Cognitive signal processor for simultaneous denoising and blind source separation

• US 10,128,820 B2
• Filed: 11/20/2017
• Issued: 11/13/2018
• Est. Priority Date: 03/19/2015
• Status: Active Grant

• Current Assignee: HRL Laboratories LLC (The Boeing Co.)
• Original Assignee: HRL Laboratories LLC (The Boeing Co.)
• Inventors: Petre, Peter, Fong, Bryan H., Rao, Shankar R., Martin, Charles E.
• Primary Examiner(s): Fan, Chieh M
• Assistant Examiner(s): Hailegiorgis, Fitwi
• Application Number:
  US15/817,906
• Publication Number:
  US 20180076795A1
• Time in Patent Office: 358 Days
• Field of Search: 375130, 375346
• CPC Class Codes: G01S 7/414 Discriminating targets with respect to background clutter
• CPC Class Codes: G01S 7/417 involving the use of neural networks
• CPC Class Codes: G06F 18/2134 based on separation criteria, e.g. independent component analysis
• CPC Class Codes: G06F 2218/22 Source localisation; Inverse modelling
• CPC Class Codes: G06N 3/044 Recurrent networks, e.g. Hopfield networks
• CPC Class Codes: G06N 3/065 Analogue means
• CPC Class Codes: H03H 2021/0034 Blind source separation
• CPC Class Codes: H03H 21/0025 Particular filtering methods
• CPC Class Codes: H04B 1/71632 Signal aspects H04B1/7172 and H04B1/7176 take precedence
• CPC Class Codes: H04B 1/719 Interference-related aspects

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

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.