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

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SRAM-Based Area-Efficient Computing-in-Memory for AI Edge Devices (AI 엣지 디바이스를 위한 SRAM 기반 면적 효율적인 컴퓨팅 인 메모리)

  • Hyun-Ki Hong;Sung-Hun Jo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.19 no.5
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    • pp.1051-1058
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    • 2024
  • In semiconductors for AI, Computing in Memory (CIM) integrates computation and memory to minimize data movement and reduce processing bottlenecks, thereby improving performance. In AI tasks that handle large amounts of data, CIM is gaining attention as a key technology that optimizes the performance of AI systems by improving power efficiency and enabling faster computation. In this paper, a new CIM architecture for AI semiconductors is proposed. The proposed architecture can perform MAC operations by controlling the width of the transistor and the pulse width of the control signal, and can be implemented in a smaller area than the existing architecture.

Real-Time Fixed Pattern Noise Suppression using Hardware Neural Networks in Infrared Images Based on DSP & FPGA (DSP & FPGA 기반의 적외선 영상에서 하드웨어 뉴럴 네트워크를 이용한 실시간 고정패턴잡음 제어)

  • Park, Chang-Han;Han, Jung-Soo;Chun, Seung-Woo
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.46 no.4
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    • pp.94-101
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    • 2009
  • In this paper, we propose design of hardware based on a high speed digital signal processor (DSP) and a field programmable gate array (FPGA) for real-time suppression of fixed pattern noise (FPN) using hardware neural networks (HNN) in cooled infrared focal plane array (IRFPA) imaging system FPN appears a limited operation by temperature in observable images which applies to non-uniformity correction for infrared detector. These have very important problems because it happen serious problem for other applications as well as degradation for image quality in our system Signal processing architecture for our system operates reference gain and offset values using three tables for low, normal, and high temperatures. Proposed method creates virtual tables to separate for overlapping region in three offset tables. We also choose an optimum tenn of temperature which controls weighted values of HNN using mean values of pixels in three regions. This operates gain and offset tables for low, normal, and high temperatures from mean values of pixels and it recursively don't have to do an offset compensation in operation of our system Based on experimental results, proposed method showed improved quality of image which suppressed FPN by change of temperature distribution from an observational image in real-time system.

Copyright Protection for Fire Video Images using an Effective Watermarking Method (효과적인 워터마킹 기법을 사용한 화재 비디오 영상의 저작권 보호)

  • Nguyen, Truc;Kim, Jong-Myon
    • KIPS Transactions on Software and Data Engineering
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    • v.2 no.8
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    • pp.579-588
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    • 2013
  • This paper proposes an effective watermarking approach for copyright protection of fire video images. The proposed watermarking approach efficiently utilizes the inherent characteristics of fire data with respect to color and texture by using a gray level co-occurrence matrix (GLCM) and fuzzy c-means (FCM) clustering. GLCM is used to generate a texture feature dataset by computing energy and homogeneity properties for each candidate fire image block. FCM is used to segment color of the fire image and to select fire texture blocks for embedding watermarks. Each selected block is then decomposed into a one-level wavelet structure with four subbands [LL, LH, HL, HH] using a discrete wavelet transform (DWT), and LH subband coefficients with a gain factor are selected for embedding watermark, where the visibility of the image does not affect. Experimental results show that the proposed watermarking approach achieves about 48 dB of high peak-signal-to-noise ratio (PSNR) and 1.6 to 2.0 of low M-singular value decomposition (M-SVD) values. In addition, the proposed approach outperforms conventional image watermarking approach in terms of normalized correlation (NC) values against several image processing attacks including noise addition, filtering, cropping, and JPEG compression.

Analysis of Magnetic Flux Leakage based Local Damage Detection Sensitivity According to Thickness of Steel Plate (누설자속 기반 강판 두께별 국부 손상 진단 감도 분석)

  • Kim, Ju-Won;Yu, Byoungjoon;Park, Sehwan;Park, Seunghee
    • Journal of Korean Society of Disaster and Security
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    • v.11 no.2
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    • pp.53-60
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    • 2018
  • To diagnosis the local damages of the steel plates, magnetic flux leakage (MFL) method that is known as a adaptable non-destructive evaluation (NDE) method for continuum ferromagnetic members was applied in this study. To analysis the sensitivity according to thickness of steel plate in MFL method based damage diagnosis, several steel plate specimens that have different thickness were prepared and three depths of artificial damage were formed to the each specimens. To measured the MFL signals, a MFL sensor head that have a constant magnetization intensity were fabricated using a hall sensor and a magnetization yoke using permanent magnets. The magnetic flux signals obtained by using MFL sensor head were improved through a series of signal processing methods. The capability of local damage detection was verified from the measured MFL signals from each damage points. And, the peak to peak values (P-P value) extracted from the detected MFL signals from each thickness specimen were compared each other to analysis the MFL based local damage detection sensitivity according to the thickness of steel plate.

