• 제목/요약/키워드: identification technology

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블라인드 채널추정기법(Blind Channel Identification)을 이용한 수중통신 연구 (Underwater Acoustic Communication Research using Blind Channel identification)

  • 김갑수;조아라;최영철;임용곤
    • 한국정보통신학회:학술대회논문집
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    • 한국해양정보통신학회 2007년도 추계종합학술대회
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    • pp.165-169
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    • 2007
  • Due to the complexity of underwater acoustic channel, signal estimation in underwater acoustic communication field is considerably affected from time-varying multipath fading channels. On this reason, the original signals should have many long training signals to estimate the channel and the purposed signals, and the bit rate of signals having information may have small rate. In order to avoid this loss of efficiency in underwater communication, this paper employed a blind channel identification method which don't use training signals. Simulations have predicted performance of the employed method in multipath environment and an aquatic plant experiment has verified the simulation results.

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Unscented Kalman Filter를 이용한 비선형 동적 구조계의 시간영역 규명기법 (Time Domain Identification of Nonlinear Structural Dynamic Systems Using Unscented Kalman Filter)

  • Yun, Chung-Bang;Koo, Ki-Young
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2001년도 가을 학술발표회 논문집
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    • pp.117-126
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    • 2001
  • In this study, the recently developed unscented Kalman filter (UKF) technique is studied for identification of nonlinear structural dynamic systems as an alternative to the extended Kalman filter (EKF). The EKF, which was originally developed as a state estimator for nonlinear systems, has been frequently employed for parameter identification by introducing the state vector augmented with the unknown parameters to be identified. However, the EKF has several drawbacks such as biased estimations and erroneous estimations especially for highly nonlinear dynamic systems due to its crude linearization scheme. To overcome the weak points of the EKF, the UKF was recently developed as a state estimator. Numerical simulation studies have been carried out on nonlinear SDOF system and nonlinear MDOF system. The results from a series of numerical simulations indicate that the UKF is superior to the EKF in the system identification of nonlinear dynamic systems especially highly nonlinear systems.

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Test Generation for Speed-Independent Asynchronous Circuits with Undetectable Faults Identification

  • Eunjung Oh;Lee, Dong-Ik;Park, Ho-Yong
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2000년도 ITC-CSCC -1
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    • pp.359-362
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    • 2000
  • In this paper, we propose a test pattern generation algorithm on the basis of the identification of undetectable faults for Speed-Independent(SI) asynchronous control circuits. The proposed methodology generates tests from the specification of a target circuit, which describes the behavior of the circuit in the form of Signal Transition Graph (STG). The proposed identification method uses only topological information of a target circuit and reachability information of a fault-free circuit, which is generated in the form of Binary Decision Diagram(BDD) during pre-processing. Experimental results show that high fault coverage over single input stuck-at fault model is obtained for several synthesized SI circuits and the use of the identification process as a preprocessing decreases execution time of the proposed test generation with negligible costs.

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Combination of Classifiers Decisions for Multilingual Speaker Identification

  • Nagaraja, B.G.;Jayanna, H.S.
    • Journal of Information Processing Systems
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    • 제13권4호
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    • pp.928-940
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    • 2017
  • State-of-the-art speaker recognition systems may work better for the English language. However, if the same system is used for recognizing those who speak different languages, the systems may yield a poor performance. In this work, the decisions of a Gaussian mixture model-universal background model (GMM-UBM) and a learning vector quantization (LVQ) are combined to improve the recognition performance of a multilingual speaker identification system. The difference between these classifiers is in their modeling techniques. The former one is based on probabilistic approach and the latter one is based on the fine-tuning of neurons. Since the approaches are different, each modeling technique identifies different sets of speakers for the same database set. Therefore, the decisions of the classifiers may be used to improve the performance. In this study, multitaper mel-frequency cepstral coefficients (MFCCs) are used as the features and the monolingual and cross-lingual speaker identification studies are conducted using NIST-2003 and our own database. The experimental results show that the combined system improves the performance by nearly 10% compared with that of the individual classifier.

Design and implementation of optical identification system using visible light and infrared

  • Lee, Seong-Ho
    • 센서학회지
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    • 제30권4호
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    • pp.196-203
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    • 2021
  • In this study, an optical identification system was developed, wherein visible light is used to transmit the interrogating signal, and infrared is used to send the response signal. In the reader, visible light from a light emitting diode (LED) array was modulated via modified pulse width modulation for flicker-free illumination and dimming control. Moreover, the duty factor of the dimming control time was employed to control the illumination from the LED. In the transponder, the spike signal in the output of the high-pass filter was utilized to recover the interrogating signal while preventing interference from the 120-Hz noise from adjacent lighting lamps. The illumination was controlled in 26-86% range of the constant wave LED illumination by changing the duty factor from 20% to 90%. This configuration is advantageous for the construction of optical identification systems for automatic security check and car fare calculation at toll gates or parking facilities.

