• Title/Summary/Keyword: 신호처리(signal processing)

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CNN based Complex Spectrogram Enhancement in Multi-Rotor UAV Environments (멀티로터 UAV 환경에서의 CNN 기반 복소 스펙트로그램 향상 기법)

  • Kim, Young-Jin;Kim, Eun-Gyung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.4
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    • pp.459-466
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    • 2020
  • The sound collected through the multi-rotor unmanned aerial vehicle (UAV) includes the ego noise generated by the motor or propeller, or the wind noise generated during the flight, and thus the quality is greatly impaired. In a multi-rotor UAV environment, both the magnitude and phase of the target sound are greatly corrupted, so it is necessary to enhance the sound in consideration of both the magnitude and phase. However, it is difficult to improve the phase because it does not show the structural characteristics. in this study, we propose a CNN-based complex spectrogram enhancement method that removes noise based on complex spectrogram that can represent both magnitude and phase. Experimental results reveal that the proposed method improves enhancement performance by considering both the magnitude and phase of the complex spectrogram.

Structure, Method, and Improved Performance Evaluation Function of SRCNN and VDSR (SRCNN과 VDSR의 구조와 방법 및 개선된 성능평가 함수)

  • Lee, Kwang-Chan;Wang, Guangxing;Shin, Seong-Yoon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.4
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    • pp.543-548
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    • 2021
  • The higher the resolution of the image, the higher the satisfaction of the viewers of the image, and the super-resolution imaging has a considerable increase in research value among the fields of computer vision and image processing. In this study, the main features of low-resolution image LR are extracted mainly using deep learning super-resolution models. It learns and reconstructs the extracted features, and focuses on reconstruction-based algorithms that generate high-resolution image HR. In this paper, we investigate SRCNN and VDSR in a super-resolution algorithm model based on reconstruction. The structure and algorithm process of the SRCNN and VDSR model are briefly introduced, and the multi-channel and special form are also examined in the improved performance evaluation function, and understand the performance of each algorithm through experiments. In the experiment, an experiment was performed to compare the results of the SRCNN and VDSR models with the peak signal-to-noise ratio and image structure similarity, so that the results can be easily judged.

Vibration Data Denoising and Performance Comparison Using Denoising Auto Encoder Method (Denoising Auto Encoder 기법을 활용한 진동 데이터 전처리 및 성능비교)

  • Jang, Jun-gyo;Noh, Chun-myoung;Kim, Sung-soo;Lee, Soon-sup;Lee, Jae-chul
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.27 no.7
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    • pp.1088-1097
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    • 2021
  • Vibration data of mechanical equipment inevitably have noise. This noise adversely af ects the maintenance of mechanical equipment. Accordingly, the performance of a learning model depends on how effectively the noise of the data is removed. In this study, the noise of the data was removed using the Denoising Auto Encoder (DAE) technique which does not include the characteristic extraction process in preprocessing time series data. In addition, the performance was compared with that of the Wavelet Transform, which is widely used for machine signal processing. The performance comparison was conducted by calculating the failure detection rate. For a more accurate comparison, a classification performance evaluation criterion, the F-1 Score, was calculated. Failure data were detected using the One-Class SVM technique. The performance comparison, revealed that the DAE technique performed better than the Wavelet Transform technique in terms of failure diagnosis and error rate.

Effective speech recognition system for patients with Parkinson's disease (파킨슨병 환자에 대한 효과적인 음성인식 시스템)

  • Huiyong, Bak;Ryul, Kim;Sangmin, Lee
    • The Journal of the Acoustical Society of Korea
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    • v.41 no.6
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    • pp.655-661
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    • 2022
  • Since speech impairment is prevalent in patients with Parkinson's disease (PD), speech recognition systems suitable for these patients are needed. In this paper, we propose a speech recognition system that effectively recognizes the speech of patients with PD. The speech recognition system is firstly pre-trained with the Globalformer using the speech data from healthy people, and then fine-tuned using relatively small amount of speech data from the patient with PD. For this analysis, we used the speech dataset of healthy people built by AI hub and that of patients with PD collected at Inha University Hospital. As a result of the experiment, the proposed speech recognition system recognized the speech of patients with PD with Character Error Rate (CER) of 22.15 %, which was a better result compared to other methods.

