Hrl Laboratories, LLC

Sanaz Adl

Peter Petre

Adour Vahe Kabakian

Bryan H Fong

Gabriel L Virbila

Austin F Garrido

Described is a system for Neuromorphic Adaptive Core (NeurACore) signal processor for ultra-wide instantaneous bandwidth denoising of a noisy signal. The NeurACore signal processor includes a digital signal pre-processing unit for performing cascaded decomposition of a wideband complex valued In-phase and Quadrature-phase (I/Q) input signal in real time. The wideband complex valued I/Q input signal is decomposed into I and Q sub-channels. The NeurACore signal processor further includes a NeurACore and local learning layers for performing high-dimensional projection of the wideband complex valued I/Q input signal into a high-dimensional state space; a global learning layer for performing a gradient descent online learning algorithm; and a neural combiner for combining outputs of the global learning layer to compute signal predictions corresponding to the wideband complex valued I/Q input signal.

Ultra-wide instantaneous bandwidth complex neuromorphic adaptive core processor

Described is a Neuromorphic Adaptive Core (NeurACore) cognitive signal processor (CSP) for wide instantaneous bandwidth denoising of noisy signals. The NeurACore CSP includes a NeurACore block, a globally learning layer, and a neural combiner. The NeurACore block is operable for receiving as an input a mixture of in-phase and quadrature (I/Q) signals and mapping the I/Q signals onto a neural network to determine complex-valued output weights of neural states of the neural network. The global learning layer is operable for adapting the complex-valued output weights to predict a most likely next value of the input I/Q signal. Further, the neural combiner is operable for combining a set of delayed neural state vectors with the weights of the global learning layer to compute an output signal, the output signal being separate in-phase and quadrature signals.

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Thousand Oaks, CA, United States of America

Sanaz Adl