• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.2
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• pp.137-146
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• 2002

In order to remove the intersymbol interference(ISI) phenomenon in data transmission channel, the structure and convergence analysis of the improved multiplication free adaptive digital filter(IMADF) is presented. Under conditions of zero-mean, wide-sense stationary and white Gaussian noise, it is shown that this paper analyze the convergence characteristics of the IMADF with a fractionally-spaced equalizer(FSE). In the experimental results, the convergence characteristics of the IMADF algorithm is almost same as the sign algorithm, but is better than the MADF algorithm. Here, this algorithm has useful characteristics when the correlation of the input signal is highly.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.11A
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• pp.1803-1811
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• 2001

In this paper, Forward Error Correction(FEC) that is satisfied with ITU-T Recommendation J.83, Annex B(North American Data Over Cable Service Interface Specifications(DOCSIS) for Multimedia Cable Network System(MCNS)) is analyzed. The FEC consist of Reed-Solomon(RS) layer, interleaving layer, randomization layer, and trellis coded modulation(TCM) layer. The effects of quantization of input symbol and of trace-back depth in the Viterbi decoder are simulated over AWGN channels.

• Journal of Biomedical Engineering Research
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• v.15 no.3
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• pp.305-316
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• 1994

All physical data in the real world are nonstationary signals that have the time varying statistical characteristics. Although few algorithms suitable to process the nonstationary signals have ever been suggested, these are treated the nonstationary signals under the assumption that the nonstationary signal is a piece-wise stationary signal. Recently, statistical analysis algorithms for the nonstationary signal have concentrated so much interest. In this paper, nonstationary EMG signals are mapped onto the orthogonal wavelet transform domain so that the eigenvalue spread of its autocorrelation matrix could be more smaller than that in the time domain. Then the model in the wavelet transform domain and an algorithm to estimate the model parameters are suggested. Also, an test signal generated by a white gaussian noise and the EMG signal are identified, and the algorithm performance is considered in the sense of the mean square error and the evaluation parameters.

• ETRI Journal
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• v.45 no.1
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• pp.119-130
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• 2023

We propose a quantized gradient search algorithm that can achieve global optimization by monotonically reducing the quantization step with respect to time when quantization is composed of integer or fixed-point fractional values applied to an optimization algorithm. According to the white noise hypothesis states, a quantization step is sufficiently small and the quantization is well defined, the round-off error caused by quantization can be regarded as a random variable with identically independent distribution. Thus, we rewrite the searching equation based on a gradient descent as a stochastic differential equation and obtain the monotonically decreasing rate of the quantization step, enabling the global optimization by stochastic analysis for deriving an objective function. Consequently, when the search equation is quantized by a monotonically decreasing quantization step, which suitably reduces the round-off error, we can derive the searching algorithm evolving from an optimization algorithm. Numerical simulations indicate that due to the property of quantization-based global optimization, the proposed algorithm shows better optimization performance on a search space to each iteration than the conventional algorithm with a higher success rate and fewer iterations.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.382-382
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• 2020

과거 많은 연구에서 다수의 모형의 결과를 이용한 앙상블 방법론은 인공지능 모형 (artificial neural network)의 예측 능력에 향상을 갖고 온다 논하였다. 본 연구에서는 미계측유역의 저수량(low flow)의 예측을 위하여 Jittering을 기반으로 한 인공지능 모형을 제시하고자 한다. 기본적인 방법론은 설명변수들에게 백색 잡음(white noise)를 삽입하여 훈련되는 자료를 증가시키는 것이다. Jittering을 기반으로 한 인공지능 모형에 대한 효과를 검증하기 위하여 본 연구에서는 Multi-output neural network model을 기반으로 모형을 구축하였다. 다음으로 Jittering을 기반으로 한 앙상블 모형을 variable importance measuring algorithm과 결합시켜서 유역특성치와 예측되는 저수량의 특성치들의 관계를 추론하였다. 본 연구에서 사용되는 방법론들의 효용성을 평가하기 위해서 미동북부에 위치하고 있는 총 207개의 유역을 사용하였다. 결과적으로 본 연구에서 제시한 Jittering을 기반으로 한 인공지능 앙상블 모형은 단일예측모형 (single modeling approach)을 정확도 측면에서 우수한 것으로 확인되었다. 또한, 적은 숫자의 앙상블 모형에서도 그 정확성이 단일예측모형보다 우수한 것을 확인하였다. 마지막으로 본 연구에서는 유역특성치들의 효과가 살펴보고자 하는 저수량의 특성치들에 따라서 일관적으로 영향을 미치거나 그 중요도가 변화하는 것을 확인하였다.