Design of 32-bit Floating Point Multiplier for FPGA (FPGA를 위한 32비트 부동소수점 곱셈기 설계)

  • Xuhao Zhang;Dae-Ik Kim
    • The Journal of the Korea institute of electronic communication sciences
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    • v.19 no.2
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    • pp.409-416
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    • 2024
  • With the expansion of floating-point operation requirements for fast high-speed data signal processing and logic operations, the speed of the floating-point operation unit is the key to affect system operation. This paper studies the performance characteristics of different floating-point multiplier schemes, completes partial product compression in the form of carry and sum, and then uses a carry look-ahead adder to obtain the result. Intel Quartus II CAD tool is used for describing Verilog HDL and evaluating performance results of the floating point multipliers. Floating point multipliers are analyzed and compared based on area, speed, and power consumption. The FMAX of modified Booth encoding with Wallace tree is 33.96 Mhz, which is 2.04 times faster than the booth encoding, 1.62 times faster than the modified booth encoding, 1.04 times faster than the booth encoding with wallace tree. Furthermore, compared to modified booth encoding, the area of modified booth encoding with wallace tree is reduced by 24.88%, and power consumption of that is reduced by 2.5%.

Acoustic range estimation of underwater vehicle with outlier elimination (특이값 제거 기법을 적용한 수중 이동체의 음향 거리 추정)

  • Kyung-won Lee;Dan-bi Ou;Ki-man Kim;Tae Hyeong Kim;Heechang Lee
    • The Journal of the Acoustical Society of Korea
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    • v.43 no.4
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    • pp.383-390
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    • 2024
  • When measuring the radiated noise of an underwater vehicle, the range information between the vehicle and the receiver is an important factor, but since Global Positioning System (GPS) is not available in underwater, an alternative method is needed. As an alternative, the range is measured by estimating the arrival time, arrival time difference, and arrival frequency difference using a separate acoustic signal. However, errors occur due to the channel environment, and these outliers become obstacles in continuously measuring range. In this paper, we propose a method to reduce errors by curve fitting with a function in the form of a V-curve as a post-processing to remove outliers that occurred in the process of measuring range information. Simulation, lake and sea trials were conducted to verify the performance of the proposed method. In the results of the lake trial, the range estimation error was reduced by about 85 % from the Root Mean Square Error (RMSE) point of view.

Effects of Antenna Modeling in 2-D FDTD Simulation of an Ultra-Wide Band Radar for Nondestructive Testing of a Concrete Wall (콘크리트 벽의 비파괴검사를 위한 초광대역 레이더의 2차원 FDTD 시뮬레이션에서 안테나 모델링의 영향)

  • Joo, Jeong-Myeong;Hong, Jin-Young;Shin, Sang-Jin;Kim, Dong-Hyeon;Oh, Yisok
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.24 no.1
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    • pp.98-105
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    • 2013
  • This paper presents a finite-difference time-domain(FDTD) simulation and a data processing technique for radar sensing of the internal structure of a wall using an ultra-wide band antenna. We first designed an ultra-wide band anti-podal vivaldi antenna with a frequency range of 0.3~7 GHz which is chosen to be relatively low after considering the characteristics of wave attenuation, wall penetration, and range resolution. In this study the two-dimensional FDTD technique was used to simulate a wall-penetration-radar experiment under practical conditions. The next, the measured radiation pattern of the practical antenna is considered as an equivalent source in the FDTD simulation, and the reflection data of a concrete wall and targets are obtained by using the simulation. Then, a data processing technique has been applied to the FDTD reflection data to get a radar image for remote sensing of the internal structure of the wall. We compared the two different source excitations in the FDTD simulation; (1) commonly-used isotropic point sources and (2) polynomial curve fitting sources of the measured radiation pattern. As a result, when we apply the measured antenna pattern into the FDTD simulation, we could obtain about 2.5 dB higher signal to noise level than using a plane wave incidence with isotropic sources.

