IP Library Granted Patent US 10,128,820
Granted Patent B2
US 10,128,820 · App. 15/817,906 · Granted Nov 13, 2018

Cognitive signal processor for simultaneous denoising and blind source separation

Inventors: Peter Petre (Oak Park, CA); Bryan H. Fong (Los Angeles, CA); Shankar R. Rao (Agoura Hills, CA); Charles E. Martin (Thousand Oaks, CA)
Assignee: HRL Laboratories, LLC
H03H21/0025G06K9/0057G06K9/624G06N3/0445H04B1/719H04B1/71632H03H2021/0034
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Quick Facts
Patent No.
US 10,128,820
App. No.
15/817,906
Granted
Nov 13, 2018
Kind
B2
Abstract

Described is a cognitive signal processor for signal denoising and blind source separation. During operation, the cognitive signal processor receives a mixture signal that comprises a plurality of source signals. A denoised reservoir state signal is generated by mapping the mixture signal to a dynamic reservoir to perform signal denoising. At least one separated source signal is identified by adaptively filtering the denoised reservoir state signal.

Claims (75)

1. A cognitive signal processor for signal denoising and blind source separation, the cognitive signal processor comprising:

one or more processors configured to perform operations of:

receiving a mixture signal that comprises a plurality of source signals;

generating a denoised reservoir state signal by mapping the mixture signal to a dynamic reservoir to perform signal denoising; and

identifying at least one separated source signal by adaptively filtering the denoised reservoir state signal;

wherein adaptively filtering the denoised reservoir state signal further comprises operations of:

detecting that a particular frequency band possesses a pulse;

switching a first filter to a tracking state with a center frequency equal to a resonant frequency of a reservoir state corresponding to the particular frequency band; and

setting the center frequency of the first filter as a protected region to prevent other filters within a bank of filters from sharing the center frequency.

2. The cognitive signal processor as set forth in claim 1 , wherein filtering the denoised reservoir state signal is performed with a bank of filters.

3. The cognitive signal processor as set forth in claim 2 , further comprising an operation of controlling the bank of filters to cause each filter within the bank of filters to filter a unique waveform.

4. The cognitive signal processor as set forth in claim 3 , wherein each filter has an adaptable center frequency.

5. The cognitive signal processor as set forth in claim 1 , wherein adaptively filtering the denoised reservoir state signal further comprises operations of:

switching the first filter to a holding state if the first filter loses the pulse of the particular frequency band;

maintaining the first filter in the holding state for a fixed period of time while maintaining the protected region;

if during the fixed period of time the pulse returns, switching the first filter to the tracking state, otherwise switching the first filter to an inactive state and removing the protected region.

6. The cognitive signal processor as set forth in claim 1 , wherein generating the denoised reservoir state signal further comprises delay embedding the reservoir state signal to generate a reservoir state history.

7. The cognitive signal processor as set forth in claim 1 , wherein generating the denoised reservoir state signal further comprises generating a predicted input signal a small-time step ahead of the mixture signal, wherein an error between the predicted input signal and mixture signal is used to update output weights of the dynamic reservoir.

8. The cognitive signal processor as set forth in claim 1 , wherein generating the denoised reservoir state signal is performed with a dynamic reservoir implemented in analog hardware by satisfying a set of ordinary differential equations.

9. A cognitive signal processor for signal denoising and blind source separation, the cognitive signal processor comprising:

one or more processors configured to perform operations of:

receiving a mixture signal that comprises a plurality of source signals;

generating a denoised reservoir state signal by mapping the mixture signal to a dynamic reservoir to perform signal denoising; and

identifying at least one separated source signal by adaptively filtering the denoised reservoir state signal;

wherein generating the denoised reservoir state signal is performed with a dynamic reservoir implemented in software or digital hardware by converting a set of ordinary differential equations to delay difference equations.

10. A computer program product for signal denoising and blind source separation, the computer program product comprising:

a non-transitory computer-readable medium having executable instructions encoded thereon, such that upon execution of the instructions by one or more processors, the one or more processors perform operations of:

receiving a mixture signal that comprises a plurality of source signals;

generating a denoised reservoir state signal by mapping the mixture signal to a dynamic reservoir to perform signal denoising; and

identifying at least one separated source signal by adaptively filtering the denoised reservoir state signal;

wherein adaptively filtering the denoised reservoir state signal further comprises operations of:

detecting that a particular frequency band possesses a pulse;

switching a first filter to a tracking state with a center frequency equal to a resonant frequency of a reservoir state corresponding to the particular frequency band; and

setting the center frequency of the first filter as a protected region to prevent other filters within a bank of filters from sharing the center frequency.

11. The computer program product as set forth in claim 10 , wherein filtering the denoised reservoir state signal is performed with a bank of filters.

12. The computer program product as set forth in claim 11 , further comprising an operation of controlling the bank of filters to cause each filter within the bank of filters to filter a unique waveform.

