Cohen M.H. & Andreou A.G. 1992. Current-Mode Subthreshold MOS Implementation of the Herault-Jutten Autoadaptive Network, IEEE J. Solid-State Circuits vol. 27, 5, 714-727 Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
Gradient Flow Broadband Beamforming And Source Separation - Stanacevic, Cauwenberghs.. (2001) (Correct)
....problem of separating delayed mixtures into a simpler problem of separating instantaneous mixtures of spatial and temporal gradients of the wave signals. This formulation is equivalent to that of standard ICA, and a number of approaches exist for such blind separation, some utilizing VLSI hardware [15]. The mixing coefficients obtained from ICA directly yield the angles of the incoming waves. Therefore our method can be seen as a broadband beamforming extension to static ICA, performing at once blind separation and localization of traveling waves. In what follows we review the principle of ....
M.H. Cohen and A.G. Andreou, "Current-mode subthreshold mos implementation of herault-jutten autoadaptive network, " IEEE J. Solid-State Circuits, vol. 27, pp. 714--727, May 1992.
Implementation of Infomax ICA Algorithm with Analog CMOS Circuits - Cho, Lee (2001) (Correct)
....in massively parallel analog CMOS circuits may be the best engineering approach to solve such as applications such as audio and video signal processing [5] ICA using Herault Jutten algorithm was realized by Cohen and Andreou. However, the convergence is sensitive to the mixing condition [7]. The improved infomax ICA algorithm incorporates natural gradient, which greatly improves the convergence. It is more practical and effective algorithm for a variety of real world problems [6] In this paper, we present a new approach to the analog CMOS implementation of ICA using infomax theory ....
Marc H. Cohen & Andreas G. Andreou. (1992), CurrentMode Subthreshold MOS Implementation of the HeraultJutten Autoadaptive Network, IEEE Journal of Solid-State Circuits 26 (5):714-727. 73
Blind Separation of Sources: Methods, Assumptions and.. - Mansour, Barros, Ohnishi (2000) (1 citation) (Correct)
....used also in some visual image communication systems [159] 17. To separate mixing images, Cichoski et al. 160] propsed a multi layer neural networks with a local adaptive learning rule for blind separation of source signals. 18. Some algorithms were implemented using digital circuits [161] [162] or VLSI [163] 6. Conclusion In this paper, we presented a survey of source separation problem, applications and the major methods and approaches. To conclude our paper, we must stress that in most studies three assumptions are fundamentals: The first two assumptions concern the sources: they ....
M. H. Cohen and A. G. Andreou, "Current-mode subthreshold mos implementation of the H'erault-Jutten autoadaptative network," IEEE Signal Processing Magazine, vol. 27, no. 5, May 1992.
An Information-Maximisation Approachto Blind Separation and.. - Anthony Bell And (1995) (149 citations) (Correct)
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Cohen M.H. & Andreou A.G. 1992. Current-Mode Subthreshold MOS Implementation of the Herault-Jutten Autoadaptive Network, IEEE J. Solid-State Circuits vol. 27, 5, 714-727
An Information-Maximization Approach to Blind Separation and.. - Bell, Sejnowski (1995) (448 citations) (Correct)
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Cohen M.H. & Andreou A.G. 1992. Current-Mode Subthreshold MOS Implementation of the Herault-Jutten Autoadaptive Network, IEEE J. Solid-State Circuits vol. 27, 5, 714-727
A Unifying Information-theoretic Framework for.. - Lee, Girolami, Bell, .. (1999) (47 citations) (Correct)
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Cohen M.H. and Andreou A.G. 1992. Current-Mode Subthreshold MOS Implementation of the Herault-Jutten Autoadaptive Network, IEEE J. Solid-State Circuits 27(5), 714-727
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