• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.7
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• pp.1028-1035
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• 1993

The signed regressor (SR) algorithm employs one bit quantization on the input regressor (or tap input) in such a way that the quantized input sequences become +1 or -1. The algorithm is computationally more efficient by nature than the popular least mean square (LMS) algorithm. The behavior of the SR algorithm unfortunately is heavily dependent on the characteristics of the input signal, and there are some Inputs for which the SR algorithm becomes unstable. It is known, however, that such a stability problem does not take place with the SR algorithm when the input signal is Gaussian, such as in the case of speech processing. In this paper, we explore a statistical analysis of the SR algorithm. Under the assumption that signals involved are zero-mean and Gaussian, and further employing the commonly used independence assumption, we derive a set of nonlinear evolution equations that characterizes the mean and mean-squared behavior of the SR algorithm. Experimental results that show very good agreement with our theoretical derivations are also presented.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.1
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• pp.121-127
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• 2010

This paper relates with the improved CMA blind adaptive equalization algorithm which uses the constellation matching method that improve the inverse modelling efficiency of a communication channel compared to the present CMA blind adaptive equalizer. The amplitude distortion can be compensated in the present CMA blind adaptive equalizer which is used for the reduction of intersymbol interference by distortion that generate such as a band limited wireless mobile channel, but in the improved adaptive alogorithm operates with the minimize the amplitude phase distortion in the output of equalizer by applying the cost function that is composition of additional signal constellation matching error terms. In order to evaluation of the inverse modeling efficiency of improved algorithm, the residual intersymbol interference and recovered signal constellation were compared by computer simulation. As a result of comparion of computer simulation, the improved algorithm has a good stability in the residual intersymbol interference in the steady state, but it has a slow convergence rate in the adaptation state in initial state.

• Journal of Korean Society of Transportation
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• v.28 no.6
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• pp.75-84
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• 2010

Controlled traffic intersection is critical point in terms of transportation network performance, where the most of traffic congestion arises. One of the most important and favorable measure of effectiveness in the signal controlled intersection is approach delay. Although lots of efforts to develop traffic delay estimation models have been made throughout the years, most of them were focusing on homogeneous traffic flow. The purpose of this research is to develop a traffic delay estimation model for traffic flow mixed with bus based on the horizontal shockwave theory. Traffic simulation is performed to test the adaptation level of the model in generic environment. The result shows that the delay increases with increasing bus traffic. Overall model accuracy comparing simulation result is acceptable, that shows the error range around 10 percent.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.12
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• pp.1337-1344
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• 2014

The objective of an echo canceller connected to any end of a communication line such as digital subscriber line (DSL) is to compensate the outgoing transmit signal in the receiving path that the hybrid circuit leaks. The echo canceller working in a full duplex environment is an adaptive system driven by the local signal. Conventional echo canceller that implement the least mean square (LMS) algorithm provides a low computational burden but poor convergence properties. The length of the echo canceller will directly affect both the degree of performance and the convergence speed of the adaptation process. To cancel long time-varying echoes, the number of tap coefficients of a conventional echo canceller must be large, which decreases the convergence speed of the adaptive filter. This paper proposes an alternative technique for the echo cancellation in a telecommunication channel. The new technique employs the bi-directional least mean square (LMS) algorithm for adaptively computing the optimal set of the coefficients of the echo canceller, which is composed of weighted combination of both feedforward and feedback algorithms. Finally, Simulation results as well as mathematical analysis demonstrates that the proposed echo canceller has faster convergence speed than the conventional LMS echo canceller with nearly equivalent complexity of computation.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.2
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• pp.28-38
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• 2001

Traffic information can be broadly categorized into point information and spatial information. Point information can be obtained by chocking only the presence of vehicles at prespecified points(small area), whereas spatial information can be obtained by monitoring large area of traffic scene. To obtain spatial information by image processing, we need to track vehicles in the whole area of traffic scene. Image detector system based on global tracking consists of video input, vehicle detection, vehicle tracking, and traffic information measurement. For video input, conventional approaches used auto iris which is very poor in adaptation for sudden brightness change. Conventional methods for background generation do not yield good results in intersections with heave traffic and most of the early studies measure only point information. In this paper, we propose user-controlled iris method to remedy the deficiency of auto iris and design flame difference-based background generation method which performs far better in complicated intersections. We also propose measurement method for spatial traffic information such as interval volume/lime/velocity, queue length, and turning/forward traffic flow. We obtain measurement accuracy of 95%∼100% when applying above mentioned new methods.