Does sports intelligence, the ability to read the game, exist? A systematic review of the relationship between sports performance and cognitive functions (게임을 읽는 머리, 스포츠 지능이 존재하는가? 스포츠 수행과 관련된 인지기능에 관한 문헌고찰)

  • Yongtawee, Atcharat;Park, Jin-Han;Woo, Min-Jung
    • Journal of the Korea Convergence Society
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    • v.12 no.3
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    • pp.325-339
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    • 2021
  • The purpose of the study is to examine sports-related cognitive functions through a systematic review and to suggest effective instruments to measure the cognitive functions. The present study was conducted based on the systematic review and meta-analysis protocol-the PRISMA. Of 429 articles searched through keywords from 2008 to 2020, 45 articles that met the selection criteria were analyzed. It was revealed that athletes had better cognitive functions than non-athletes, that the higher the sports expertise was, the higher the cognitive functions, and that there were differences in cognitive functions according to the sport types. The primary cognitive functions related to sports performance summarized as executive functions (inhibition ability, cognitive flexibility), information processing speed, spatial ability, and attention. As tasks for measuring each cognitive function, a stop signal task for inhibition ability, a design flexibility task for cognitive flexibility, a simple and choice reaction time test for information processing, a mental rotation task for spatial ability, and an attention network test for attention are appropriate.

Machine Learning-based Phase Picking Algorithm of P and S Waves for Distributed Acoustic Sensing Data (분포형 광섬유 센서 자료 적용을 위한 기계학습 기반 P, S파 위상 발췌 알고리즘 개발)

  • Yonggyu, Choi;Youngseok, Song;Soon Jee, Seol;Joongmoo, Byun
    • Geophysics and Geophysical Exploration
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    • v.25 no.4
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    • pp.177-188
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    • 2022
  • Recently, the application of distributed acoustic sensors (DAS), which can replace geophones and seismometers, has significantly increased along with interest in micro-seismic monitoring technique, which is one of the CO2 storage monitoring techniques. A significant amount of temporally and spatially continuous data is recorded in a DAS monitoring system, thereby necessitating fast and accurate data processing techniques. Because event detection and seismic phase picking are the most basic data processing techniques, they should be performed on all data. In this study, a machine learning-based P, S wave phase picking algorithm was developed to compensate for the limitations of conventional phase picking algorithms, and it was modified using a transfer learning technique for the application of DAS data consisting of a single component with a low signal-to-noise ratio. Our model was constructed by modifying the convolution-based EQTransformer, which performs well in phase picking, to the ResUNet structure. Not only the global earthquake dataset, STEAD but also the augmented dataset was used as training datasets to enhance the prediction performance on the unseen characteristics of the target dataset. The performance of the developed algorithm was verified using K-net and KiK-net data with characteristics different from the training data. Additionally, after modifying the trained model to suit DAS data using the transfer learning technique, the performance was verified by applying it to the DAS field data measured in the Pohang Janggi basin.

Modeling of Sensorineural Hearing Loss for the Evaluation of Digital Hearing Aid Algorithms (디지털 보청기 알고리즘 평가를 위한 감음신경성 난청의 모델링)

  • 김동욱;박영철
    • Journal of Biomedical Engineering Research
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    • v.19 no.1
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    • pp.59-68
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    • 1998
  • Digital hearing aids offer many advantages over conventional analog hearing aids. With the advent of high speed digital signal processing chips, new digital techniques have been introduced to digital hearing aids. In addition, the evaluation of new ideas in hearing aids is necessarily accompanied by intensive subject-based clinical tests which requires much time and cost. In this paper, we present an objective method to evaluate and predict the performance of hearing aid systems without the help of such subject-based tests. In the hearing impairment simulation(HIS) algorithm, a sensorineural hearing impairment medel is established from auditory test data of the impaired subject being simulated. Also, the nonlinear behavior of the loudness recruitment is defined using hearing loss functions generated from the measurements. To transform the natural input sound into the impaired one, a frequency sampling filter is designed. The filter is continuously refreshed with the level-dependent frequency response function provided by the impairment model. To assess the performance, the HIS algorithm was implemented in real-time using a floating-point DSP. Signals processed with the real-time system were presented to normal subjects and their auditory data modified by the system was measured. The sensorineural hearing impairment was simulated and tested. The threshold of hearing and the speech discrimination tests exhibited the efficiency of the system in its use for the hearing impairment simulation. Using the HIS system we evaluated three typical hearing aid algorithms.

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