• Journal of Satellite, Information and Communications
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• v.10 no.1
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• pp.22-28
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• 2015

In this paper, we propose a new computationally efficient joint iterative multi-input multi-output (MIMO) detection scheme using a soft interference cancellation and minimum mean squared-error (SIC-MMSE) method. The critical computational burden of the SIC-MMSE scheme lies in the multiple inverse operations of the complex matrices. We find a new way which requires only a single matrix inversion by utilizing the Taylor series expansion of the matrix, and thus the computational complexity can be reduced. The computational complexity reduction increases as the number of antennas is increased. The simulation results show that our method produces almost the same performances as the conventional SIC-MMSE with reduced computational complexity.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.25 no.4
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• pp.467-474
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• 2001

The mathematical model of a air-conditioning system is generally very complex and difficult to apply to controller design. In this paper, simple models applicable to the controller design are obtained by modeling the air-conditioning system by single-input single-output between compressor speed and indoor temperature, and by multi-input single-output between compressor speed, indoor fan speed and indoor temperature. Using these empirical models, model predictive control(MPC) technique was implemented for indoor temperature control of the air-conditioning system. It has been shown from various experiments that the indoor temperature control based on the MPC scheme yields reasonably good tracking performance with smooth changes in plant inputs. this multi-input multi-output MPC approach can be extended to multi air- conditioning systems where the conventional PID control scheme is very difficult to apply.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.21 no.4
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• pp.321-328
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• 2008

In this paper, variable gain amplifier(VGA) with a gain slope controller has been proposed and verified by circuit simulations and measurements. The proposed VGA has a gain control, gain slope switch and variable gain range. The input source coupled pair with diode connected load is used for VGA gain stage. The gain slope controller with switch can control VGA gain slope. The proposed VGA is fabricated in $0.18{\mu}m$ CMOS process for multi -standard wireless receiver. The proposed two stage VGA consumes min. 2.0 mW to max. 2.6 mW in gain control range and gives input IP3 of -3.77 dBm and NF of 28.7 dB at 1.8 V power supply under -25 dBm, 1 MHz input. The proposed VGA has 37 dB(-16 dB $\sim$ 21 dB) variable gain range, and 8 dB gain range control per 0.3 V control voltage, and can provide variable gain, positive and negative gain slope control, and gain range control. This VGA characteristics provide design flexibility in multi-standard wireless receiver.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.32 no.11
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• pp.394-403
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• 1983

This paper discusses a model reference adaptive control for a multi-input multi-output continuos system in matrix fraction description. The controller is of Monopoli-Narendra type with a time-varying gain matrix in the parameter adaptation law. The transfer matrix of the given plant with an adjustable controller is made to approach to that of the reference model asymptotically. It is shown that, under some plausible assumptions such as on the knowlidge of an interactor matrix, the algorithm for a single-input single-output system can be appropriately extended to a multi-input multi-output system. The convergence of an adaptation law is estavlished with some stability theory and stability of the overall system is asserted by an analytical investigation.

• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.1
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• pp.53-62
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• 2024

In this study, we built a model to estimate frost occurrence in South Korea using single-input deep learning and multi-input deep learning. Meteorological factors used as learning data included minimum temperature, wind speed, relative humidity, cloud cover, and precipitation. As a result of statistical analysis for each factor on days when frost occurred and days when frost did not occur, significant differences were found. When evaluating the frost occurrence models based on single-input deep learning and multi-input deep learning model, the model using both GRU and MLP was highest accuracy at 0.8774 on average. As a result, it was found that frost occurrence model adopting multi-input deep learning improved performance more than using MLP, LSTM, GRU respectively.

• Current Optics and Photonics
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• v.8 no.3
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• pp.215-224
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• 2024

In medium- and long-range optical imaging systems, atmospheric turbulence causes blurring and distortion of images, resulting in loss of image information. An image-restoration method based on an adaptive feature-fusion multi-input-multi-output (MIMO) dense U-shaped network (Unet) is proposed, to restore a single image degraded by atmospheric turbulence. The network's model is based on the MIMO-Unet framework and incorporates patch-embedding shallow-convolution modules. These modules help in extracting shallow features of images and facilitate the processing of the multi-input dense encoding modules that follow. The combination of these modules improves the model's ability to analyze and extract features effectively. An asymmetric feature-fusion module is utilized to combine encoded features at varying scales, facilitating the feature reconstruction of the subsequent multi-output decoding modules for restoration of turbulence-degraded images. Based on experimental results, the adaptive feature-fusion MIMO dense U-shaped network outperforms traditional restoration methods, CMFNet network models, and standard MIMO-Unet network models, in terms of image-quality restoration. It effectively minimizes geometric deformation and blurring of images.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.9
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• pp.1-8
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• 2007

In this paper, the new beamforming is proposed for an orthogonal frequency division multiplexing(OFDM) system with multi-input multi-output(MIMO). Through the proposed Pre-FFT beamforming technique for MIMO-OFDM, the multibeams are formed toward each multi-transmitter antenna of the desired user. The proposed beamforming for MIMO-OFDM can reduce cochannel interference and get diversity gain in the multi-user environment. Therefore, the performance of MIMO-OFDM system is very improved. BER performance improvement of the proposed approach is investigated through computer simulation by applying it to MIMO-OFDM system in the multi-user environment.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.52 no.1
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• pp.20-27
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• 2003

In this study, we designed and made Ultrasonic motor-digital multi controller(USM-DMC) using FPGA chip, A54SX72A made in Actel Corporation. By the minute, USM-DMC can adjust the frequency, duty ratio, and phase difference parameters of USM by digital input to be each 11bit from PC. Therefore, when we use this controller, it is possible to apply typical three parameters individually as well as multi-parameters simultaneously to control the speed and the torque. What is more, the strongest point is that it can trace frequency based on optimized frequency as compared with the phase difference because we can input optimized resonant frequency while in motoring. And we test the speed of USM with the adjustment of multi-parameters, the phase difference-frequency. As the result of the test, in the case of the multi-parameters of the phase difference and frequency, the speed characteristic is more linear and stable, and wider in the range of control than the single-parameter of the phase difference or the frequency.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.1
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• pp.17-25
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• 2005

This paper provides sufficient conditions for the robustness of Affine linear TFM(Transfer Function Matrix) MIMO (Multi-Input Multi-Output) uncertain systems based on Rosenbrock's DNA (Direct Nyquist Array). The parametric uncertainty is modeled through a Affine TFM MIMO description, and the unstructured uncertainty through a bounded perturbation of Affine polynomials. Gershgorin's theorem and concepts of diagonal dominance and GB(Gershgorin Bands) are extended to include model uncertainty. For this type of parametric robust performance we show robustness of the Affine TFM systems using Nyquist diagram and GB, DNA(Direct Nyquist Array). Multiloop PI/PB controllers can be tuned by using a modified version of the Ziegler-Nickels (ZN) relations. Simulation examples show the performance and efficiency of the proposed multiloop design method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.194-198
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• 1998

A novel fuzzy basis function vector- based adaptive control approach for Multi-input and Multi-output(MIMO) system is presented in this paper, in which the nonlinear plants is first linearised, the fuzzy basis function vector is then introduced to adaptively learn the upper bound of the system uncertainty vector, and its output is used as the paramenters of the compensator in the sense that both the robustness and the asymptotic error convergence can be obtained for the closed loop nonlinear control system.