• Title/Summary/Keyword: Test vectors

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Derivation of Dynamic Characteristic Values for Multi-degree-of-freedom Frame Structures based on Frequency Response Function(FRF) (주파수응답함수 기반 다자유도 골조 구조물의 동특성치 도출 및 구조모델링 적용 )

  • So-Yeon Kim;Min-Young Kim;Seung-Jae Lee;Kyoung-Kyu Choi
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.27 no.4
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    • pp.1-10
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    • 2023
  • In the seismic design of structures, seismic forces are calculated based on structural models and analysis. In order to accurately address the dynamic characteristics of the actual structure in the structural model, calibration based on actual measurements is required. In this study, a 4-story frame test specimen was manufactured to simulate frame building, accelerometers were attached at each floor, and 1-axis shaking table test was performed. The natural period of the specimen was similar to that of the actual 4 story frame building, and the columns were designed to behave with double-curvature having the infinite stiffness of the horizontal members. To investigate the effects seismic waves characteristics, historical and artificial excitations with various frequencies and acceleration magnitudes were applied. The natural frequencies, damping ratios, and mode shapes were obtained using frequency response functions obtained from dynamic response signals, and the mode vector deviations according to the input seismic waves were verified using the Mode assurance criterion (MAC). In addition, the damping ratios obtained from the vibration tests were applied to the structural model, and the method with refined dynamic characteristics was validated by comparing the analysis results with the experimental data.

Real-time Implementation of the AMR-WB+ Audio Coder using ARM Core(R) (ARM Core(R)를 이용한 AMR-WB+ 오디오 부호화기의 실시간 구현)

  • Won, Yang-Hee;Lee, Hyung-Il;Kang, Sang-Won
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.46 no.3
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    • pp.119-124
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    • 2009
  • In this paper, AMR-WB+ audio coder is implemented, in real-time, using Intel 400MHz Xscale PXA250 with 32bit RISC processor ARM9E-J(R)core. The assembly code for ARM9E-J(R)core is developed through the serial process of C code optimization, cross compile, assembly code manual optimization and adjusting the optimized code to Embedded Visual C++ platform. C code is trimmed on Visual C++ platform. Cross compile and assembly code manual optimization are performed on CodeWarrior with ARM compiler. Through these stages the code for both ARM EVM board and PDA is implemented. The average complexities of the code are 160.75MHz on encoder and 33.05MHz on decoder. In case of static link library(SLL), the required memories are 65.21Kbyte, 32.01Kbyte and 279.81Kbyte on encoder, decoder and common sources, respectively. The implemented coder is evaluated using 16 test vectors given by 3GPP to verify the bit-exactness of the coder.

A Real-Time Embedded Speech Recognition System

  • Nam, Sang-Yep;Lee, Chun-Woo;Lee, Sang-Won;Park, In-Jung
    • Proceedings of the IEEK Conference
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    • 2002.07a
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    • pp.690-693
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    • 2002
  • According to the growth of communication biz, embedded market rapidly developing in domestic and overseas. Embedded system can be used in various way such as wire and wireless communication equipment or information products. There are lots of developing performance applying speech recognition to embedded system, for instance, PDA, PCS, CDMA-2000 or IMT-2000. This study implement minimum memory of speech recognition engine and DB for apply real time embedded system. The implement measure of speech recognition equipment to fit on embedded system is like following. At first, DC element is removed from Input voice and then a compensation of high frequency was achieved by pre-emphasis with coefficients value, 0.97 and constitute division data as same size as 256 sample by lapped shift method. Through by Levinson - Durbin Algorithm, these data can get linear predictive coefficient and again, using Cepstrum - Transformer attain feature vectors. During HMM training, We used Baum-Welch reestimation Algorithm for each words training and can get the recognition result from executed likelihood method on each words. The used speech data is using 40 speech command data and 10 digits extracted form each 15 of male and female speaker spoken menu control command of Embedded system. Since, in many times, ARM CPU is adopted in embedded system, it's peformed porting the speech recognition engine on ARM core evaluation board. And do the recognition test with select set 1 and set 3 parameter that has good recognition rate on commander and no digit after the several tests using by 5 proposal recognition parameter sets. The recognition engine of recognition rate shows 95%, speech commander recognizer shows 96% and digits recognizer shows 94%.

