• Proceedings of the IEEK Conference
• /
• 2001.06a
• /
• pp.233-236
• /
• 2001

Orthogonal freqency division multiplexing (OFDM) is an attractive technique for achieving high-bit-rate wireless data transmission. However, the potentially large peak-to-average power ratio (PAPR) has limited its application; An OFDM signal with the large PAPR can cause power degradation (In-band distortion) and spectral spreading (Out-of-band distortion) by being clipped passing through a power amplifier. Thus, we propose the combining algorithm of Hadamard transform and phase shift, which is ascribed to the relation between the correlation of the IFFT input sequence function and PAPR. Extensive computer simulations show that the combining algorithm is an effective technique to reduce PAPR.

• Journal of Electrical Engineering and information Science
• /
• v.1 no.2
• /
• pp.101-108
• /
• 1996

A new speed controller based on the fuzzy algorithm with hierarchical structure is presented. The input variables of the controller are speed error and its derivative(change of error), where the output variable is the change of torque current command. Several comparisons were performed with conventional PI (proportional plus integral) controller and proposed controller. These controllers are applied to the laboratory model drive system with 2.2kW induction motor. Some simulation and experimental results show that the speed controller using fuzzy algorithm is more robust than the conventional PI controller.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.7
• /
• pp.119-124
• /
• 2015

Speech enhancement has been required as a preprocessor for a noise robust speech recognition system. Codebook-based Speech Enhancement (CBSE) is highly robust in nonstationary noise environments compared with conventional noise estimation algorithms. However, its performance is severely degraded for the codevector combinations that have lower correlation with the input signal since CBSE depends on the trained codebook information. To overcome this problem, only the reliable codevector combinations are selected to be used to remove the codevector combinations that have lower correlation with input signal. The proposed method produces the improved performance compared to the conventional CBSE in terms of Log-Spectral Distortion (LSD) and Perceptual Evaluation of Speech Quality (PESQ).

• Journal of the Korean Graphic Arts Communication Society
• /
• v.30 no.3
• /
• pp.1-11
• /
• 2012

According as the latest printing technology is converted from analogue to digital, life cycle of a printing technology is shortened and the existent printing companies were faced always in a new technology. Specially, way of foreign countries export opened because globalization of printing market is accelerated. But, printing buyers of advanced nation require standard printing process control. fect at product process step. Emphasized in IPA technical conference for past several years tendency about graphic art color proofing and technical analysis and comparison going through Color Proofing RoundUP. These researchers have developed a color management technology. A specially developed printing technology and reference characterization data brought certain high quality elevation in a graphic art proofing technology. When excessive GCR method application supervise printing, width of color conversion necks by requiring a lot of color conversions than proofing. But, these point is lacking relatively than a lot of effects that GCR gives. Therefore, correct interests of GCR algorithm and verification step to forecast beforehand result about actuality application are positively necessary. Therefore, this research forced into input file which is applied with different levels from input to print for printing optimization that consider standard printing with eco-friendly by method to solve these problem. And experimented using manuscript who GCR level is applied as is different in each field, and analyzed the result. Also, it is verification method by step to last printing from input file that solve been the various quality who generate in actuality field through these analysis result. ICC color management confirmed printing optimization process applying GCR algorithm improved to base.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.13 no.11
• /
• pp.5379-5388
• /
• 2012

In fuzzy modeling for nonlinear process, the fuzzy rules are typically formed by selection of the input variables, the number of space division and membership functions. The Generation of fuzzy rules for nonlinear processes have the problem that the number of fuzzy rules exponentially increases. To solve this problem, complex nonlinear process can be modeled by generating the fuzzy rules by means of fuzzy division of input space. Therefore, in this paper, rules of non-fuzzy inference systems are generated by partitioning the input space in the scatter form using HCM clustering algorithm. The premise parameters of the rules are determined by membership matrix by means of HCM clustering algorithm. The consequence part of the rules is represented in the form of polynomial functions and the consequence parameters of each rule are identified by the standard least-squares method. And lastly, we evaluate the performance and the nonlinear characteristics using the data widely used in nonlinear process. Through this experiment, we showed that high-dimensional nonlinear systems can be modeled by a very small number of rules.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.7
• /
• pp.3433-3446
• /
• 2019

Aiming at the high complexity of traditional single-channel demodulation algorithm for PCMA signals, a new demodulation algorithm based on neural network is proposed to reduce the complexity of demodulation in the system of non-cooperative PCMA communication. The demodulation network is trained in this paper, which combines the preprocessing module and decision module. Firstly, the preprocessing module is used to estimate the initial parameters, and the auxiliary signals are obtained by using the information of frequency offset estimation. Then, the time-frequency characteristic data of auxiliary signals are obtained, which is taken as the input data of the neural network to be trained. Finally, the decision module is used to output the demodulated bit sequence. Compared with traditional single-channel demodulation algorithms, the proposed algorithm does not need to go through all the possible values of transmit symbol pairs, which greatly reduces the complexity of demodulation. The simulation results show that the trained neural network can greatly extract the time-frequency characteristics of PCMA signals. The performance of the proposed algorithm is similar to that of PSP algorithm, but the complexity of demodulation can be greatly reduced through the proposed algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.22 no.6
• /
• pp.1160-1169
• /
• 1997

This paper presents an algorithm to separate vowels from consonants in Korean characters captured in noisy environment andto recognize them. The algorithm has been originally developed for recognition of the usage code (which is represented by a single Korean character) in the license plates of Korean vehicles. It, however, could be easily adopted to other applications with minor changes, in which character recognition is needed and the environment is noisy. The key ideas of the algorithm are to localize the vowels utilizing Hough transformation and to separate the vowels from consonants utilizing mathematical morphology. We observed that the presented algorithm effectively separates vowels even if the vowels and consonants are joined together after thresholding. We also observed that our algorithm outperforms some conventional algorithms especially when the input images are noisy. The details of the comparison study are presented in the paper.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.21 no.5
• /
• pp.1221-1229
• /
• 1996

This paper proposes a heuristic algorithm for low power implementation of combinational circuits. Selecting an input variable for a given function, the proposed algorithm performs Shannon exansion with respect to the variable to reduce the number of gates in the subcircuit realizing the coffactor function, reducting the power dissipation of the implemented circuit. experimental results for the MCNC benchmarks show that the proposed algorithm is effective by generating the circuits consuming the power 48.9% less on the average, when compared to the previous algorithm based on precomputation logic.

• The Journal of the Acoustical Society of Korea
• /
• v.17 no.1E
• /
• pp.36-43
• /
• 1998

A fuzzy logic filter is constructed from a set of fuzzy IF-THEN rules which change adaptively to minimize some criterion function as new information becomes available. This paper generalizes the fuzzy logic filter and it's adaptive filtering algorithm to include complex parameters and complex signals. Using the complex Stone-Weierstrass theorem, we prove that linear combinations of the fuzzy basis functions are capable of uniformly approximating and complex continuous function on a compact set to arbitrary accuracy. Based on the fuzzy basis function representations, a complex orthogonal least-squares (COLS) learning algorithm is developed for designing fuzzy systems based on given input-output pairs. Also, we propose an adaptive algorithm based on LMS which adjust simultaneously filter parameters and the parameter of the membership function which characterize the fuzzy concepts in the IF-THEN rules. The modeling of a nonlinear communications channel based on a complex fuzzy is used to demonstrate the effectiveness of these algorithm.