Methods and apparatus for spiking neural network computing based on e.g., a multi-layer kernel architecture, shared dendritic encoding, and/or thresholding of accumulated spiking signals. In one exemplary embodiment, a multi-layer mixed-signal kernel is disclosed that uses different characteristics of its constituent stages to perform neuromorphic computing. Specifically, analog domain processing inexpensively provides diversity, speed, and efficiency, whereas digital domain processing enables a variety of complex logical manipulations (e.g., digital noise rejection, error correction, arithmetic manipulations, etc.). Isolating different processing techniques into different stages between the layers of a multi-layer kernel results in substantial operational efficiencies.
METHODS AND APPARATUS FOR SPIKING NEURAL NETWORK COMPUTING BASED ON A MULTI-LAYER KERNEL ARCHITECTURE