• Journal of Microbiology and Biotechnology
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• v.22 no.1
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• pp.84-91
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• 2012

Two staphylococcal lipases were obtained from Staphylococcus epidermidis S2 and Staphylococcus aureus S11 isolated from sebaceous areas on the skin of the human face. The molecular mass of both enzymes was estimated to be 45 kDa by SDS-PAGE. S2 lipase displayed its highest activity in the hydrolysis of olive oil at $32^{\circ}C$ and pH 8, whereas S11 lipase showed optimal activity at $31^{\circ}C$ and pH 8.5. The S2 lipase showed the property of cold-adaptation, with activation energy of 6.52 kcal/mol. In contrast, S11 lipase's activation energy, at 21 kcal/mol, was more characteristic of mesophilic lipases. S2 lipase was stable up to $45^{\circ}C$ and within the pH range from 5 to 9, whereas S11 lipase was stable up to $50^{\circ}C$ and from pH 6 to 10. Both enzymes had high activity against tributyrin, waste soybean oil, and fish oil. Sequence analysis of the S2 lipase gene showed an open reading frame of 2,067 bp encoding a signal peptide (35 aa), a pro-peptide (267 aa), and a mature enzyme (386 aa); the S11 lipase gene, at 2,076 bp, also encoded a signal peptide (37 aa), pro-peptide (255 aa), and mature enzyme (399 aa). The two enzymes maintained amino acid sequence identity of 98-99% with other similar staphylococcal lipases. Their microbial origins and biochemical properties may make these staphylococcal lipases isolated from facial sebaceous skin suitable for use as catalysts in the cosmetic, medicinal, food, or detergent industries.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.5
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• pp.543-548
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• 2014

Multiple-model based speech recognition framework (MMSR) has been known to be very successful in speech recognition. Since it uses multiple hidden Markov modes (HMMs) that corresponds to various noise types and signal-to-noise ratio (SNR) values, the selected acoustic model can have a close match with the test noisy speech. However, since the number of HMM sets is limited in practical use, the acoustic mismatch still remains as a problem. In this study, we experimentally determined the optimal SNR mapping between the test noisy speech and the HMM set to mitigate the mismatch between them. Improved performance was obtained by employing the SNR mapping instead of using the estimated SNR from the test noisy speech. When we applied the proposed method to the MMSR, the experimental results on the Aurora 2 database show that the relative word error rate reduction of 6.3% and 9.4% was achieved compared to a conventional MMSR and multi-condition training (MTR), respectively.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.2
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• pp.145-149
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• 2011

Recently, as the design of a system gets larger and more complex, functional verification method based on system-level becomes more important. The verification of a functional block mainly uses BFM(bus functional model). The larger the burden on functional verification is, the more the importance of configuring a proper verification environment increases rapidly. SystemVerilog unifies hardware design languages and verification languages in the form of extensions to the Veri log HDL. The processing of design description, function simulation and verification using same language has many advantages in system development. In this paper, we design DUT that is composed of AMBA bus and function blocks using SystemVerilog and verify the function of DUT in verification environment using layered testbench. Adaptive FIR filter and Booth's multiplier are chosen as function blocks. We confirm that verification environment can be reused through a minor adaptation of interface to verify functions of other DUT.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.101-106
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• 2016

This paper proposes the SU-SE-MMA algorithm which applying the concept of selective updaing to the SE-MMA that is possible to reduce the intersymbol interference due to distortion occurred at the channel when transmit the nonconstant modulus 16-QAM signal. The SE-MMA emerged for the simplifying the computational operation from the current MMA adaptation algorithm, then it's has the fast convergence speed and has a problem of increase the residual component in the steady state. The SU-SE-MMA performs the selectively tap updating when the distance of equalizer output and specified transmit signal point is greater than the given threshold value and tap updaing does not occurred in the small distance. By this selective updating process, it is possible to more reduction in the computational operation in the propose algorithm. The improved adaptive equalization performance of SU-SE-MMA like as the equalizer output signal constellation, residual isi, MD, SER were confirmed by computer simulation compared to SE-MMA. As a result of simulation, the AV-SE-MMA has better performance in output signal constellation, residual isi and MD compared to the SE-MMA, but it was confirmed that the AV-SE-MMA has similar in the SER performance that means the robustness to the noise.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.1
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• pp.49-55
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• 2002

A decrease in the birthrate and aging are progressing in Japan and several countries. In that society, it is important that physically weak persons such as elderly persons are able to take care of themselves. We have been developing exoskeletal robots for human (especially for physically weak persons) motion support. In this study, the controller controls the angular position and impedance of the exoskeltal robot system using multiple fuzzy-neuro controllers based on biological signals that reflect the human subject's intention. Skin surface electromyogram (EMG) signals and the generated wrist force by the human subject during the elbow motion have been used as input information of the controller. Since the activation level of working muscles tends to vary in accordance with the flexion angle of elbow, multiple fuzzy-neuro controllers are applied in the proposed method. The multiple fuzzy-neuro controllers are moderately switched in accordance with the elbow flexion angle. Because of the adaptation ability of the fuzzy-neuro controllers, the exoskeletal robot is flexible enough to deal with biological signal such as EMG. The experimental results show the effectiveness of the proposed controller.