. IEEE.

[26]  S.Y. Kung,et al.  Adaptive Principal component EXtraction (APEX) and applications , 1994, IEEE Trans. Signal Process..

[27]  Andreas G. Andreou,et al.  Current-mode subthreshold MOS implementation of the Herault-Jutten autoadaptive network , 1992 .

[28]  Pierre Comon,et al.  Independent component analysis, A new concept? , 1994, Signal Process..

[29]  Dinh-Tuan Pham,et al.  Blind separation of instantaneous mixtures of nonstationary sources , 2001, IEEE Trans. Signal Process..

[30]  Andrzej Cichocki,et al.  Information-theoretic approach to blind separation of sources in non-linear mixture , 1998, Signal Process..

[31]  Andreas Ziehe,et al.  Adaptive On-line Learning in Changing Environments , 1996, NIPS.

[32]  Christian Jutten,et al.  Wavelet denoising for highly noisy source separation , 2002, 2002 IEEE International Symposium on Circuits and Systems. Proceedings (Cat. No.02CH37353).

[33]  C. Jutten,et al.  Blind source separation processing for intelligent sensor microsystems , 1999, IECON'99. Conference Proceedings. 25th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.99CH37029).

[34]  Richard M. Everson,et al.  Independent Component Analysis: Principles and Practice , 2001 .

[35]  Gert van der Horn,et al.  Integrated Smart Sensors: Design and Calibration , 1997 .

[36]  Christian Jutten,et al.  Source separation in post-nonlinear mixtures , 1999, IEEE Trans. Signal Process..

[37]  R. Liu,et al.  AMUSE: a new blind identification algorithm , 1990, IEEE International Symposium on Circuits and Systems.

[38]  Terrence J. Sejnowski,et al.  An Information-Maximization Approach to Blind Separation and Blind Deconvolution , 1995, Neural Computation.

[39]  Shun-ichi Amari,et al.  Comparison of ICA/BSS algorithms for noisy data , 2000 .

[40]  Jean-François Cardoso,et al.  Equivariant adaptive source separation , 1996, IEEE Trans. Signal Process..

[41]  Randy Frank Understanding Smart Sensors , 1995 .

[42]  Jean-Louis Lacoume,et al.  Separation of independent sources from correlated inputs , 1992, IEEE Trans. Signal Process..

[43]  Erkki Oja,et al.  An Experimental Comparison of Neural Algorithms for Independent Component Analysis and Blind Separation , 1999, Int. J. Neural Syst..

[44]  Erkki Oja,et al.  Independence: a new criterion for the analysis of the electromagnetic fields in the global brain? , 2000, Neural Networks.

[45]  C.P.O Treutler,et al.  Magnetic sensors for automotive applications , 2001 .