Abstract: A low power system on chip for supporting partial clock gating is provided. The system on chip includes a network on chip including a first CG-network interface module, a second CG-network interface module, and a clock gating control module, a first IP block that communicates through the first CG-network interface module, and a second IP block that communicates through the second CG-network interface module. The clock gating control module receives a clock gating request from the first IP block, outputs a communication control signal to the second CG-network interface module in response to the received clock gating request, and performs a clock gating operation for a clock signal in response to the received clock gating request to selectively deliver the clock signal to the second IP block.

Abstract: Disclosed is a synaptic circuit including a weight memory that stores a weight value, a current-mode digital-to-analog converter (C-DAC) circuit that receives the weight value from the weight memory and supplies a current based on the weight value, a parasitic capacitor correction circuit that receives the weight value from the weight memory and to correct a value of parasitic capacitance generated by the C-DAC circuit based on the weight value, and a pre-discharge circuit that drains charges accumulated by the parasitic capacitance.

Abstract: Disclosed is an SNN circuit including a spike generator that receives an input spike signal and converts the input spike signal into a sub-spike signal and a main spike signal, a synaptic circuit that generates an operation signal based on a weight and outputs the operation signal in response to the main spike signal, a membrane capacitor that accumulates the operation signal, and a potential correction circuit that corrects an output terminal voltage of the synaptic circuit based on a voltage of the membrane capacitor.

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.

Abstract: Provided are a human body communication device and an operating method of the same. The human body communication device according to an embodiment of the inventive concept includes a first electrode, a second electrode, a transmitting circuit, a receiving circuit, a ground electrode, and a switch. The transmitting circuit generates a first signal in a transmitting mode and transmits the first signal to the first electrode. The receiving circuit receives a second signal from the first electrode in the receiving mode. The receiving circuit includes a differential amplifier that amplifies a difference between a voltage level of a first input terminal depending on the second signal and a voltage level of a second input terminal. The switch electrically connects the second electrode and the ground electrode in the transmitting mode, and electrically connects the second electrode and the second input terminal in the receiving mode.

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.

Abstract: Disclosed is a learning method of a neural network which includes a first intermediate neuron layer and a second intermediate neuron layer. The method includes performing first learning, which is based on a first synaptic weight layer, with respect to input subjects and the first intermediate neuron layer, determining intermediate neurons, which will perform second learning, from among intermediate neurons of the first intermediate neuron layer, based on the number of spikes of each of spike output signals of the intermediate neurons of the first intermediate neuron layer, and performing the second learning, which is based on a second synaptic weight layer, with respect to the intermediate neurons determined to perform the second learning.

Abstract: Disclosed are a human body communication receiver and an operating method thereof, which may effectively remove low frequency noise. The human body communication receiver according to the present disclosure includes a receiving electrode, a virtual electrode, a filter circuit that is connected between the receiving electrode and the virtual electrode, and removes low frequency noise from a signal received through the receiving electrode to generate a high frequency signal, a low frequency reconstruction circuit that is connected to a rear end of the filter circuit and reconstructs a low frequency baseband signal by rectifying the high frequency signal, and an amplifying circuit that is connected to a rear end of the low frequency reconstruction circuit, and amplifies the low frequency baseband signal.

Abstract: Provided is a receiver. The receiver according to the inventive concept includes a first filter circuit, a second filter circuit, and an amplifier. The first filter circuit provides a first path for first frequency components below first cutoff frequency of input frequency components and passes second frequency components except for the first frequency components of the input frequency components through second path. The second filter circuit attenuates third frequency components below a second cutoff frequency of the second frequency components. The amplifier amplifies the second frequency components including the attenuated third frequency components.

Abstract: Disclosed is a spike neural network circuit according to an embodiment of the present disclosure, which includes a self-correcting control circuit that generates an input signal and a first control code, a bias voltage generation circuit that generates a first bias voltage based on the first control code, a synaptic circuit including a first synaptic column that performs an operation of the input signal and a first weight signal and generates a first operation signal, a neuron circuit including a first neuron that generates a first output signal based on a comparison of the first operation signal and a threshold voltage, and a spike comparison circuit that generates a first comparison signal corresponding to a difference between the first output signal and a reference number, and the self-correcting control circuit further generates a second control code for correcting the first bias voltage.

Abstract: Provided is a spike neural network circuit. The spike neural network circuit includes an axon configured to generate an input spike signal, a synapse including a first transistor for outputting a current according to a weight and a second transistor connected to the first transistor and outputting the current according to an input spike signal, a neuron configured to compare a value according to the current output from the synapse with a reference value and generate an output spike signal based on a comparison result, and a radiation source attached to a substrate on which the synapse is formed, configured to output radiation particles to the synapse, and configured to increase magnitudes of threshold voltages of the first and second transistors of the synapse.

