Abstract: The present disclosure relates to a spike event decision-making device, method, chip, and electronic device to eliminate inherent delays of an output spike event of the neuromorphic chip when reading decisions. The spike event decision-making device includes a first counting module configured to count a number of input spike events of the spiking neural network, a second counting module configured to count some or all of the output spike events of the spiking neural network; and a decision-making module configured to generate a decision-making result according to numbers of spike events fired by neurons in an output layer of the spiking neural network when the number counted by the first counting module reaches a first predetermined value, or when the total count counted by the second counting module reaches a second predetermined value.

Abstract: A divisive normalization method, device, audio feature extractor, and a chip are disclosed. For improving the robustness against variations of the background noise, the proposed per-channel divisive normalization method comprises: obtaining an average number of input spikes over an averaging window by a low-pass filter to produce a threshold parameter, then deciding whether to enable an integrate-and fire (IAF) counter counting over a clock period of a divisive normalization module, when the count value of IAF counter reaches the threshold, resetting IAF counter and producing a single spike at the output. Compared with the prior art, the proposed method does not require any Linear Feedback Shift Register (LFSR) and is easier to implement. It also has a simpler structure, higher accuracy and better statistical performance, and a lower cost and a lower power consumption.