13. The computer program product as set forth in claim 12 , wherein each filter has an adaptable center frequency.

14. The computer program product as set forth in claim 10 , wherein adaptively filtering the denoised reservoir state signal further comprises operations of:

switching the first filter to a holding state if the first filter loses the pulse of the particular frequency band;

maintaining the first filter in the holding state for a fixed period of time while maintaining the protected region;

if during the fixed period of time the pulse returns, switching the first filter to the tracking state, otherwise switching the first filter to an inactive state and removing the protected region.

15. The computer program product as set forth in claim 10 , wherein generating the denoised reservoir state signal further comprises delay embedding the reservoir state signal to generate a reservoir state history.

16. The computer program product as set forth in claim 10 , wherein generating the denoised reservoir state signal further comprises generating a predicted input signal a small-time step ahead of the mixture signal, wherein an error between the predicted input signal and mixture signal is used to update output weights of the dynamic reservoir.

17. The computer program product as set forth in claim 10 , wherein generating the denoised reservoir state signal is performed with a dynamic reservoir implemented in analog hardware by satisfying a set of ordinary differential equations.

18. A computer program product for signal denoising and blind source separation, the computer program product comprising:

a non-transitory computer-readable medium having executable instructions encoded thereon, such that upon execution of the instructions by one or more processors, the one or more processors perform operations of:

receiving a mixture signal that comprises a plurality of source signals;

generating a denoised reservoir state signal by mapping the mixture signal to a dynamic reservoir to perform signal denoising; and

identifying at least one separated source signal by adaptively filtering the denoised reservoir state signal;

wherein generating the denoised reservoir state signal is performed with a dynamic reservoir implemented in software or digital hardware by converting a set of ordinary differential equations to delay difference equations.

19. A computer implemented method processor for signal denoising and blind source separation, the method comprising an act of:

causing one or more processers to execute instructions encoded on a non-transitory computer-readable medium, such that upon execution, the one or more processors perform operations of:

receiving a mixture signal that comprises a plurality of source signals;

generating a denoised reservoir state signal by mapping the mixture signal to a dynamic reservoir to perform signal denoising; and

identifying at least one separated source signal by adaptively filtering the denoised reservoir state signal;

wherein adaptively filtering the denoised reservoir state signal further comprises operations of:

detecting that a particular frequency band possesses a pulse;

switching a first filter to a tracking state with a center frequency equal to a resonant frequency of a reservoir state corresponding to the particular frequency band; and

setting the center frequency of the first filter as a protected region to prevent other filters within a bank of filters from sharing the center frequency.

20. The computer implemented method as set forth in claim 19 , wherein filtering the denoised reservoir state signal is performed with a bank of filters.

21. The computer implemented method as set forth in claim 20 , further comprising an operation of controlling the bank of filters to cause each filter within the bank of filters to filter a unique waveform.

22. The computer implemented method as set forth in claim 21 , wherein each filter has an adaptable center frequency.

23. The computer implemented method as set forth in claim 19 , wherein adaptively filtering the denoised reservoir state signal further comprises operations of:

switching the first filter to a holding state if the first filter loses the pulse of the particular frequency band;

maintaining the first filter in the holding state for a fixed period of time while maintaining the protected region;

if during the fixed period of time the pulse returns, switching the first filter to the tracking state, otherwise switching the first filter to an inactive state and removing the protected region.

24. The computer implemented method as set forth in claim 19 , wherein generating the denoised reservoir state signal further comprises delay embedding the reservoir state signal to generate a reservoir state history.

25. The computer implemented method as set forth in claim 19 , wherein generating the denoised reservoir state signal further comprises generating a predicted input signal a small-time step ahead of the mixture signal, wherein an error between the predicted input signal and mixture signal is used to update output weights of the dynamic reservoir.

26. The computer implemented method as set forth in claim 19 , wherein generating the denoised reservoir state signal is performed with a dynamic reservoir implemented in analog hardware by satisfying a set of ordinary differential equations.

27. A computer implemented method processor for signal denoising and blind source separation, the method comprising an act of:

causing one or more processers to execute instructions encoded on a non-transitory computer-readable medium, such that upon execution, the one or more processors perform operations of:

receiving a mixture signal that comprises a plurality of source signals;

generating a denoised reservoir state signal by mapping the mixture signal to a dynamic reservoir to perform signal denoising; and

identifying at least one separated source signal by adaptively filtering the denoised reservoir state signal;

wherein generating the denoised reservoir state signal is performed with a dynamic reservoir implemented in software or digital hardware by converting a set of ordinary differential equations to delay difference equations.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 6, 2018
From: PETRE, PETER; FONG, BRYAN H.; RAO, SHANKAR R.; MARTIN, CHARLES E.
To: HRL LABORATORIES, LLC
Reel/Frame 044846/0909 →
Continuity (7)
Continuation In Part 15452155 · Mar 7, 2017
Continuation In Part 15452412 · Mar 7, 2017
Continuation In Part 15073626 · Mar 17, 2016
Provisional Application 62135539 · Mar 19, 2015
Provisional Application 62304623 · Mar 7, 2016
Provisional Application 62447883 · Jan 18, 2017
Related Publication 20180076795A1 · Mar 15, 2018
Cited By (3)
US 12,499,355 US 12,566,244 US 12,644,960