• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.13 no.4
• /
• pp.83-89
• /
• 2013

An adaptive blind equalization is a technique using to minimize the Inter-symbol Interference occurred on a communication channel in the transmission of the high speed digital data. In this paper, we propose a blind equalization more improving performance of the conventional MSAGF-MMA adaptive blind equalization algorithm by applying a multiple step size. This algorithm apply a LMS algorithm with a several step size according to each region divided by absolute values of decision-directed error to MSAGF-MMA. By computer simulation, it is confirmed that the proposed algorithm has a performance highly enhanced in terms of a convergence speed, a residual ISI and a residual error and an ensemble averaged MSE in a steady status compared with MMA and MSAGF-MMA.

• Journal of the Institute of Electronics Engineers of Korea TE
• /
• v.39 no.2
• /
• pp.17-28
• /
• 2002

Recently, the study on non-linear equalization, self-recovering equalization using the neural Network structure or Fuzzy logic, is lively in progress. In this thesis, if the value of error difference is large, coefficient adaptation rate is bigger, and if being small, it is smaller. We proposed the new FSG(Fuzzy Stochastic Gradient)/CMA algorithm combining TS(Tagaki-Sugeno) fuzzy model having fast convergence rate and low mean square error(MSE) and CMA(Constant Modulus Algorithm) which is prone to ISI and insensitive to phase alteration. As a simulation result of the designed channel adaptive equalizer using the proposed FSG/CMA algorithm, it is shown that SNR is improved about 3.5dB comparing to the conventional algorithm. 

• The Journal of the Korea institute of electronic communication sciences
• /
• v.9 no.5
• /
• pp.549-554
• /
• 2014

In the paper, we propose a new Signed LMS(Least Mean Square) algorithm for ICS(Interference Cancellation System). The proposed Signed LMS algorithm improved performances by adjusting step size values. At the convergence of 1000 iteration state, the MSE(Mean Square Error) performance of the proposed Signed LMS algorithm with step size of 0.067 is about 3 ~ 18 dB better than the conventional LMS, CMA algorithm. And the proposed Signed LMS algorithm requires 500 ~ 4000 less iterations than the and LMS and CMA algorithms at MSE of -25dB.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.19 no.10
• /
• pp.2001-2013
• /
• 1994

In this paper, the method of processing a blurred noisy image has been researched. The conventional method of processing signal has faluts which are slow convergence speed and long time-consuming process at the singular point and or in the ill condition. There is the process, the Gauss Seidel's method to remove these faults, but it takes too much time because it processed singnal repeatedly. For overcoming the faults, this paper shows a image restoration method which takes shorter than the Gauss-Seidel's by comparing the Gauss Seidel's with proposed alogorithm and accelerating convergence speed at the singular point and/or in the ill condition. In this paper, the conventional process method(Gauss-Seidel) and proposed optimal algorithm were used to get a standard image($256{\times}56{\times}bits$). and then the results are simulated and compared each other in order to examine the variance of MSE(Mean Square Error) by the acceleration parameter in the proposed image restoration. The result of the signal process and the process time was measured at all change of acceleration parameter in order to verify the effectveness of the proposed algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.18 no.3
• /
• pp.77-82
• /
• 2018

This paper is concerned with the performance analysis of a modified stop-and-go generalized multi-modulus algorithm (MSAG-GMMA) adaptive blind equalization algorithm with variable step size. The proposed algorithm multiplies the fixed step size by the error signal of the decision-oriented algorithm in the equalization coefficient update equation, and changes the step size according to the error size. Also, the MSAG-GMMA having a fixed step size is operated so as to maintain a fast convergence speed from a certain threshold to a steady state by determining the error signal size of the decision-directed algorithm, and when the MSAG-GMMA to work To evaluate the performance of the proposed algorithm, we use the ensemble ISI, ensemble-averaged MSE, and equalized constellation obtained from the output of the equalizer as the performance index. Simulation results show that the proposed algorithm has faster convergence speeds than MMA, GMMA, and MSAG-GMMA and has a small residual error in steady state.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.20 no.3
• /
• pp.53-58
• /
• 2020