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Frame Rate Up-Conversion with Occlusion Detection Function (폐색영역탐지 기능을 갖는 프레임율 변환)

  • Kim, Nam-Uk;Lee, Yung-Lyul
    • Journal of Broadcast Engineering
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    • v.20 no.2
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    • pp.265-272
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    • 2015
  • A new technology on video frame rate up-conversion (FRUC) is presented by combining the median filter and motion estimation (ME) with an occlusion detection (OD) method. First, ME is performed to have a motion vector. Then, the OD method is used to refine motion vector in the occlusion region. Since the wrong motion vector can be obtained with high possibility in the occluded area, a median filtering that less depends on the motion vector is applied to that area, and since the motion vector is continuous and robust in the non-occluded area, BDMC(Bi-Directional Motion Compensated interpolation) is applied to obtain interpolated image in that area. BDMC using the bi-directional motion vectors achieves good results when continuity and robustness of the motion vector is higher. Experimental results show that the proposed algorithm provides better performance than the conventional approach. The average gain of PSNR (Peak Signal to Noise Ratio) is approximately 0.16 dB in the test sequences compared with BDMC.

Hierarchical Neural Network for Real-time Medicine-bottle Classification (실시간 약통 분류를 위한 계층적 신경회로망)

  • Kim, Jung-Joon;Kim, Tae-Hun;Ryu, Gang-Soo;Lee, Dae-Sik;Lee, Jong-Hak;Park, Kil-Houm
    • Journal of the Korean Institute of Intelligent Systems
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    • v.23 no.3
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    • pp.226-231
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    • 2013
  • In The matching algorithm for automatic packaging of drugs is essential to determine whether the canister can exactly refill the suitable medicine. In this paper, we propose a hierarchical neural network with the upper and lower layers which can perform real-time processing and classification of many types of medicine bottles to prevent accidental medicine disaster. A few number of low-dimensional feature vector are extracted from the label images presenting medicine-bottle information. By using the extracted feature vectors, the lower layer of MLP(Multi-layer Perceptron) neural networks is learned. Then, the output of the learned middle layer of the MLP is used as the input to the upper layer of the MLP learning. The proposed hierarchical neural network shows good classification performance and real- time operation in the test of up to 30 degrees rotated to the left and right images of 100 different medicine bottles.

Classification of Transient Signals in Ocean Background Noise Using Bayesian Classifier (베이즈 분류기를 이용한 수중 배경소음하의 과도신호 분류)

  • Kim, Ju-Ho;Bok, Tae-Hoon;Paeng, Dong-Guk;Bae, Jin-Ho;Lee, Chong-Hyun;Kim, Seong-Il
    • Journal of Ocean Engineering and Technology
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    • v.26 no.4
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    • pp.57-63
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    • 2012
  • In this paper, a Bayesian classifier based on PCA (principle component analysis) is proposed to classify underwater transient signals using $16^{th}$ order LPC (linear predictive coding) coefficients as feature vector. The proposed classifier is composed of two steps. The mechanical signals were separated from biological signals in the first step, and then each type of the mechanical signal was recognized in the second step. Three biological transient signals and two mechanical signals were used to conduct experiments. The classification ratios for the feature vectors of biological signals and mechanical signals were 94.75% and 97.23%, respectively, when all 16 order LPC vector were used. In order to determine the effect of underwater noise on the classification performance, underwater ambient noise was added to the test signals and the classification ratio according to SNR (signal-to-noise ratio) was compared by changing dimension of feature vector using PCA. The classification ratios of the biological and mechanical signals under ocean ambient noise at 10dB SNR, were 0.51% and 100% respectively. However, the ratios were changed to 53.07% and 83.14% when the dimension of feature vector was converted to three by applying PCA. For correct, classification, it is required SNR over 10 dB for three dimension feature vector and over 30dB SNR for seven dimension feature vector under ocean ambient noise environment.

