Abstract:
Provided is a capsule endoscope. The capsule endoscope includes: an imaging device configured to perform imaging on a digestive tract in vivo to generate an image; an artificial neural network configured to determine whether there is a lesion area in the image; and a transmitter configured to transmit the image based on a determination result of the artificial neural network.
Abstract:
Disclosed are an electric power conversion apparatus and method in an energy harvesting system. In more detail, it is possible to obtain the maximum electric power from the plurality of energy sources by selecting the connection structure between the source terminals or the connection structure between the source terminals and the collection terminals using the electrical characteristic values (for example, open voltage, short current, and internal impedance) of each source and adjusting the load impedance in the selected connection structure in the energy harvesting system.
Abstract:
Disclosed is a neuron circuit, which includes a first bias circuit that adds a bias current to an input current to generate a biased input current, a logarithm-based neuron calculation circuit that performs a logarithm calculation on an amount of current of the biased input current to generate an input logarithm value and generates a biased output voltage by performing a logarithm-based Hodgkin-Huxley model calculation based on the input logarithm value, and a second bias circuit that adds a bias voltage to the biased output voltage to generate an output voltage.
Abstract:
Disclosed is an electronic device that supports a neural network including a neuron array including neurons, a row address encoder that receives spike signals from neurons and outputs request signals in response to the received spike signals, and a row arbiter tree that receives request signals from the row address encoder and outputs response signals in response to the received request signals. The row arbiter tree includes a first arbiter that arbitrates first and second request signals among request signals, a first latch circuit that stores a state of the first arbiter, a second arbiter that arbitrates third and fourth request signals among request signals, a second latch circuit that stores a state of the second arbiter, and a third arbiter that delivers a response signal to the first and second arbiters based on information stored in the first and second latch circuits.
Abstract:
Disclosed is operation method of an encoder that receives a continuous time-series signal and respectively transmits first to N-th input signals to first to N-th input neuron circuits of spike neural network circuit. The method of operating the encoder includes receiving the continuous time-series signal, generating a plurality of discrete quantum signals by sampling and quantizing the continuous time-series signal, selecting first to N-th discrete quantum signals among the plurality of discrete quantum signals, matching the selected first to N-th discrete quantum signals with the first to N-th input neuron circuits, respectively, identifying discrete quantum signals, each of which has a quantum level different from a quantum level of a previous discrete quantum signal, from among the second to N-th discrete quantum signals, and activating the input signals to be transmitted to the input neuron circuits corresponding to the identified discrete quantum signals and the first discrete quantum signal.
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 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 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:
Provided is a capsule endoscope. The capsule endoscope includes: an imaging device configured to perform imaging on a digestive tract in vivo to generate an image; an artificial neural network configured to determine whether there is a lesion area in the image; and a transmitter configured to transmit the image based on a determination result of the artificial neural network.