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.

    AUTHENTICATION ELECTRONIC DEVICE BASED ON BIOMETRIC TEMPLATE AND OPERATING METHOD THEREOF

    公开(公告)号:US20220382842A1

    公开(公告)日:2022-12-01

    申请号:US17825453

    申请日:2022-05-26

    Abstract: Disclosed are a biometric template-based authentication electronic device and an operating method thereof. The electronic device includes a memory, a transmitter that transmits a chirp signal, of which a frequency is changed, to a user, a receiver that obtains a biometric channel response signal, which responds to the transmitted chirp signal, from the user, and at least one processor that executes a biometric template authentication module based on machine learning. When executing the biometric template authentication module, the processor obtains a feature signal from the obtained biometric channel response signal, generates a biometric template from the obtained feature signal, performs the machine learning such that identification information of the user is inferred from the generated biometric template, and authenticates the user based on the result of the machine learning.

    CAPSULE ENDOSCOPE IMAGE RECEIVER AND CAPSULE ENDOSCOPE DEVICE HAVING THE SAME

    公开(公告)号:US20200315438A1

    公开(公告)日:2020-10-08

    申请号:US16842497

    申请日:2020-04-07

    Abstract: A capsule endoscope image receiver includes a receiving electrode unit that receives first and second differential signals from a capsule endoscope image transmitter through a human body communication channel, an analog amplifying unit that receives the first and second differential signals and outputs first and second amplified differential signals, and a signal restoring unit that receives the first and second amplified differential signals and restores image information. The analog amplifying unit includes a first amplifier that outputs the first amplified differential signal, a second amplifier that outputs the second amplified differential signal, and an input impedance that is connected between a first inverting input terminal of the first amplifier and a second inverting input terminal of the second amplifier and obtains a gain of differential signal amplification in which a high frequency component of the first and second amplified differential signals is greater than a low frequency component.

    ANOMALY DATA DETECTION DEVICE AND OPERATION METHOD OF THE SAME

    公开(公告)号:US20240265245A1

    公开(公告)日:2024-08-08

    申请号:US18235919

    申请日:2023-08-21

    CPC classification number: G06N3/049 G06N3/063

    Abstract: Disclosed is an anomaly data detection device, which includes a sampler that generates session data including first to m-th sample data based on input data input during a first time interval, a spike signal generator that generates first to m-th spike signals respectively corresponding to the first to m-th sample data based on the session data, a spike neural network that detects whether an output spike fires in at least one output neuron from among output neurons based on the first to m-th spike signals and synaptic weights of each of the output neurons, and a detection circuit that generates a detection signal based on the number of output neurons firing the output spike, and each of the first to m-th spike signals is generated by converting feature information of the corresponding first to m-th sample data into a spike rate code.

    SPIKE NEURAL NETWORK CIRCUIT
    10.
    发明公开

    公开(公告)号:US20230385620A1

    公开(公告)日:2023-11-30

    申请号:US18125553

    申请日:2023-03-23

    CPC classification number: G06N3/063 G06N3/049

    Abstract: Disclosed is a spike neural network circuit which includes a pulse generator that receives an input spike signal and generates a first modulation pulse and a second modulation pulse based on the input spike signal, first and second current source arrays controlled based on a weight memory, a membrane capacitor, a first switch that delivers a first calculation signal generated from the first current source array to the membrane capacitor, in response to the first modulation pulse, and a second switch that delivers a second calculation signal generated from the second current source array to the membrane capacitor, in response to the second modulation pulse.

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