公开(公告)号：US12057989B1

公开(公告)日：2024-08-06

申请号：US17579871

申请日：2022-01-20

申请人： HRL Laboratories, LLC

发明人： Sanaz Adl ,  Peter Petre ,  Adour V. Kabakian ,  Bryan H. Fong

IPC分类号： H04L27/38

CPC分类号： H04L27/38

摘要： 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.

公开(公告)号：US11863221B1

公开(公告)日：2024-01-02

申请号：US17375724

申请日：2021-07-14

申请人： HRL Laboratories, LLC

发明人： Sanaz Adl ,  Peter Petre ,  Gabriel L. Virbila ,  Austin F. Garrido ,  Bryan H. Fong ,  Adour V. Kabakian

IPC分类号： H04B1/12 ,  G06N3/08

CPC分类号： H04B1/123 ,  G06N3/08

摘要： 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.