Abstract: Disclosed is an operating method of a user communication device, which includes receiving a wakeup signal from a stationary communication device over a first human body communication channel, the wakeup signal having a frequency in a low frequency band, switching from a standby mode to a wakeup mode in response to the wakeup signal, and receiving a data signal from the stationary communication device over the first human body communication channel during the wakeup mode, and the first human body communication channel is provided by a body of a user of the user communication device.

Abstract: Disclosed is a spiking neural network circuit, which includes an axon circuit that generates an input spike signal, a first synapse zone and a second synapse zone each including one or more synapses, wherein each of the synapses is configured to perform an operation based on the input spike signal and each weight, and a neuron circuit that generates an output spike signal based on operation results of the synapses. The input spike signal is transferred to the first synapse zone and the second synapse zone through a tree structure, and each of branch nodes of the tree structure includes a driving buffer.

Abstract: Disclosed is a method for learning an artificial neural network in a synapse of an artificial intelligence system including generating, by an input neuron of the artificial intelligence system, a first input signal, generating, by the input neuron, a second input signal after a predetermined time, generating, by an output neuron of the artificial intelligence system, an output signal in response to the first input signal and the second input signal that are generated by the input neuron, and adjusting, by the synapse of the artificial intelligence system, connection strength of the artificial neural network based on a temporal order of the first input signal and the second input signal that are generated by the input neuron.

Abstract: Provided is and electrode selection device communicating with a capsule endoscope. The device includes an analog front end configured to recover first data based on first signals transmitted from the capsule endoscope to a first electrode and a second electrode, recover second data based on second signals transmitted from the capsule endoscope to the first electrode and a third electrode, and recover third data based on third signals transmitted from the capsule endoscope to the second electrode and the third electrode, and a digital receiver configured to calculate a first correlation value between the first and second electrodes, a second correlation value between the first and third electrodes, and a third correlation value between the second and third electrodes based on the first to third data. The digital receiver calculates first to third correlation sums, and selects a receiving electrode pair based on the first to third correlation sums.

Abstract: Disclosed is a network-on-chip including a first data converter that receives first image data and second image data from at least one image sensor and encodes one image data among the first image data and the second image data, into first data, based on whether the first image data is identical to the second image data and a second data converter that receives non-image data from at least one non-image sensor and encodes the received non-image data into second data. The network-on-chip outputs the first data and the second data to transmit the first data and the second data to an external server at a burst length.

Abstract: A human body communication device includes an electrode, a matching circuit, a switch providing a first path electrically connected to the matching circuit and a second path electrically connected to the matching circuit, a sensor, in a first state, connected to the matching circuit through the switch, outputting a first sensing signal to the matching circuit, and outputting a second sensing signal when a difference between a signal generated from the matching circuit in response to the first sensing signal and the first sensing signal is greater than or equal to a threshold, a transmitter, in a second state, connected to the matching circuit through the switch, and outputting a data signal to the matching circuit, and a controller controlling the switch from the first state to the second state in response to receiving the second sensing signal from the sensor, in the first state.

Abstract: Provided is an artificial intelligence system. The system includes a first sensor configured to generate a first sensing signal during a sensing time, a second sensor disposed adjacent to the first sensor and configured to generate a second sensing signal during the sensing time, a pre-processing unit configured to select valid data according to a magnitude of a differential signal generated based on a difference between the first sensing signal and the second sensing signal, and an artificial intelligence module configured to analyze the valid data to generate result data.

Abstract: Disclosed are a human body communication receiver and an operating method thereof, which may effectively remove low frequency noise. The human body communication receiver according to the present disclosure includes a receiving electrode, a virtual electrode, a filter circuit that is connected between the receiving electrode and the virtual electrode, and removes low frequency noise from a signal received through the receiving electrode to generate a high frequency signal, a low frequency reconstruction circuit that is connected to a rear end of the filter circuit and reconstructs a low frequency baseband signal by rectifying the high frequency signal, and an amplifying circuit that is connected to a rear end of the low frequency reconstruction circuit, and amplifies the low frequency baseband signal.

Abstract: Disclosed is a data processing device of a spike neural network. The data processing device according to the present disclosure includes an input terminal that receives time series data, a processor that differentiates the input time series data, determines a point at which a differential value of the time series data is “0”, and generates an output in a discrete form, based on the determination result, and an output terminal that generates a spike train signal, based on the output and outputs the generated spike train signal to external axons.