Experimental study on structural integrity assessment of utility tunnels using coupled pulse-impact echo method (결합된 초음파-충격 반향 기법 기반의 일반 지하구 구조체의 건전도 평가에 관한 실험적 연구)

  • Jin Kim;Jeong-Uk Bang;Seungbo Shim;Gye-Chun Cho
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.25 no.6
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    • pp.479-493
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    • 2023
  • The need for safety management has arisen due to the increasing number of years of operated underground structures, such as tunnels and utility tunnels, and accidents caused by those aging infrastructures. However, in the case of privately managed underground utility ducts, there is a lack of detailed guidelines for facility safety and maintenance, resulting in inadequate safety management. Furthermore, the absence of basic design information and the limited space for safety assessments make applying currently used non-destructive testing methods challenging. Therefore, this study suggests non-destructive inspection methods using ultrasonic and impact-echo techniques to assess the quality of underground structures. Thickness, presence of rebars, depth of rebars, and the presence and depth of internal defects are assessed to provide fundamental data for the safety assessment of box-type general underground structures. To validate the proposed methodology, different conditions of concrete specimens are designed and cured to simulate actual field conditions. Applying ultrasonic and impact signals and collecting data through multi-channel accelerometers determine the thickness of the simulated specimens, the depth of embedded rebar, and the extent of defects. The predicted results are well agreed upon compared with actual measurements. The proposed methodology is expected to contribute to developing safety diagnostic methods applicable to general underground structures in practical field conditions.

The Obstacle Avoidance Algorithm of Mobile Robot using Line Histogram Intensity (Line Histogram Intensity를 이용한 이동로봇의 장애물 회피 알고리즘)

  • 류한성;최중경;구본민;박무열;방만식
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.6 no.8
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    • pp.1365-1373
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    • 2002
  • In this paper, we present two types of vision algorithm that mobile robot has CCD camera. for obstacle avoidance. This is simple algorithm that compare with grey level from input images. Also, The mobile robot depend on image processing and move command from PC host. we has been studied self controlled mobile robot system with CCD camera. This system consists of digital signal processor, step motor, RF module and CCD camera. we used wireless RF module for movable command transmitting between robot and host PC. This robot go straight until recognize obstacle from input image that preprocessed by edge detection, converting, thresholding. And it could avoid the obstacle when recognize obstacle by line histogram intensity. Host PC measurement wave from various line histogram each 20 pixel. This histogram is (x, y) value of pixel. For example, first line histogram intensity wave from (0, 0) to (0, 197) and last wave from (280, 0) to (2n, 197. So we find uniform wave region and nonuniform wave region. The period of uniform wave is obstacle region. we guess that algorithm is very useful about moving robot for obstacle avoidance.

Double Threshold Method for EMG-based Human-Computer Interface (근전도 기반 휴먼-컴퓨터 인터페이스를 위한 이중 문턱치 기법)

  • Lee Myungjoon;Moon Inhyuk;Mun Museong
    • Journal of Biomedical Engineering Research
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    • v.25 no.6
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    • pp.471-478
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    • 2004
  • Electromyogram (EMC) signal generated by voluntary contraction of muscles is often used in a rehabilitation devices such as an upper limb prosthesis because of its distinct output characteristics compared to other bio-signals. This paper proposes an EMG-based human-computer interface (HCI) for the control of the above-elbow prosthesis or the wheelchair. To control such rehabilitation devices, user generates four commands by combining voluntary contraction of two different muscles such as levator scapulae muscles and flexor-extensor carpi ulnaris muscles. The muscle contraction is detected by comparing the mean absolute value of the EMG signal with a preset threshold value. However. since the time difference in muscle firing can occur when the patient tries simultaneous co-contraction of two muscles, it is difficult to determine whether the patient's intention is co-contraction. Hence, the use of the comparison method using a single threshold value is not feasible for recognizing such co-contraction motion. Here, we propose a novel method using double threshold values composed of a primary threshold and an auxiliary threshold. Using the double threshold method, the co-contraction state is easily detected, and diverse interface commands can be used for the EMG-based HCI. The experimental results with real-time EMG processing showed that the double threshold method is feasible for the EMG-based HCI to control the myoelectric prosthetic hand and the powered wheelchair.

