• Journal of the Institute of Convergence Signal Processing
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• v.4 no.3
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• pp.7-14
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• 2003

MPEG-1 audio standard is the algorithm for the compression of high-qualify digital audio signals. The standard dictates the functions of encoder and decoder pair, and includes three different layers as the complexity and the performance of the encoder and decoder. In this paper, we implemented the real-time system of MPEG-1 audio layer III decoder(MP3) with the TMS320C541 fixed point DSP chip. MP3 algorithm uses psycho-acoustic characteristic of human hearing system, and it reduces the amount of data with eliminating the signals hard to be heard to the hearing system of human being. It is difficult to implement MP3 decoder with fixed Point DSP because of it's broad dynamic range. We implemented realtime system with fixed DSP chip by using weighted look-up tables to reduce the amount of calculation and solve the problem of broad dynamic range.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.4
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• pp.174-179
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• 2018

Currently, various security technologies such as fingerprint recognition and face recognition are being developed. However, although many technologies have been developed, the field of incorporating technologies is quite limited. In particular, it is easy to adapt modern security technologies into existing digital systems, but it is difficult to introduce new digital technologies in systems using analog systems. However, if the system can be widely used, it is worth replacing the analog system with the digital system. Therefore, the selected topic is the electronic attendance system. In this paper, a camera is installed to a door to perform a Haar-like feature training for face detecting and real-time face recognition with a Eigenface in principal component analysis(PCA) based face recognition using raspberry pi. The collected data was transmitted to the smartphone using wireless communication, and the application for the viewer who can receive and manage the information on the smartphone was completed.

• Journal of Navigation and Port Research
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• v.29 no.1 s.97
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• pp.91-96
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• 2005

The National Marine Electronics Association(NMEA) is nonprofit-making cooperation composed with manufacturers, distributors, wholesalers and educational institutions. We use the basic port of equipment in order to process the signal from NMEA signal using equipment. When we don't have enough one, we use the multi-port for processing. However, we need to have module development simulation which could multiplex and provide NMEA related signal that we could solve the problems in multi-port application and exclusive equipment generation for a number of signal. For now, we don't have any case or product using NMEA multiplexer so that we import expensive foreign equipment or embody NMEA signal transmission program like software, using multi-port. These have problems since we have to pay lots ci money and build separate processing part for every application programs. Besides, every equipment generating NMEA signal are from different manufactures and have different platform so that it could cause double waste and loss of recourse. For making up for it, I suggest the NMEA multiplexer embodiment, which could independently move by reliable process and high performance single hardware module, improve the memory efficiency of module by designing the optimized Queue, and keep having reliability for realtime communication among the equipment such as main input sensor equipment Gyrocompass, Echo-sound, and GPS.

• The KIPS Transactions:PartC
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• v.9C no.2
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• pp.283-292
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• 2002

This paper develops a scheme of resource management for guaranteeing QoS of realtime traffic in wireless mobile internet environments Mobile terminal has significant impact on the QoS originating mobility provided to a real-time application. The currently proposed MRSVP is not clear the boundary of resource reservation tregion and also can give rise to signal overhead to maintain sessions. To solve above problem, we propose the new reservation protocol, mobile cluster based H-MRSVP to combine MRSVP with moving cluster concept. In this paper, we analytically design our model for guaranteeing the QoS of realtime traffic and compare the three schemes: guard channel allocation schemes, DCA and our model. The performance measures are the probabilities of new call blocking, handoff dropping, resource utilization and service completion versus the system offered Erlang load. Consequently, Simulation indicate our model is more flexible than DCA in a view pint of channel utilization and gains the advantage over guard channel scheme with respects to the mobility.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.7C
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• pp.962-970
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• 2004

This paper presents an efficient implementation of the 2.4 kbps EHSX(Enhanced Harmonic Stochastic Excitation) speech coder on a TMS320C6701$^{TM}$ floating-point digital signal processor. The EHSX speech codec is based on a harmonic and CELP(Code Excited Linear Prediction) modeling of the excitation signal respectively according to the frame characteristic such as a voiced speech and an unvoiced speech. In this paper, we represent the optimization methods to reduce the complexity for real-time implementation. The complexity in the filtering of a CELP algorithm that is the main part for the EHSX algorithm complexity can be reduced by converting program using floating-point variable to program using fixed-point variable. We also present the efficient optimization methods including the code allocation considering a DSP architecture and the low complexity algorithm of harmonic/pitch search in encoder part. Finally, we obtained the subjective quality of MOS 3.28 from speech quality test using the PESQ(perceptual evaluation of speech quality), ITU-T Recommendation P.862 and could get a goal of realtime operation of the EHSX codec.c.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.516-519
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• 2001

