Claims
- 1. A method for reducing noise in a time series signal, comprising:
modeling generation of a primary signal by a dynamic system with a continuum of states, the primary signal including generic noise; adding a secondary signal to the primary signal to form a combined signal, the secondary signal including time series data; estimating the generic noise in the combined signal using the dynamic system; and removing the estimated generic noise from the combined signal to recover the secondary signal.
- 2. The method of claim 1 wherein the generic noise includes stationary and non-stationary noise.
- 3. The method of claim 1 wherein the secondary signal is an acoustic signal.
- 4. The method of claim 3 wherein the acoustic signal is a speech signal.
- 6. The method of claim 1 wherein the dynamic system includes a continuum of states.
- 7. The method of claim 1 further comprising:
sampling the continuum of states at time steps to obtain an estimated distribution of the primary signal.
- 8. The method of claim 7 further comprising:
locally linearizing a non-linear relationship between the primary signal and the combined signal around each sample of the combined signal.
- 9. The method of claim 1 wherein the estimating and removing are performed in on-line during a single pass on the combined signal.
- 10. The method of claim 1 wherein the dynamic system is represented in a closed form.
- 11. The method of claim 4 wherein the secondary signal is assumed to corrupt the primary generic noise signal.
- 12. The method of claim 1 wherein the dynamic system uses linear Markovian dynamics.
- 13. The method of claim 12 further comprising:
learning first-order parameters of the Markovian dynamics from training data.
- 14. The method of claim 1 wherein the dynamic system is modeled by a state equation
- 15. The method of claim 14 wherein log-spectral vectors of the primary signal are expressed as
- 16. The method of claim 9 further comprising:
performing the estimating is done in real-time.
- 17. The method of claim 1 wherein the dynamic system uses non-linear Markovian dynamics.
- 18. A method for reducing noise in a combined signal, the combined signal including time series data and generic noise, comprising:
estimating the generic noise in the combined signal using a dynamic system modeling the generic noise, the dynamic system having a continuum of states; and removing the estimated generic noise from the combined signal to recover the time series data.
- 19. The method of claim 18 wherein the generic noise includes stationary and non-stationary noise.
- 20. A system for reducing noise in a time series signal, comprising:
a dynamic system configured to model a generation of a primary signal including generic noise, the dynamic system having a continuum of states; means for adding a secondary signal to the primary signal to form a combined signal, the secondary signal including time series data; means for estimating the generic noise in the combined signal using the dynamic system; and means for removing the estimated generic noise from the combined signal to recover the secondary signal.
STATEMENT OF GOVERNMENT INTEREST
[0001] The invention described herein may be manufactured and used by or for the Government of the United States of America for governmental purposes without the payment of any royalties thereon or therefor.