• Journal of electromagnetic engineering and science
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• v.18 no.1
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• pp.58-62
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• 2018

In this study, we propose a software-defined radio-based frequency interference emulator in the space-time domain. This emulator can easily model actual interference environments because of the versatile programming capability of the universal software radio peripheral and LabVIEW. As an example of an interfering network using the contention-based multiple access scheme in the time domain, we emulate a coordinated Wi-Fi network that consists of one access point and two Wi-Fi nodes. Results show that our emulator can successfully model multiple interfering signals in the Wi-Fi network and easily adjust various space-time domain parameters.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.12 no.1
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• pp.60-70
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• 1987

Recently the tendency of the network system development rapidly progresses toward ISDN that intergrates all presetn-day communication networks and services into a single, universal network set up on the basis of the exisiting telephone network. For this reason many countries pay worldwide attention to the researches about ISDN, especially to the researches about the exchange and the ISDN user-network interface which is one of the most important parts of network system. This paper is the first part of the two-par papers describing the ISDN user-network interface. in this paper, after surveying the architecture of ISDN exchange recommended by CCITT, the general architecture of the ISDN exchage is proposed, Based on this architecture, the switching emulator is implemented, and the necessary conditions of the ISDN exchage(LAPO, CCP etc) are also studied.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.125-130
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• 2015

In this paper, a command and control (C2) system development using a network emulator is treated. Due to the development of information and communication technologies enabling reinforcement of information exchange and computational capability, an operational concept network centric warfare (NCW) was introduced. In here, it summarizes a developmental test environment build based on dummynet, one of the software based network emulator, and an operational concept of target command and control system. Moreover, I explain command and control system developmental test cases and results, and suggest an operational concept to overcome limitations of target communication system. I expect this concept will reduce data traffic of proposed C2 system especially plot messages which is distributed same data with short interval.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.386-389
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• 1997

Error-backpropagation has been used in the bulk of Practical applications for neural networks. While an emulator, a multilayered neural network, learns to identify the system's dynamic characteristics. There is, however, no concrete theoretical results about the structure of a plant and the structure of a multilayered neural network and the learning rate. The paper investigates the relation between structure of a plant and a multilayered network and learning rate. Simulation study shows that the plant signal with a short period and a fast sam time is preferable for learning of the network emulator.

• Journal of electromagnetic engineering and science
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• v.18 no.4
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• pp.254-260
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• 2018

In this study, we suggest an emulator for generating multiple heterogeneous interference signals in the Korean radio frequency identification/ubiquitous sensor network (RFID/USN) frequency band. The proposed emulator uses only one universal software radio peripheral to generate multiple heterogeneous interference signals more economically. Moreover, the physical and media access control parameters can be adjusted in real time using the LabVIEW program, thereby making it possible to create various time-varying interference environments easily. As an example showing the capability of the proposed emulator, multiple interference signals consisting of a frequency-hopping RFID signal and two LoRa signals with different spreading factors were generated. The generated signals were confirmed in both frequency and time domains. From the experimental results, we verified that our emulator could successfully generate multiple heterogeneous interference signals with different frequency and time domain characteristics.

• Proceedings of the KIEE Conference
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• 1995.07a
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• pp.251-254
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• 1995

The Fuzzy-Neural Controller is constructed to resolve some dificulties taking place in decision of membership functions, input and output gains and an inferenced method for desinging fuzzy logic controller. In addition Neural network emulator is used to emulate induction motor forward dynamics and to get error signal at fuzzy-neural controller output layer. Error signal is backpropagated through neural network emulator. A back propagation algorithm is used to train fuzzy-neural controller and emulator. The experimental results show that this control system can provide good dynamical responses.

• Journal of information and communication convergence engineering
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• v.18 no.1
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• pp.1-7
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• 2020

This paper proposes a fast-processing and low-cost hardware multiple input multiple output (MIMO) channel emulator. The channel emulator is an important component of hardware-based simulation systems. The novelty of this work is the use of sharing and pipelining functions to reduce hardware resource utilization while maintaining a high sample rate. In our proposed emulator, the samples are created sequentially and interpolated to ensure the sample rate is equal to the base band rate. The proposed 4 × 4 MIMO requires low-cost hardware resource so that it can be implemented on a single field-programmable gate array (FPGA) chip. An implementation on Xilinx Virtex-7 VX980T was found to occupy 10.47% of the available configurable slice registers and 12.58% of the FPGA's slice lookup tables. The maximum frequency of the proposed emulator is 758.064 MHz, so up to 560 different paths can be processed simultaneously to generate 560 × 758 million × 2 × 32 bit complex-valued fading samples per second.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.516-518
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• 1999

This paper presents an feed-forward neural network design instead PI controller for the speed control of an Induction Motor. The design employs the training strategy with Neural Network Controller(NNC) and Neural Network Emulator(NNE). Emulator identifies the motor by simulating the input and output map. In order to update the weights of the Controller. Emulator supplies the error path to the output stage of the controller using backpropagation algorithm. and then Controller produces an adequate output to the system due to neural networks learning capability. Therefore it becomes adjustable to the system with changing characteristics caused by a load. The speed control based on neural networks for induction motor is implemented by a vector controlled induction motor. The simulation results demonstrate that actual motor speed with neural network system well follows the reference speed minimizing the error and is available to implement on the vector control theory.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.6
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• pp.1010-1016
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• 2004

In this paper, a scheme for estimating the parameters of solar cells and a NN-based emulator for predicting the maximum power point are presented. The diode model with series and shunt resistors is used to estimate parameters highly affecting its V-I characteristic curve and both a real-coded genetic algorithm and the model adjustment technique are employed. For implementing the emulator, a multi-layered neural network incorporating with the BP algorithm is used. A set of simulation works using both field data and generated data are carried out to demonstrate the effectiveness of the proposed method.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.1
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• pp.42-53
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• 1996

The paper presents a speed control system of vector controlled induct- ion motor using neural networks. The main feature of proposed speed control system is a Neural Network Controller(NNC) which supplies torque current to induction motor and Neural Network Emulator(NNE) which captures the forward dynamics of induction motor. A back propagation training algorithm is employed to train the NNE and NNC. In order to determine the NNC output error, plant(induction motor) output error can be back propagated through the NNE. The NNC and NNE for speed control of vector controlled induction motor is carried out by TMS320C30 DSP and IGBT current regulated PWM inverter. Through computer simulation and experimental results, it is verified that proposed speed control system is robust to the load variation. (author). refs., figs.