To diagnose a patient's blood vessel disease, apoplexy, hypertension, arteriosclerosis, the blood velocity is very important. Determining the blood velocity methods using ultrasound are Continuous Doppler System and Pulse Doppler System. In using the Pulse Doppler System, we can obtain the position of blood velocity. But it is more complex hardware than Continuous Doppler System and it has low SNR(signal-noise ratio). So in this study, to obtain a believable information we use the Continuous Pulse Doppler System. Thus system have analog part and digital part. In analog part is composed of ultrasound generating part, the amplifying part to amplify the received signal from ultrasound sensor, the demodulation part to detect blood velocity and the filtering part to remove the noise. In digital part is composed of the A/D conversion part, digital signal processing part, and the communication part to communicate the PC. In this study to implement efficient ultrasound blood velocity measurement system, we can get the patient's blood velocity information in realtime. Thus, It is a useful in the accurate diagnosis with C.T(computered tomography), M.R.I(magnetic resonance imaging).

• Journal of Digital Contents Society
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• v.19 no.6
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• pp.1207-1212
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• 2018

The ultrasound image uses ultrasonic pulses to receive the reflected waves and construct an image necessary for diagnosis. At this time, when the signal becomes weak, noise is generated and a slight difference in brightness occurs. In addition, fluctuation of image due to breathing phenomenon, which is the characteristic of ultrasound image, and change of motion in real time occurs. Such a noise is difficult to recognize and diagnose visually in the analysis process. In this paper, morphological features are automatically extracted by using image processing technique on ultrasound acquired images. In this paper, we implemented a GPU - based fast filter using a cloud big data processing platform for image processing. In applying the GPU - based high - performance filter, the algorithm was run with performance 4.7 times faster than CPU - based and the PSNR was 37.2dB, which is very similar to the original.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.176-180
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• 2004

The ST-segment that the beginning part of T wave is the important diagnostic parameter to finding myocardial ischemia. Abnormal ST appears in two types. One is the level change, and the other is the pattern change. In this paper, we describe the monitoring of abnormal ST using PC based system. Hardware of this system consists of transmitter, receiver and PC. The function of transmitter is measuring ECG in three channels which are selected manually and transmitting the data to receiver by digital radio way. Connection with receiver and PC is by RS232C, and the data received on the PC is analyzed automatically by ECG analysis algorithm and saved to file. In the algorithm part for detecting abnormal ST, ST-segments are approximated by a polynomial. This method can detect all of the deviation and pattern change of ST-segment regardless the change in the heart rate or sampling rate. To gain algorithm reliability, the method rejects distorted polynomial approximation by calculation the difference between the approximated ST-segment and original ST-segment. In pre-signal processing, the wavelet transformation separates high frequency bands including QRS complex from the original ECG. Consequently, the process improves the performance of detecting each feature points.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.4
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• pp.91-98
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• 2017

Previous works for detecting arrhythmia have mostly used nonlinear method such as artificial neural network, fuzzy theory, support vector machine to increase classification accuracy. Most methods require higher computational cost and larger processing time. Therefore it is necessary to design efficient algorithm that classifies PVC(premature ventricular contraction) and decreases computational cost by accurately detecting minimal feature point based on only R peak through optimal R wave. We propose an optimal R wave detection and PVC classification method through extracting minimal feature point in IoT environment. For this purpose, we detected R wave through optimal threshold value and extracted RR interval and R peak pattern from noise-free ECG signal through the preprocessing method. Also, we classified PVC in realtime through RR interval and R peak pattern. The performance of R wave detection and PVC classification is evaluated by using record of MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.758% in R wave detection and the rate of 93.94% in PVC classification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.8
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• pp.1947-1954
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• 2013

Previous works for detecting arrhythmia have mostly used nonlinear method such as artificial neural network, fuzzy theory, support vector machine to increase classification accuracy. Most methods require accurate detection of P-QRS-T point, higher computational cost and larger processing time. But it is difficult to detect the P and T wave signal because of person's individual difference. Therefore it is necessary to design efficient algorithm that classifies different arrhythmia in realtime and decreases computational cost by extrating minimal feature. In this paper, we propose arrhythmia detection based on binary coding using QRS feature varibility. For this purpose, we detected R wave, RR interval, QRS width from noise-free ECG signal through the preprocessing method. Also, we classified arrhythmia in realtime by converting threshold variability of feature to binary code. PVC, PAC, Normal, BBB, Paced beat classification is evaluated by using 39 record of MIT-BIH arrhythmia database. The achieved scores indicate the average of 97.18%, 94.14%, 99.83%, 92.77%, 97.48% in PVC, PAC, Normal, BBB, Paced beat classification.