• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.421-424
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• 2008

This paper proposes an adaptive noise suppression system based on human auditory model to enhance speech signal that is degraded by various background noises. The proposed system detects voiced and unvoiced sections for each frame and implements the adaptive auditory process, then reduces the noise speech signal using neural network including amplitude component and phase component. Base on measuring signal-to-noise ratios, experiments confirm that the proposed system is effective for speech signal that is degraded by various noises.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.472-477
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• 1996

This paper presents a new approachtothe design of adaptive control system using DSPs(TMS320C30) for robotic manipulators to achieve trajectory tracking by the joint angles. Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed control scheme, adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaaptive feedforward controller, feedback controller, and PID type time-varying auxillary control elements. The prpposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.143-160
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• 2001

Micro-simulation models have been recognized as an efficient assessment tool in developing traffic signal control technologies. In this paper a prototype of a microscopic simulation model which can be applied to evaluate the performance of traffic-adaptive signal control strategies was developed. In the simulation process, space-based arrays were appled to estimate parameters of car following and lane changing models. Two levels of link types, a micro-type and macro-type links, were also embodied in the simulation process. The proposed model was tested on a test network consists of 9 intersections. The performance of the proposed model was evaluated in link by link comparisons with the results of NETSIM. The results show that the proposed model could appropriately simulate traffic flows of the test network. The model also produces traffic adaptive signal timings, cycle lengths and green times for turning movements, based on the detector data. It implies that the optimization process of the model produces reasonable signal timings for the test network on the cycle basis.

• JSTS:Journal of Semiconductor Technology and Science
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• v.13 no.6
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• pp.608-616
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• 2013

This paper presents an adaptive sampling method for electrocardiogram (ECG) signal detection. First, by employing the strings matching process with compression dictionary, we recognize each segment of ECG with different characteristics. Then, based on the non-uniform sampling strategy, the sampling rate is determined adaptively. As the results of simulation indicated, our approach reconstructed the ECG signal at an optimized sampling rate with the guarantee of ECG integrity. Compared with the existing adaptive sampling technique, our approach acquires an ECG signal at a 30% lower sampling rate. Finally, the experiment exhibits its superiority in terms of energy efficiency and memory capacity performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.4
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• pp.652-657
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• 2009

This paper proposes an adaptive noise suppression system based on human auditory model to enhance speech signal that is degraded by various background noises. The proposed system detects voiced, unvoiced and silence sections for each frame and implements an adaptive auditory process, then reduces the noise speech signal using a neural network including amplitude component and phase component. Based on measuring signal-to-noise ratios, experiments confirm that the proposed system is effective for speech signal that is degraded by various noises.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.1
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• pp.138-149
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• 1994

This paper introduces a new monitoring technique which utilizes an adaptive signal processing for feature generation, coupled with a multilayered merual network for pattern recognition. The cutting force signal in face milling operation was modeled by a low order discrete autoregressive model, shere parameters were estimated recursively at each sampling instant using a parameter adaptation algorithm based on an RLS(recursive least square) method with discounted measurements. The influences of the adaptation algorithm parameters as well as some considerations for modeling on the estimation results are discussed. The sensitivity of the extimated model parameters to the tool state(new and worn tool)is presented, and the application of a multilayered neural network to tool state monitoring using the previously generated features is also demonstrated with a high success rate. The methodology turned out to be quite suitable for in-process tool wear monitoring in the sense that the model parameters are effective as tool state features in milling operation and that the classifier successfully maps the sensors data to correct output decision.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.366-368
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• 2006

Electronic warfare Support(ES) system measures pulse characteristics for received RF signals that received from all directions. ES system discriminates the pulse trains that have a rule, correlationship, continuance from collected data and analyze the characteristics of the data, and identify the emitters by comparison with emitter identification data(EID). Because pulse density is very high and various signal source exists at modem signal environments, high-speed and accurate signal analysis is needed for realtime countermeasure to emitters. Grouping alleviates the load of signal analysis process and supports reliable analysis. In this paper, we suggest an adaptive clustering scheme regarding signal patterns.

• Journal of information and communication convergence engineering
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• v.17 no.4
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• pp.285-289
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• 2019

A 1.9-GHz linear CMOS power amplifier is presented. An adaptive bias circuit (ABC) that utilizes an AC ground to detect the power level of the input signal is proposed to enhance the linearity and efficiency of the power amplifier. The ABC utilizes the second harmonic component as the input to mitigate the distortion of the fundamental signal. The input power level of the ABC was detected at the AC ground located at the V_DD node of the power amplifier. The output of the ABC was fed into the inputs of the power stage. The input signal distortion was mitigated by detecting the input power level at the AC ground. The power amplifier was designed using a 180 nm RFCMOS process to evaluate the feasibility of the application of the proposed ABC in the power amplifier. The measured output power and power-added efficiency were improved by 1.7 dB and 2.9%, respectively.

• The Journal of Korean Association of Computer Education
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• v.9 no.1
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• pp.61-70
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• 2006

In the area of e-learning education, SCORM2004 that is suggested by ADL and is a defacto standard allows to design and apply various interrelations among learning objects which organize learning process through consolidating IMS Simple Sequencing into S&N. In this paper, we intend to realize a web_based adaptive learning management that enable to guide experientially the learning activity through the SCORM 2004 S&N and the Traffic-Signal-Lamp Metaphor. This adaptive system allows professor to design the learning courseware realizing various learning strategies to be able to reuse same learning contents and student to be leaded a adaptive learning through being supplied immediately the state and evaluation of learning.

• Journal of Welding and Joining
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• v.16 no.6
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• pp.7-16
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• 1998