NEURAL NETWORK ACCELERATOR CONFIGURED TO PERFORM OPERATION ON LOGARITHM DOMAIN

    公开(公告)号:US20210334635A1

    公开(公告)日:2021-10-28

    申请号:US17238490

    申请日:2021-04-23

    Abstract: Disclosed is a neural network accelerator including a maximum value determiner outputting a maximum value based on a first magnitude component corresponding to first input data and a second magnitude component corresponding to second input data, a sign determiner outputting a sign component corresponding to the maximum value among a first sign component corresponding to the first input data and a second sign component corresponding to the second input data, as an output sign component, an offset operator quantizing a difference between the first magnitude component and the second magnitude component and outputting an output offset based on the first sign component, the second sign component, and the quantization result, and a magnitude operator calculating an output magnitude component of an output data based on the maximum value and the output offset. Each of the first input data and the second input data is data on a logarithm domain.

    NEURON CIRCUIT WITH SYNAPTIC WEIGHT LEARNING

    公开(公告)号:US20230289582A1

    公开(公告)日:2023-09-14

    申请号:US18084234

    申请日:2022-12-19

    CPC classification number: G06N3/063 G06N3/049

    Abstract: A neuron circuit including a first internal circuit that receives a plurality of spike input signals, generates a first sum value by summing a plurality of synaptic weights corresponding to the plurality of spike input signals, and outputs a second sum value by adding a membrane potential value to the first sum value, a spike generating circuit that generates a spike output signal, a membrane potential generating circuit that generates the membrane potential value, a second internal circuit that counts a last spike time based on the spike output signal, and an online learning circuit that receives a last input time from the first internal circuit and performs LTP learning based on the last input time or receives the last spike time from the second internal circuit and performs LTD learning based on the last spike time.

    ENCODER AND OPERATION METHOD THEREOF

    公开(公告)号:US20230068675A1

    公开(公告)日:2023-03-02

    申请号:US17895532

    申请日:2022-08-25

    Abstract: Disclosed is an encoder including event layer outputs first and second event signals, weight layer applies first and second weights to the first and second event signals respectively, and provides the first event signal in which the first weight is applied and the second event signal in which the second weight is applied to first node, and first spike generation circuit generates first input spike signal of which firing period is changed based on voltage level of the first node. The voltage level of the first node is reduced continuously, increases for first voltage corresponding to the first weight in response to the first event signal activated, and increases for second voltage corresponding to the second weight in response to the second event signal activated.

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