• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.18 no.3
• /
• pp.318-326
• /
• 1993

It is not easy to diagnose rapidly the cause of trouble in the signal service which is currently provided by the fully electronic switching system such as TDX. To solve these problems, it is necessary to acquire and analyze the service signal. This paper describes the development of PCM acquirer which can analyze the signal characteristics by acquiring the PCM signal in SHW(subhighway). Also an algorithm which analyzes the acquired signal and determines the signal frequency si discussed by using CZT.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.10 no.3
• /
• pp.143-149
• /
• 2014

This paper is on the blind signal separation(BSS) method by the geometric method. To separate the signal sources, we use Hough transform and BSS. Hough transform is a geometric method which let us know the local informations of the signal. We find the orientations of signals by Hough transform and know the number of signal sources. When the number of sensors is more than the number of sources. the BSS algorithm can separate the mixtures well in the time domain. This algorithm has a good performance in converging fast. We had checked up the quality of the algorithm after separating the mixed signals. The results of simulations show that this BSS method has the abnormal waveforms due to unconverging coefficients in the beginning, and stably has the separated waveforms which almost equal to the sources in the most period.

• Journal of the Korean Institute of Navigation
• /
• v.20 no.3
• /
• pp.85-95
• /
• 1996

In the velocimeter, the ultrasonic pulse signal is used for measuring the profile velocity of moving targets distributed in space because of the merits of its high distance resolution and harmless affect to the human body. The velocity reading in conventional ultrasonic pulsed velocimeter depends on the wave pattern reflecting the spatial distribution of scatters and includes observational error due to the signal processing of analyzing pulse signal. In this paper, we evaluate an influence of the received waveform of pulsed signal on the velocity information by setting a model. Subsequently, in order to improve the distance resolution and to obtain precise velocity information without the influence of the spatial distribution of scatterers, we propose a new method for the analysis of Doppler pulsed signal, in which the pulsed signal is transformed into a phase function with local data. Finally, it is confirmed that the performance of the velocimeter is more improved in the proposed method than in the conventional one.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.17 no.6
• /
• pp.572-579
• /
• 1992

In this thesis, feedback circuit and FM detector applied to superheterodyne receiver to extract audio signal without random noise Is implemented. The feedback loop circuit converts 45MHz received signal to 4SiKHz If signal containing mess-age without random noise. Also the feedback loop provides the End local frequency, so narrowband BPF which is containing maximum Doppler frequency without message Is needed. Finally, quadrature FM detector extract audio signal by synthesis o350" shifted signal and ampli-tude limited signal. RSSI characteristics is measured and audio characteristics Is compared with existing If module.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.13 no.4
• /
• pp.332-339
• /
• 1988

Using a generalized observation model, in which one can express the effects of non-additive noise such as signal-dependent noise and multiplicative noise in addition to purely-additive noise, the problem of weak random-signal detection is investigated. It is shown that the test statistics of locally optimum detectors for detection of weak random signals in signal-dependent noise model are interesting extensions of those in purely-additive noise model. This result is a complement to the result for weak random-signal detction in multiplicative noise model.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.10 no.1
• /
• pp.131-138
• /
• 2014

This paper is on a stereo acoustic echo canceller with the blind signal separation for post processing. The convergence speed of the stereo acoustic echo canceller is deteriorated due to mixing two residual signals which are update signals of each echo canceller. To solve this problem, we are to use the blind signal separation(BSS) method separating the mixed signals after the echo cancellers. The blind signal separation method can extracts the source signals by means of the iterative computations with two input signals. We had verified performances of the proposed acoustic echo canceller for stereo through simulations. The results of simulations show that the acoustic echo canceller for stereo using this algorithm operates stably without divergence in the normal state. And, when the speech signals were inputted, this echo canceller achieved about 2dB higher ERLE with the BSS post processing method than without this method. This stereo echo canceller showed the best performance in the case of inputting the real voice signal.

• Proceedings of the IEEK Conference
• /
• summer
• /
• pp.27-30
• /
• 2004

OFDMA is considered as one of the major candidates for broadband wireless access. The OFDMA signal is usually coherently demodulated, requiring the channel estimation which can be estimated using a known pilot signal. In multi-cell environment, the performance of channel estimation is mainly limited by intercell interference. It is desirable to use a pilot signal that can estimate the channel information robust to the intercell interference in the OFDMA uplink system. In this paper, we consider two types of pilot signal applicable to multi-cell OFDMA uplink systems: One is time-multiplexed pilot signal and the other is code­multiplexed pilot signal. Simulation results show that the code-multiplexed pilot is suitable for low mobility environment and time-multiplexed pilot is suitable for high mobility environment.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.8 no.3
• /
• pp.125-131
• /
• 2012

This paper is on a stereo acoustic echo canceller with the blind signal separation. The convergence speed of the stereo acoustic echo canceller is deteriorated due to mixing two residual signals in the update signal of each echo canceller. To solve this problem, we are to use the blind signal separation(BSS) method separating the mixed signals. The blind signal separation method can extracts the source signals by means of the iterative computations with two input signals. We had verified performances of the proposed acoustic echo canceller for stereo through simulations. The results of simulations show that the acoustic echo canceller for stereo using this algorithm operates stably without divergence in the normal state. And, when the speech signals were inputted, this echo canceller achieved about 3dB higher ERLE in the case of using the BSS algorithm than the case of not using the BSS algorithm. But this echo canceller didn't get good performances in the case of inputting the white noises as stereo signals.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.17 no.4
• /
• pp.85-94
• /
• 2021

The LPR system's trigger sensor makes problem occasionally due to the heave weight of vehicle or the obsolescence equipment. If we replace the hardware sensor to the deep-learning based software sensor in order to generate the trigger signal, LPR system maintenance would be a lot easier. In this paper we proposed the deep-learning sliding window based object detection and tracking algorithm for the LPR system's trigger signal generation. The gate passing vehicle's license plate recognition results are combined into the normal tracking algorithm to catch the position of the vehicle on the trigger line. The experimental results show that the deep learning sliding window based trigger signal generating performance was 100% for the gate passing vehicles including the 5.5% trigger signal position errors due to the minimum bounding box location errors in the vehicle detection process.

• Journal of the Semiconductor & Display Technology
• /
• v.23 no.1
• /
• pp.61-64
• /
• 2024

As research on autonomous driving technology becomes more active, various studies on signal recognition of traffic lights are also being conducted. When recognizing traffic lights with different purposes and shapes, such as pedestrian traffic lights, vehicle-only traffic lights, and right-turn traffic lights, existing classification methods may cause misrecognition problems. Therefore, in this study, we studied a model that allows accurate signal recognition by subdividing the classification of signals according to the purpose and type of traffic lights. A signal recognition model was created by classifying traffic lights according to their shape and purpose into horizontal, vertical, right turn, etc., and by comparing them with the existing signal recognition model based on YOLOv5, it was confirmed that more correct and accurate recognition was possible.