Studies in Biomechanical Properties on Brain-spinal Cord Response Mechanism by Human Posture Control Ability (자세조절능력에 따른 뇌-척수 신경 반응기전의 역학적 해석)

  • Yoo, Kyoung-Seok
    • 한국체육학회지인문사회과학편
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    • v.58 no.6
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    • pp.449-459
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    • 2019
  • The purpose of this study is to identify how postural mechanics affects postural control on balance and stability by using frequency analysis technique from the kinematic data acquired during the one leg standing posture. For this purpose, the experimental group consisted of two groups, the normal group (n=6) and the national Gymnastics group (n=6). Displacement data of CoP were analyzed by frequency analysis of rambling (RM) and trembling (TR) by FFT signal processing. As a results, there was a significant difference in evaluating the stabilization index between the two groups with the eyes open and closed one leg stnading (p <.05). The cause of the difference was found to be the output of the maximum amplitude of RM (f1) and TR (f2) (p <.05). In particular, in the low frequency RM of 8-9 Hz, which is a natural frequency of signal wave involved in postural feedback feedback, the main frequency appeared to be performs the exercise mechanism of stable brain posture control. And in the high frequency TM of 120-135 Hz, it is considered that the adaptation of the reflective muscle response is minimized to minimize posture shaking. In conclusion, this study provides evidence for the intrinsic main frequencies according to the postural control ability which affects the CNS in one leg standing.

Development of smart car intelligent wheel hub bearing embedded system using predictive diagnosis algorithm

  • Sam-Taek Kim
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.10
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    • pp.1-8
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    • 2023
  • If there is a defect in the wheel bearing, which is a major part of the car, it can cause problems such as traffic accidents. In order to solve this problem, big data is collected and monitoring is conducted to provide early information on the presence or absence of wheel bearing failure and type of failure through predictive diagnosis and management technology. System development is needed. In this paper, to implement such an intelligent wheel hub bearing maintenance system, we develop an embedded system equipped with sensors for monitoring reliability and soundness and algorithms for predictive diagnosis. The algorithm used acquires vibration signals from acceleration sensors installed in wheel bearings and can predict and diagnose failures through big data technology through signal processing techniques, fault frequency analysis, and health characteristic parameter definition. The implemented algorithm applies a stable signal extraction algorithm that can minimize vibration frequency components and maximize vibration components occurring in wheel bearings. In noise removal using a filter, an artificial intelligence-based soundness extraction algorithm is applied, and FFT is applied. The fault frequency was analyzed and the fault was diagnosed by extracting fault characteristic factors. The performance target of this system was over 12,800 ODR, and the target was met through test results.

Development of Optical Frequency Modulated Fiber Optic Interferometric Sensor (광주파수 변조 광섬유 간섭형 센서의 개발)

  • Kwon, Il-Bum;Kim, Chi-Yeop;Kim, Min-Soo;Lee, Wang-Joo
    • Journal of Sensor Science and Technology
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    • v.9 no.3
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    • pp.163-170
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    • 2000
  • Optical frequency modulated fiber optic interferometric sensor was developed to sense the mechanical quantities, such as displacement, strain, force etc. It has been difficult to distinguish whether the increase of the mechanical quantities or the decrease of the quantities measured by the conventional fiber optic interferometric sensors because their signals only have a sinusoidal wave pattern related to the change of mechanical quantities. In this study, in order to measure the mechanical quantifies with the distinction of the changing direction of the quantities, the fiber of optic Michelson interferometric sensor was simply constructed by the laser light modulated with saw tooth wave pattern. The output signal of the sensor was controlled as the sinusoidal wave. The signal processing was based on the counting of the wave number of the output signal during constant time duration. The strain was determined by the cumulative value of the wave number producted by the gage factor. In order to verify the strain measurement capability of this sensor, the strain increase-decrease test was performed by universal testing machine installed with the aluminum specimen bonded with the fiber optic sensor and electrical strain gage. In the result of the test, the strain from the fiber optic sensor had a good agreement with the values from the electrical strain gage.

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