• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7A
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• pp.535-544
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• 2012

Multi-Input Multi-Output (MIMO) transmission is now considered as one of essential techniques enabling high rate data transmissions in wireless communication systems. In addition, severe channel impairments in wireless systems should be compensated by using highly efficient forward error correction (FEC) codes. Turbo codes or low density parity check (LDPC) codes, using iterative decoding with soft decision detection information (SDDI), are the most common examples. The excellent performance of these codes should be conditioned on accurate estimation of SDDI from the MIMO detection process. In this paper, we propose a soft MIMO detection scheme using QR decomposition of channel matrices as an efficient means to provide accurate SDDI to the iterative decoder. The proposed method employed a two sequential soft MIMO detection process in order to reduce computational complexity. Compared to the soft ZF method calculating the direct inverse of the channel matrix, the complexity of the proposed method can be further reduced as the number of antennas is increased, without any performance degradation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1131-1143
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• 2016

Differential detection schemes do not require any channel estimation, which can be employed under user mobility with low computational complexity. In this work, a soft-input soft-output (SISO) differential detection algorithm is proposed for amplify-and-forward (AF) over time-varying relaying channels based cooperative communications system. Furthermore, maximum-likelihood (ML) detector for M-ary differential Phase-shift keying (DPSK) is derived to calculate a posteriori probabilities (APP) of information bits. In addition, when the SISO is exploited in conjunction with channel decoding, iterative detection and decoding approach by exchanging extrinsic information with outer code is obtained. Finally, simulation results show that the proposed non-coherent approach improves detection performance significantly. In particular, the system can obtain greater performance gain under fast-fading channels.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.3
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• pp.747-752
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• 1996

In this paper, we propose a new SO-MLSE(soft-output maximum likelihood sequence estimation) equalizer, which can be used in GSM digital cellular system) it uses complex correlation of training sequence to obtain the channel information and the equalization is performed by MLSE using Viterbi algorithm. In order to generate a soft-decision input to channel decoder (Viterbi decoder), the soft-output equalization algorithm is needed. The adopted algorithm doesn't require to modify the structure of HO-MLSE(hard output MLSE) equalizer, that is, SO-MLSE equalizer can be implemented by adding soft-output generation block to HO-MLSE equalizer. This algorithm uses the outputs of matched filter and HO-MLSE equalizer. It turns out that the complexity of proposed SO-MLSE equalizer is simpler than those of other SO-MLSE equalizer and its perforance is almost the same as those of others. Finally, the proposed SO-MLSE equalizer is also implemented s a prototype with ADSP-2101 16-bits fixed point digital signal processing chip.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.6A
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• pp.611-616
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• 2006

In this paper, we propose a practical implementation method of a soft bit decision expression for an R-QAM (Gray coded Rectangular Quadrature Amplitude Modulation) signal based on the Max-Log-MAP algorithm. The parameters of the soft decision expression for the practical implementation can be obtained with simple arithmetic functions associated with some deterministic parameters such as a received value, distances between symbols, and the order of modulation on a signal space. Also, we analyze the performance of an iterative decoding scheme for the QAM signal with I/Q phase unbalance. The unbalance results from the non-ideal characteristic of components such as a phase shifter between in-phase and quadrature paths for quadrature modulator/demondulator.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.1
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• pp.21-28
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• 2004

In this paper we apply block turbo coding at the transmitter and iterative decoding algorithm at the receiver for different operating modes, based on the 5 ㎓ IEEE 802.1 la WLAN system, instead of convolutional coding and soft decision viterbi algorithm to improve forward error correcting performance. Experimental results showed that each coding scheme outperforms coding gains of up to 3.5 ㏈ at the BER of 10$\^$-3/.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.805-807
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• 2018

본 논문은 인공 대역 확장에서 스펙트럼 포락선 확장 시 발생하는 스펙트럼 왜곡을 줄이는 개선된 조합 매핑(Improved combined mapping) 알고리즘을 제안한다. 벡터양자화를 기반으로 하는 코드북 매핑(Codebook mapping)과 스펙트럼 포락선(Spectrum Envelope)의 선형 의존도를 이용한 선형 매핑(Linear mapping)을 사용하여 각각 확장된 광대역 LSP(Line Spectrum Pair)를 추론하고, 연판정(Soft-decision)을 통해 최적화된 LSP를 추론한다. 제안된 알고리즘으로 합성된 음성신호의 스펙트럼 왜곡(Spectrum Distortion)이 기존 조합매핑으로 얻은 음성 신호의 스펙트럼 왜곡보다 더 적은 왜곡을 갖는 결과를 나타내었다.

• Advanced Industrial SCIence
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• v.3 no.2
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• pp.1-7
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• 2024

This paper deals with the topic of quantification of soft power through emotional analysis. Sentiment analysis refers to the process of detecting and analyzing emotions or emotions in various data such as text, voice, and images. Therefore, in this paper, we explored the methodology and significance of how soft power can be quantified through emotional analysis. Soft power refers to the ability of a country or organization to influence the behavior of another country or organization in a desired direction. It is built by soft factors such as culture, values, and political system rather than military or economic means. Additionally, sentiment analysis is being used as a useful tool to measure and understand these soft areas.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1132-1136
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• 2005

In this paper, adaptive equalizer receiver for a turbo code direct sequence code division multiple access (DSCDMA) by using least mean square (LMS) adaptive algorithm is presented. The proposed adaptive equalizer is using soft output of decision feedback adaptive equalizer (DFE) to examines the output of the equalizer and the Log- maximum a posteriori (Log-MAP) algorithm for the turbo decoding process of the system. The objective of the proposed equalizer is to minimize the bit error rate (BER) of the data due to the disturbances of noise and intersymbol interference (ISI)phenomenon on the channel of the DS-CDMA digital communication system. The computer program simulation results shown that the proposed soft output decision feedback adaptive equalizer provides a good BER than the others one such as conventional adaptive equalizer, infinite impulse response adaptive equalizer.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1489-1502
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• 2019

This work introduces a novel unweighted combination method (UCSS) for business failure perdition (BFP). With considering features of BFP in the age of big data, UCSS integrates the quantitative and qualitative analysis by utilizing soft set theory (SS). We adopt the conventional expert system (ES) as the basic qualitative classifier, the logistic regression model (LR) and the support vector machine (SVM) as basic quantitative classifiers. Unlike other traditional combination methods, we employ soft set theory to integrate the results of each basic classifier without weighting. In this way, UCSS inherits the advantages of ES, LR, SVM, and SS. To verify the performance of UCSS, it is applied to real datasets. We adopt ES, LR, SVM, combination models utilizing the equal weight approach (CMEW), neural network algorithm (CMNN), rough set and D-S evidence theory (CMRD), and the receiver operating characteristic curve (ROC) and SS (CFBSS) as benchmarks. The superior performance of UCSS has been verified by the empirical experiments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1061-1066
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• 2014

Transmission characteristics of the sound propagation is very complicate and sparse in shallow water. To increase the performance of underwater acoustic communication system, lots of channel estimation technique has been proposed. In this paper, we proposed the channel estimation based on LMS(Least Mean Square) algorithm which has faster convergence speed than conventional sparse-aware LMS algorithms. The proposed method combines $L_p$-norm LMS with soft decision process. Simulation was performed by using the sound velocity profile which acquired in real sea trial. As a result, we confirmed that the proposed method shows the improved performance and faster convergence speed than conventional methods.