아이핀 기반 본인확인서비스의 안전성 강화 방안 (Safety Improvement Methods of Personal Identification Services using the i-Pin)

  • 김종배
    • 한국IT서비스학회지
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    • 제16권2호
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    • pp.97-110
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    • 2017
  • Due to development of IT, various Internet services via the non-face-to-face are increasing rapidly. In the past, the resident registration numbers (RRN) was used a mean of personal identification, but the use of RRN is prohibited by the relevant laws, and the personal identification services using alternative means are activated. According to the prohibition policy of RRN, i-PIN service appeared as an alternative means to identify a person. However, the user's knowledge-based i-PIN service continues to cause fraudulent issuance, account hijacking, and fraud attempts due to hacking accidents. Due to these problems, the usage rate of i-PIN service which performs a nationwide free personal identification service, is rapidly decreasing. Therefore, this paper proposes a technical safety enhancement method for security enhancement in the i-PIN-based personal identification service. In order to strengthen the security of i-PIN, this paper analyzes the encryption key exposure, key exchange and i-PIN authentication model problems of i-PIN and suggests countermeasures. Through the proposed paper, the i-PIN can be expected to be used more effectively as a substitution of RRN by suggesting measures to enhance the safety of personal identification information. Secured personal identification services will enable safer online non-face-to-face transactions. By securing the technical, institutional, and administrative safety of the i-PIN service, the usage rate will gradually increase.

Identification of Fuzzy Inference Systems Using a Multi-objective Space Search Algorithm and Information Granulation

  • Huang, Wei;Oh, Sung-Kwun;Ding, Lixin;Kim, Hyun-Ki;Joo, Su-Chong
    • Journal of Electrical Engineering and Technology
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    • 제6권6호
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    • pp.853-866
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    • 2011
  • We propose a multi-objective space search algorithm (MSSA) and introduce the identification of fuzzy inference systems based on the MSSA and information granulation (IG). The MSSA is a multi-objective optimization algorithm whose search method is associated with the analysis of the solution space. The multi-objective mechanism of MSSA is realized using a non-dominated sorting-based multi-objective strategy. In the identification of the fuzzy inference system, the MSSA is exploited to carry out parametric optimization of the fuzzy model and to achieve its structural optimization. The granulation of information is attained using the C-Means clustering algorithm. The overall optimization of fuzzy inference systems comes in the form of two identification mechanisms: structure identification (such as the number of input variables to be used, a specific subset of input variables, the number of membership functions, and the polynomial type) and parameter identification (viz. the apexes of membership function). The structure identification is developed by the MSSA and C-Means, whereas the parameter identification is realized via the MSSA and least squares method. The evaluation of the performance of the proposed model was conducted using three representative numerical examples such as gas furnace, NOx emission process data, and Mackey-Glass time series. The proposed model was also compared with the quality of some "conventional" fuzzy models encountered in the literature.

Implementation of persistent identification of topological entities based on macro-parametrics approach

  • Farjana, Shahjadi Hisan;Han, Soonhung;Mun, Duhwan
    • Journal of Computational Design and Engineering
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    • 제3권2호
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    • pp.161-177
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    • 2016
  • In history based parametric CAD modeling systems, persistent identification of the topological entities after design modification is mandatory to keep the design intent by recording model creation history and modification history. Persistent identification of geometric and topological entities is necessary in the product design phase as well as in the re-evaluation stage. For the identification, entities should be named first according to the methodology which will be applicable for all the entities unconditionally. After successive feature operations on a part body, topology based persistent identification mechanism generates ambiguity problem that usually stems from topology splitting and topology merging. Solving the ambiguity problem needs a complex method which is a combination of topology and geometry. Topology is used to assign the basic name to the entities. And geometry is used for the ambiguity solving between the entities. In the macro parametrics approach of iCAD lab of KAIST a topology based persistent identification mechanism is applied which will solve the ambiguity problem arising from topology splitting and also in case of topology merging. Here, a method is proposed where no geometry comparison is necessary for topology merging. The present research is focused on the enhancement of the persistent identification schema for the support of ambiguity problem especially of topology splitting problem and topology merging problem. It also focused on basic naming of pattern features.

음성의 묵음구간 검출을 통한 DTW의 성능개선에 관한 연구 (A Study on the Improvement of DTW with Speech Silence Detection)

  • 김종국;조왕래;배명진
    • 음성과학
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    • 제10권4호
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    • pp.117-124
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    • 2003
  • Speaker recognition is the technology that confirms the identification of speaker by using the characteristic of speech. Such technique is classified into speaker identification and speaker verification: The first method discriminates the speaker from the preregistered group and recognize the word, the second verifies the speaker who claims the identification. This method that extracts the information of speaker from the speech and confirms the individual identification becomes one of the most efficient technology as the service via telephone network is popularized. Some problems, however, must be solved for the real application as follows; The first thing is concerning that the safe method is necessary to reject the imposter because the recognition is not performed for the only preregistered customer. The second thing is about the fact that the characteristic of speech is changed as time goes by, So this fact causes the severe degradation of recognition rate and the inconvenience of users as the number of times to utter the text increases. The last thing is relating to the fact that the common characteristic among speakers causes the wrong recognition result. The silence parts being included the center of speech cause that identification rate is decreased. In this paper, to make improvement, We proposed identification rate can be improved by removing silence part before processing identification algorithm. The methods detecting speech area are zero crossing rate, energy of signal detect end point and starting point of the speech and process DTW algorithm by using two methods in this paper. As a result, the proposed method is obtained about 3% of improved recognition rate compare with the conventional methods.

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