Data processing: measuring – calibrating – or testing – Measurement system – Measured signal processing
Reexamination Certificate
2005-09-13
2005-09-13
Mehta, Bhavesh M. (Department: 2625)
Data processing: measuring, calibrating, or testing
Measurement system
Measured signal processing
C702S197000, C382S261000, C382S265000, C382S276000, C348S610000
Reexamination Certificate
active
06944579
ABSTRACT:
Signals are separated by introducing a function having a monotonously increasing characteristic like an exponential type function as a cost function, and applying an adaptive algorithm that minimizes that cost function in terms of a signal separation matrix. That is, there is provided a signal processing apparatus that separates and outputs an original signal from the observed signalx(t), in which multiple multidimensional signals are mixed, wherein the nonlinear function21is operated on an input observed signalx(t) and an estimated separation matrixW(t−1) estimated at a previous cycle. Then, an error signale(t) is calculated22based ony(t) formed by this nonlinear function21, the estimated separation matrixW(t−1) estimated at the previous cycle, and the observed signalx(t) at that time. Then, based on the calculated error signale(t), the update of the separation matrixW(t) at that time is performed23such that consideration weight is increased when estimation errors are large using the cost function having a monotonously increasing characteristic.
REFERENCES:
patent: 5261007 (1993-11-01), Hirsch
patent: 5706402 (1998-01-01), Bell
patent: 5721694 (1998-02-01), Graupe
patent: 5999956 (1999-12-01), Deville
patent: 6026183 (2000-02-01), Talluri et al.
patent: 6614930 (2003-09-01), Agnihotri et al.
patent: 06-021838 (1994-01-01), None
patent: 2000-242624 (2000-09-01), None
patent: 2002-528778 (2000-09-01), None
Cardoso et al. (“Equivalent Adaptive Source Separation,” IEEE Trans. Signal Processing, vol. 44, No. 12, Dec. 1996, pp. 3017-3030).
Hassibi et al. (“H-Infinity Optimality of the LMS Algorithm,” IEEE Trans. Signal Processing, vol. 44, No. 2, Feb. 1996, pp. 267-280).
“Information Capacity of Channels With Partially Unknown Noise. I. Finite-Dimensional Channels”, C.R. Baker et al., 1996, 18 pages.
“H∞ Filtering for Noise Reduction Using a Total Least Squares Estimation Approach”, Jun'ya Shimizu et al., 1998, 4 pages.
“Least-Squares Methods for Blind Source Separation Based on Nonlinear PCA”, Pajunen et al., International Journal of Neural Systems, vol. 8, Nos. 5 & 6, 1997, pp. 601-612.
“Equivariant Adaptive Source Separation”, Cardoso et al., IEEE Transactions on Signal Processing, vol. 44, No. 12, 1996, pp. 3017-3030.
“Blind Separation of Sources, Part I: An Adaptive Algorithm Based on Neuromimetic Architecture”, Jutten et al., Signal Processing vol. 24, No. 1, 1991, pp. 1-10.
“Stochastic ICA Contrast Maximisation Using OJA'S Nonlinear PCA Algorithm”, Girolami et al., International Journal of Neural Systems, vol. 8, No. 5 & 6, 1997, pp. 661-678.
International Business Machines - Corporation
Percello Louis
Perman & Green LLP
LandOfFree
SIGNAL SEPARATION METHOD, SIGNAL PROCESSING APPARATUS, IMAGE... does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with SIGNAL SEPARATION METHOD, SIGNAL PROCESSING APPARATUS, IMAGE..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and SIGNAL SEPARATION METHOD, SIGNAL PROCESSING APPARATUS, IMAGE... will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-3367353