• Title/Summary/Keyword: computer-assisted spectral analysis

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Qualitative Analysis by Derivative Spectrophotometry (II) - Computer-assisted spectral analysis using derivative spectra and Root Mean of Squares of differences -

  • Park, Man-Ki;Park, Jeong-Hill;Cho, Jung-Hwan
    • Archives of Pharmacal Research
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    • v.12 no.4
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    • pp.289-294
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    • 1989
  • A computer program which can differentiate compounds whose absorbance spectra are very similar was developed. The program. [SPECMAN PLUS], written in Pascal provides automated spectral comparison techniques, utilizing the values of Root Mean of Squares (RMS) of differences. This comparison routine of the program can deal with spectra of compounds different concentrations and different spectral recording resolutions. In addition, the program was designed applicable to any spectral data of digital form. The program was applied to the UV spectra of 13 pencillins and 5 cephalosporins, whose absorbance spectra are so similar. As a result, all compounds examined could be differentiated from each other.

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Performance Evaluation of Attention-inattetion Classifiers using Non-linear Recurrence Pattern and Spectrum Analysis (비선형 반복 패턴과 스펙트럼 분석을 이용한 집중-비집중 분류기의 성능 평가)

  • Lee, Jee-Eun;Yoo, Sun-Kook;Lee, Byung-Chae
    • Science of Emotion and Sensibility
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    • v.16 no.3
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    • pp.409-416
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    • 2013
  • Attention is one of important cognitive functions in human affecting on the selectional concentration of relevant events and ignorance of irrelevant events. The discrimination of attentional and inattentional status is the first step to manage human's attentional capability using computer assisted device. In this paper, we newly combine the non-linear recurrence pattern analysis and spectrum analysis to effectively extract features(total number of 13) from the electroencephalographic signal used in the input to classifiers. The performance of diverse types of attention-inattention classifiers, including supporting vector machine, back-propagation algorithm, linear discrimination, gradient decent, and logistic regression classifiers were evaluated. Among them, the support vector machine classifier shows the best performance with the classification accuracy of 81 %. The use of spectral band feature set alone(accuracy of 76 %) shows better performance than that of non-linear recurrence pattern feature set alone(accuracy of 67 %). The support vector machine classifier with hybrid combination of non-linear and spectral analysis can be used in later designing attention-related devices.

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Design and Performance Analysis of FSC Receiver for Improvement of D2D Communication in Cellular Network (셀룰러 네트워크에서 D2D 통신 향상을 위한 FSC 수신기 설계 및 성능 분석)

  • Moon, Sangmi;Choe, Hun;Chu, Myeonghun;Kim, Hanjong;Hwang, Intae
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.5
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    • pp.33-47
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    • 2015
  • Cellular Network assisted device-to-device (D2D) communication has been growing to reduce the overload of eNodeB and mitigate the frequency shortage. However, by sharing the uplink frequency resource with the cellular network, the interference between cellular and D2D is increased. In this paper, we propose an advanced receiver for full suppression cancellation (FSC) to reduce the interference between cellular and D2D. The proposed receiver can suppress and cancel the interference by integrating the interference rejection combining (IRC) technique with successive interference cancellation (SIC). We perform a system level simulation based on the 20-MHz bandwidth of the 3GPP LTE-A system. Simulation results show that the proposed receiver can improve SINR, throughput and spectral efficiency compared to conventional receivers.

Design and Performance Analysis of Hybrid Receiver based on System Level Simulation in Backhaul System (백홀 시스템에서 시스템 레벨 시뮬레이션 기반 하이브리드 수신기 설계 및 성능 분석)

  • Moon, Sangmi;Chu, Myeonghun;Kim, Hanjong;Kim, Daejin;Hwang, Intae
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.11
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    • pp.3-11
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    • 2015
  • An advanced receiver which can manage inter-cell interference is required to cope with the explosively increasing mobile data traffic. 3rd Generation Partnership Project (3GPP) has discussed network assisted interference cancellation and suppression (NAICS) to improve signal-to-noise-plus-interference ratio (SINR) and receiver performance by suppression or cancellation of interference signal from inter-cells. In this paper, we propose the advanced receiver based on soft decision to reduce the interference from neighbor cell in LTE-Advanced downlink system. The proposed receiver can suppress and cancel the interference by calculating the unbiased estimation value of interference signal using minimum mean square error (MMSE) or interference rejection combing (IRC) receiver. The interference signal is updated using soft information expressed by log-likelihood ratio (LLR). We perform the system level simulation based on 20MHz bandwidth of 3GPP LTE-Advanced downlink system. Simulation results show that the proposed receiver can improve SINR, throughput, and spectral efficiency of conventional system.