Efficient cognitive signal denoising with sparse output layers
AssigneeHRL Laboratories, LLC
InventorsShankar R. Rao, Peter Petre
Life of this patent
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Abstract
Described is a system for signal denoising. The system linearly maps a noisy input signal into a high-dimensional reservoir, where the noisy input signal is a time-series of data points from a mixture of waveforms. A high-dimensional state-space representation of the mixture of waveforms is created by combining the noisy input signal with reservoir states. A delay embedded state signal is generated from the reservoir states, and a denoised spectrogram of the noisy input signal is generated.
Claims15
A system for signal denoising, the system comprising:
- one or more processors and a non-transitory computer-readable medium having executable instructions encoded thereon such that when executed, the one or more processors perform operations of:
- linearly mapping a noisy input signal into a high-dimensional reservoir, wherein the noisy input signal is a time-series of data points from a mixture of waveforms;
- creating a high-dimensional state-space representation of the mixture of waveforms by combining the noisy input signal with reservoir states,
- wherein the reservoir is a recurrent neural network having a plurality of nodes, and
- wherein a connectivity matrix of the reservoir comprises a block diagonal form optimized such that computation of the reservoir states scales linearly with the number of nodes;
- generating a delay embedded state signal from the reservoir states;
- and
- generating a denoised spectrogram of the noisy input signal.
A computer implemented method for signal denoising, 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:
- linearly mapping a noisy input signal into a high-dimensional reservoir, wherein the noisy input signal is a time-series of data points from a mixture of waveforms;
- creating a high-dimensional state-space representation of the mixture of waveforms by combining the noisy input signal with reservoir states,
- wherein the reservoir is a recurrent neural network having a plurality of nodes, and
- wherein a connectivity matrix of the reservoir comprises a block diagonal form optimized such that computation of the reservoir states scales linearly with the number of nodes;
- generating a delay embedded state signal from the reservoir states;
- and
- generating a denoised spectrogram of the noisy input signal.
A computer program product for signal denoising, the computer program product comprising:
- computer-readable instructions stored on a non-transitory computer-readable medium that are executable by a computer having one or more processors for causing the processor to perform operations of:
- linearly mapping a noisy input signal into a high-dimensional reservoir, wherein the noisy input signal is a time-series of data points from a mixture of waveforms;
- creating a high-dimensional state-space representation of the mixture of waveforms by combining the noisy input signal with reservoir states,
- wherein the reservoir is a recurrent neural network having a plurality of nodes, and
- wherein a connectivity matrix of the reservoir comprises a block diagonal form optimized such that computation of the reservoir states scales linearly with the number of nodes;
- generating a delay embedded state signal from the reservoir states;
- and
- generating a denoised spectrogram of the noisy input signal.
Dependencies are inferred from the claim text.