Abstract: Various embodiments of a system and methods for audio source separation via multi-scale feature learning are disclosed.

Abstract: Various embodiments of a system and associated method for audio source separation based on generative priors trained on individual sources. Through the use of projected gradient descent optimization, the present approach simultaneously searches in the source-specific latent spaces to effectively recover the constituent sources. Though the generative priors can be defined in the time domain directly, it was found that using spectral domain loss functions leads to good-quality source estimates.

Abstract: A system reconfigures a photovoltaic array used in solar energy based on observed shading conditions to determine an optimal topology of the photovoltaic array to maximize power output. Specifically, the system is designed to reconfigure a photovoltaic array when the photovoltaic array is partially shaded. The system uses a neural network model to determine a topology that maximizes power output of the photovoltaic array based on irradiance data obtained from the photovoltaic array.

Abstract: Various embodiments for a connection topology reconfiguration technique for photovoltaic (PV) arrays to maximize power output under partial shading and fault conditions using neural networks are disclosed herein.

Abstract: Various embodiments of a system and associated method for detection of COVID-19 and other respiratory diseases through classification of audio samples are disclosed herein. The system utilizes features directly extracted from the coughing audio and develops automated diagnostic tools for COVID-19. In particular, the present application discusses a novel modification of a deep neural network architecture by using log-mel spectrograms of the audio excerpts and by optimizing a combination of binary cross-entropy and focal loss parameters. One embodiment of the system achieved an average validation AUC of 82.23% and a test AUC of 78.3% at a sensitivity of 80.49%.

Abstract: Various embodiments of a system and associated method for audio source separation based on generative priors trained on individual sources. Through the use of projected gradient descent optimization, the present approach simultaneously searches in the source-specific latent spaces to effectively recover the constituent sources. Though the generative priors can be defined in the time domain directly, it was found that using spectral domain loss functions leads to good-quality source estimates.

Abstract: Various embodiments of a system and methods for audio source separation via multi-scale feature learning are disclosed.

Abstract: Various embodiments for a connection topology reconfiguration technique for photovoltaic (PV) arrays to maximize power output under partial shading and fault conditions using neural networks are disclosed herein.