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OwnerNewton Howard, Ahsan Adeel +2inventors
InventorsNewton Howard, Ahsan Adeel, Mandar Gogate, Amir Hussain
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Embodiments of the present systems and methods may provide a more efficient and low-powered cognitive computational platform utilizing a deep cognitive neural network (DCNN), incorporating an architecture that integrates convolutional feedforward and recurrent networks, and replaces multi-layer perceptron (MLP) based sigmoidal neural structures with a queuing theory-driven design. For example, in an embodiment, a circuit may comprise a plurality of layers of neural network circuitry, each layer comprising a plurality of neuron circuits, each neuron comprising a plurality of computational circuits, and each neuron connected to a plurality of other neurons in the same layer by synapse circuitry, wherein the plurality of layers of neural network circuitry are adapted to process symbolic and conceptual information.
A circuit comprising:
A system comprising a processor, memory accessible by the processor, and computer program instructions stored in the memory and executable by the processor to implement:
A computer program product comprising a non-transitory computer readable storage having program instructions embodied therewith, the program instructions executable by a computer, to cause the computer to implement:
Dependencies are inferred from the claim text.