This paper is concerned with the performance analysis of MSAGF-MMA with variable step size whose step size varies according to input power signal and decision-directed error signal. The proposed algorithm is made to change according to the input power signal which can reliably increase the convergence speed to the steady state by making the step size less affected by the fluctuation of the input signal in the MMA having the binary flag obtained from the modified Stop-and-Go algorithm. At the same time, the step size can be varied according to the decision-directed error signal so that the residual error can be reduced in the steady state. As a result of computer simulations, it is confirmed that the proposed algorithm has a very good performance in the evaluation of residual ISI and averaged-MSE in steady state as well as in terms of convergence speed to steady state compared to MMA and MSAGF-MMA.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.14 no.6
• /
• pp.55-61
• /
• 2014

This paper related with the ECMA (Enchanced CMA) algorithm performance which is possible to simultaneously compensation of the amplitude and phase by appling the minimum disturbance techniques in the CMA adatpve equalizer. The ECMA can improving the gradient noise amplification problem, stability and roburstness performance by the minimum disturbance technique that is the minimization of the equalizer tap weight variation in the point of squared euclidiean norm and the decision directed mode, and then the now cost function were proposed in order to simultaneouly compensation of amplitude and phase of the received signal with the minimum increment of computational operations. The performance of ECMA algorithm was compared to present MCMA by the computer simulation. For proving the performance, the recovered signal constellation that is the output of equalizer output signal and the residual isi and Maximum Distortion charateristic and MSE learning curve that are presents the convergence performance in the equalizer and the overall frequency transfer function of channel and equalizer were used. As a result of computer simulation, the ECMA has more better compensation capability of amplitude and phase in the recovered constellation, and the convergence time of adaptive equalization has improved compared to the MCMA.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.13 no.4
• /
• pp.127-133
• /
• 2013

This paper compare the performance of CCA (Compact Constellation Algorithm) adaptive equalization algorithm by effect of the compact slice weighting value for minimization of the intersymbol interference in the communication channel. The CCA combines the conventional DDA and RCA algorithm, it uses the constant modulus of the transmission signal and the considering the output of decision device by the power of compact slice weighting value in order to improving the initial convergence characteristics and the equalization noise by misadjustment in the steady state. In this process, it is confirmed by computer simulation that the compact slice weight affects the performance of CCA adaptive equalization algorithm. The performance index includes the output signal constellation, the residual isi and maximum distortion and MSE that is for the convergence characteristics, the SER according to the signal and noise power ratio at the channel is used. As a result of computer, it shows that the large weighting value gives more good in every performance index. But in SER performance, it is known that the small values gives more good in low SNR and the large values gives more good in high SNR.

• Journal of Digital Policy
• /
• v.1 no.2
• /
• pp.61-69
• /
• 2022

The paper is a study to develop and verify a blood glucose level prediction model based on biosignals obtained from photoplethysmography (PPG) sensors, ICT technology and data. Blood glucose prediction used the MLP architecture of machine learning. The input layer of the machine learning model consists of 10 input nodes and 5 hidden layers: heart rate, heart rate variability, age, gender, VLF, LF, HF, SDNN, RMSSD, and PNN50. The results of the predictive model are MSE=0.0724, MAE=1.1022 and RMSE=1.0285, and the coefficient of determination (R²) is 0.9985. A blood glucose prediction model using bio-signal data collected from digital devices and machine learning was established and verified. If research to standardize and increase accuracy of machine learning datasets for various digital devices continues, it could be an alternative method for individual blood glucose management.

• Journal of the Korea Convergence Society
• /
• v.13 no.1
• /
• pp.43-50
• /
• 2022

In this paper, it is shown how the performance of the monopulse algorithm in additive noise is evaluated. In the previous study, the performance analysis of the amplitude-comparison monopulse algorithm was conducted via the first-order and second-order Taylor expansion of four variables. By defining two new random variables from the four variables, it is shown that computational complexity associated with two random variables is much smaller than that associated with four random variables. Performance in terms of mean square error is analyzed from Monte-Carlo simulation. The scheme proposed in this paper is more efficient than that suggested in the previous study in terms of computational complexity. The expressions derived in this study can be utilized in getting analytic expressions of the mean square errors.