Wind Vector Quality Control Using Symmetry of Doppler Spectral Peak (도플러 스펙트럼 대칭성을 이용한 바람 벡터 품질 관리)

  • Kim, Min-Seong;Lee, Kyung-Hun;Kwon, Byung-Hyuk;Yoon, Hong-Joo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.15 no.5
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    • pp.841-848
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    • 2020
  • The 1.29 GHz wind profiler radar is a remote observation device that is useful not only for calculating wind vectors in clear air, but also for detecting rainfall. The Doppler spectrum symmetry test is essential in the horizontal wind treatment process. Since asymmetry may be detected in rainfall cases, it is necessary to reflect in the wind calculation algorithm that the sign of the radial velocity is the same according to the magnitude of the vertical velocity. In the summer of 2017 (June, July), a wind vector calculation algorithm by Bragg scattering and Rayleigh scattering was developed using Changwon wind profiler data, and verified by comparing it with radiosonde data at 6 hour intervals.

Real-time Implementation of the G.729 Annex A Using ARM9 $Thumb^{\circledR}$ Processor Core (ARM9 $Thumb^{\circledR}$ 프로세서 코어를 이용한 G.729A의 실시간 구현)

  • 성호상;이동원
    • The Journal of the Acoustical Society of Korea
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    • v.20 no.7
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    • pp.63-68
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    • 2001
  • This paper describes the details of ITU-T SGIS G.729A speech coder implementation using ARM9 Thumb/sup R/ processor core and various techniques used in the optimization process. ITU-T G.729 speech coder is the standard of the toll quality 8 kbit/s speech coding. The input to the speech encoder is assumed to be a 16 bits PCM signal at a sampling rate of 8000 samples per second. G.729A is reduced complexity version of the G.729 coder. This version is bit stream interoperable with the full version. The implemented coder requires 34.8 MIPS for the encoder and 8.1 MIPS for the decoder, 36.5 kBytes of program ROM and 6.3 kBytes of data RAM, respectively. The implemented coder is tested against the set of 9 test vectors provided by ITU-T for bit exact implementation.

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Real-time Implementation of a GSM-EFR Speech Coder on a 16 Bit Fixed-point DSP (16 비트 고정 소수점 DSP를 이용한 GSM-EFR 음성 부호화기의 실시간 구현)

  • 최민석;변경진;김경수
    • The Journal of the Acoustical Society of Korea
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    • v.19 no.7
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    • pp.42-47
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    • 2000
  • This paper describes a real-time implementation of a GSM-EFR (Global System for Mobil communications Enhanced Full Rate) speech coder using OakDSP core; a 16bit fixed-point Digital Signal Processor (DSP) by DSP Group, Inc. The real-time implemented speech coder required about 24MIPS for computation and 7.06K words and 12.19K words for code and data memory, respectively. The implemented GSM-EFR speech coder passes all of test vectors provided by ETSI (European Telecommunication Standard Institute), and perceptual speech quality measurement using MNB algorithm shows that the quality of the GSM-EFR speech coder is similar to the one of 32kbps ADPCM. The real-time implemented GSM-EFR speech coder which is the highest bit-rate mode of the GSM-AMR speech coder will be used as the basic structure of the GSM-AMR speech coder which is embedded in MODEM ASIC of IMT2000 asynchronous mode mobile station.

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A Text Summarization Model Based on Sentence Clustering (문장 클러스터링에 기반한 자동요약 모형)

  • 정영미;최상희
    • Journal of the Korean Society for information Management
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    • v.18 no.3
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    • pp.159-178
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    • 2001
  • This paper presents an automatic text summarization model which selects representative sentences from sentence clusters to create a summary. Summary generation experiments were performed on two sets of test documents after learning the optimum environment from a training set. Centroid clustering method turned out to be the most effective in clustering sentences, and sentence weight was found more effective than the similarity value between sentence and cluster centroid vectors in selecting a representative sentence from each cluster. The result of experiments also proves that inverse sentence weight as well as title word weight for terms and location weight for sentences are effective in improving the performance of summarization.

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