• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.4
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• pp.383-390
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• 2014

This paper presents an excitatory CMOS neuron oscillator circuit design, which can synchronize two neuron-bursting patterns. The excitatory CMOS neuron oscillator is composed of CMOS neurons and CMOS excitatory synapses. And the neurons and synapses are connected into a close loop. The CMOS neuron is based on the Hindmarsh-Rose (HR) neuron model and excitatory synapse is based on the chemical synapse model. In order to fabricate using a 0.18 um CMOS standard process technology with 1.8V compatible transistors, both time and amplitude scaling of HR neuron model is adopted. This full-chip integration minimizes the power consumption and circuit size, which is ideal for motion control unit of the proposed bio-mimetic micro-robot. The experimental results demonstrate that the proposed excitatory CMOS neuron oscillator performs the expected waveforms with scaled time and amplitude. The active silicon area of the fabricated chip is $1.1mm^2$ including I/O pads.

• Journal of Biomedical Engineering Research
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• v.30 no.2
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• pp.103-112
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• 2009

Neuron-on-a-Chip technology is based on advanced neuronal culture technique, surface micropatterning, microelectrode array technology, and multi-dimensional data analysis techniques. The combination of these techniques allowed us to design and analyze live biological neural networks in vitro using real neurons. In this review article, two underlying technologies are reviewed: Microelectrode array technology and Neuronal patterning technology. There are new opportunities in the fusion of these technologies to apply them in neurobiology, neuroscience, neural prostheses, and cell-based biosensor areas.

• Journal of Sensor Science and Technology
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• v.28 no.5
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• pp.284-288
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• 2019

A calibration-free analog neuron circuit is proposed as a viable alternative to the power hungry digital neuron in implementing a deep neural network. The conventional analog neuron requires calibrations because a voltage-mode link is used between the soma and the synapse, which results in significant uncertainty in terms of current mapping. In this work, a current-mode link is used to establish a robust link between the soma and the synapse against the variations in the process and interconnection impedances. The increased hardware owing to the adoption of the current-mode link is estimated to be manageable because the number of neurons in each layer of the neural network is typically bounded. To demonstrate the utility of the proposed analog neuron, a simple neural network with $4{\times}7{\times}3$ architecture has been designed for classifying iris flowers. The chip is now under fabrication in 0.35 mm CMOS technology. Thus, the proposed true current-mode analog neuron can be a practical option in realizing power-efficient neural networks for edge computing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.8
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• pp.1654-1660
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• 2004

In this paper, we describes the design and implementation of LonWorks communication module for distributed intelligent control using LonWorks technology of Echelon. LonWorks communication module can be divided hardware and firmware. First, hardwares is divided into microcontroller attaching sensors and LonWorks components for working together control network and data network. Hardwares are consisted of neuron chip, microcontroller, transceiver, LONCard. Second, operating firmware is realized with neuron C using NodeBulider 3.0 development tool. Produced and implemented LonWorks communication module is pretested using LTM-10A, Gizmo 4 I/O board, parallel I/O Interface. For field test, microcontroller module part is tested by HyperTerminal, communication procedure in data network is certified by transmitting and receiving short message using LonMaker for Windows tool. Herewith, LON technology is based on network communication technique using LonWorks.

• Journal of Sensor Science and Technology
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• v.18 no.2
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• pp.128-134
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• 2009

Integrated circuit of a new neuron chain with a synapse function for Hodgkin-Huxley model which is a good electrical model about a real biological neuron is implemented in a $0.5{\mu}m$ 1 poly 2 metal CMOS technology. Pulse type neuron chain consist of series connected current controlled single neurons through synapses. For the realization of the single neuron, a pair of voltage mode oscillators using operational transconductance amplifiers and capacitors is used. The synapse block which is a connection element between neurons consist of a voltage-current conversion circuit using current mirror. SPICE simulation results of the proposed circuit show 160 mV amplitude pulse output and propagation of the signal through synapses. Measurements of the fabricated pulse type neuron chip in condition of ${\pm}2.5\;V$ power supply are shown and compared with the simulated results.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.4
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• pp.155-165
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• 1994

An analog neural network circuit of rhigh density integration is introduced. It's prototype chip is designed in 3 by 3 mm2 die. It uses only one MOSFET to implement a synapse. The number of synapses per neuron can be expanded by cascading several chips. The influence of nonlinearity in synapses is analyzed. A formalization of the back propagation which can be applied to this circuit is shown. Some simulation results are shown and disscussed.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2003.11a
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• pp.251-257
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• 2003

In this paper, a new distributed intelligent control module based on LonWorks fieldbus for air handling unit(AHU) of heating, ventilating and air-conditioning(HVAC) is proposed to replace with a conventional direct digital control(DDC) with 32 bit microprocessor. The proposed control architecture has a excellent features such as highly compact and flexible function design, a low priced smart front-end and reliable performance with various functions. This also addresses issues in control network configuration, logical design of field devices by S/W tool, Internet networking and electronic element installation. Experimental results showing the system performance are also included in this paper.

• 전자공학회논문지 IE
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• v.46 no.1
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• pp.16-22
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• 2009

Integrated circuit of a pulse-type neuron for Hodgkin-Huxley model is implemented in a $0.5{\mu}m$ 1 poly 2 metal CMOS technology. Proposed pulse-type neuron model consist of input stage with summing function and pulse generating block which make neuron pulse above threshold value. Pulse generating circuit consist of several transistors, capacitors and negative resistor with a charge supply function. SPICE simulation results show that neuron pulse is generated above threshold current of 70 nA. Measurements of the fabricated pulse type neuron chip in condition of 5 V power supply are shown and compared with the simulated results.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2226-2229
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• 2003

A new method is presented to construct a classifier. This was accomplished by combining a generalized regression neural network (GRNN) and a genetic algorithm (GA). The classifier constructed in this way is referred to as a GA-GRNN. The GA played a role of controlling training factors simultaneously. In GA optimization, neuron spreads were represented in a chromosome. The proposed optimization method was applied to a data set, consisted of 4 different promoter sequences. The training and test data were composed of 115 and 58 sequence patterns, respectively. The range of neuron spreads was experimentally varied from 0.4 to 1.4 with an increment of 0.1. The GA-GRNN was compared to a conventional GRNN. The classifier performance was investigated in terms of the classification sensitivity and prediction accuracy. The GA-GRNN significantly improved the total classification sensitivity compared to the conventional GRNN. Also, the GA-GRNN demonstrated an improvement of about 10.1% in the total prediction accuracy. As a result, the proposed GA-GRNN illustrated improved classification sensitivity and prediction accuracy over the conventional GRNN.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.1
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• pp.115-121
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• 2004

In this paper, a new distributed intelligent control module based on LonWoks fieldbus for air handling unit(AHU) of heating, ventilating and air-conditioning(HVAC) is proposed to replace with a conventional direct digital control(DDC) system with 32 bit microprocessor. The proposed control architecture has a excellent features such as highly compact and flexible function design, a low priced smart front-end and reliable performance with various functions. This also addresses issues in control network configuration, logical design of field devices by S/W tool, Internet networking and electronic element installation. Experimental results for showing the system performance are also included in this paper.