• ETRI Journal
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• v.39 no.2
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• pp.213-221
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• 2017

The advent of wireless access in vehicular environments (WAVE) technology has improved the intelligence of transportation systems and enabled generic traffic problems to be solved automatically. Based on the IEEE 802.11p standard for vehicle-to-anything (V2X) communications, WAVE provides wireless links with latencies less than 100 ms to vehicles operating at speeds up to 200 km/h. To date, most research has been based on field test results. In contrast, this paper presents a numerical analysis of the V2X broadcast throughput limit using a path loss model. First, the maximum throughput and minimum delay limit were obtained from the MAC frame format of IEEE 802.11p. Second, the packet error probability was derived for additive white Gaussian noise and fading channel conditions. Finally, the maximum throughput limit of the system was derived from the packet error rate using a two-ray path loss model for a typical highway topology. The throughput was analyzed for each data rate, which allowed the performance at the different data rates to be compared. The analysis method can be easily applied to different topologies by substituting an appropriate target path loss model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.3862-3879
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• 2019

More and more problems for public security have occurred due to the limited solutions for drone detection especially for micro-drone in long range conditions. This paper aims at dealing with drones detection using a radar system. The radio frequency (RF) signals emitted by a controller can be acquired using the radar, which are usually too weak to extract. To detect the drone successfully, the static clutters and linear trend terms are suppressed based on the background estimation algorithm and linear trend suppression. The principal component analysis technique is used to classify the noises and effective RF signals. The automatic gain control technique is used to enhance the signal to noise ratios (SNR) of RF signals. Meanwhile, the empirical mode decomposition (EMD) based wavelet transform (WT) is developed to decrease the influences of the Gaussian white noises. Then, both the azimuth information between the drone and radar and the bandwidth of the RF signals are acquired based on the statistical analysis algorithm developed in this paper. Meanwhile, the proposed accumulation algorithm can also provide the bandwidth estimation, which can be used to make a decision accurately whether there are drones or not in the detection environments based on the probability theory. The detection performance is validated with several experiments conducted outdoors with strong interferences.

• Journal of Broadcast Engineering
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• v.18 no.6
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• pp.927-934
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• 2013

This paper aims to realize a Signal to Noise Ratio Estimator which constitutes a critical index of the broadcasting system in OFDM system with a synchronized type based on ISDB-T system. Of the elements which are comprising OFDM segments of ISDB-T system using the MSE algorithm suitable for ASIC design owing to its low complexity among a diverse SNR estimation methods, SNR estimation method using the broadcasting information data and the SNR estimation method using scattered pilot signal were realized by RTL. These two methods were compared in terms of their performance through simulation test not only in the AWGN channel which is an ideal channel, but also in SFN channel and frequency selective fading channel, which are distorted channels. Complexity of two methods were also compared through RTL realization. As a result of this comparison analysis, it was concluded that the SNR estimation method using scattered pilot signal shows more excellent performance and easiness in realization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.2C
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• pp.187-198
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• 2004

In this paper, we analyze the performance of BPM (Bi-Phase Modulation) UWB (Ultra Wide Band) multiple access system using PN (Pseudo Noise) code based time hopping sequence in indoor wireless channels. In particular, we compare BPM UWB multiple access system with PPM (Pulse Position Modulation) UWB multiple access system in terms of signalling and demodulation schemes. Moreover, we analytically evaluate the performance of these UWB systems by deriving the bit error rate expressions under the assumption that pulse energy and data transmission rate are identical for both systems. Simulation results in additive white Gaussian noise and realistic indoor multipath wireless channels show that the performance of BPM scheme is approximately 1 dB better than that of PPM scheme. However, the performance discrepancy becomes negligible as the number of users increases.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.7 s.337
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• pp.27-34
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• 2005

Iterative detection (ID) has proven to be a near-optimal solution for concatenated Finite State Machines (FSMs) with interleavers over an additive white Gaussian noise (AWGN) channel. When perfect channel state information (CSI) is not available at the receiver, an adaptive ID (AID) scheme is required to deal with the unknown, and possibly time-varying parameters. The basic building block for ID or AID is the soft-input soft-output (SISO) or adaptive SISO (A-SISO) module. In this paper, Reduced State SISO (RS-SISO) algorithms have been applied for complexity reduction of the A-SISO module. We show that serially concatenated CPM (SCCPM) with AID has turbo-like performance over fading ISI channels and also RS-A-SISO systems have large iteration gains. Various design options for RS-A-SISO algorithms are evaluated. Recently developed density evolution technique is used to analyze RS-A-SISO algorithms. We show that density evolution technique that is usually used for AWGN systems is also a good analysis tool for RS-A-SISO systems over frequency-selective fading channels.