• Title/Summary/Keyword: square norm

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Heart Rate Variability in Cold Pattern: 3-year Follow-up Study (추적관찰을 통해 살펴본 한증 HRV지표)

  • Bae, Kwang Ho;Park, Ki Hyun;Jang, Eunsu
    • Journal of Physiology & Pathology in Korean Medicine
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    • v.34 no.1
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    • pp.30-36
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    • 2020
  • This study aimed to investigate heart rate variability (HRV) characteristics of cold pattern with repeated measurement data. Participants were taken from a Daejeon University cohort study from 2015 to 2018. Forty-seven of the participants studied displayed cold pattern while 23 showed signs of non-cold pattern. HRV was measured in supine position for 5 minutes at each year, and an 8-item cold pattern questionnaire was used for the diagnosis of cold pattern. SDNN (standard deviation of the NN intervals) and RMSSD (the square root of the mean squared differences of successive NN intervals) were used as time domain analysis, and TP (total power), VLF (power in very low frequency range), LF (power in low frequency range), HF (power in high frequency range), LF norm (LF power in normalized units), HF norm (HF power in normalized units) and LF/HF were used as frequency domain analysis. In the Mann-Whitney U test, LF norm, HF norm, and LF/HF showed differences between the cold pattern group and non-cold pattern group at every measurement, and in the independent t-test, the differences were also observed at three points except for the baseline (2015). In the repeated measures ANOVA, the interaction effects were not observed in all HRV parameters, but the time period effects were observed in SDNN, RMSSD, TP, VLF, LF and HF. There were significant differences between those two groups in LF norm, HF norm and LF/HF. This study suggests that LF norm, HF norm and LF/HF might be a useful indicator of cold pattern properties.

Batch-mode Learning in Neural Networks (신경회로망에서 일괄 학습)

  • 김명찬;최종호
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.32B no.3
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    • pp.503-511
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    • 1995
  • A batch-mode algorithm is proposed to increase the speed of learning in the error backpropagation algorithm with variable learning rate and variable momentum parameters in classification problems. The objective function is normalized with respect to the number of patterns and output nodes. Also the gradient of the objective function is normalized in updating the connection weights to increase the effect of its backpropagated error. The learning rate and momentum parameters are determined from a function of the gradient norm and the number of weights. The learning rate depends on the square rott of the gradient norm while the momentum parameters depend on the gradient norm. In the two typical classification problems, simulation results demonstrate the effectiveness of the proposed algorithm.

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On the admissibility condition in the model matching problem

  • Park, Kiheon
    • 제어로봇시스템학회:학술대회논문집
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    • 1994.10a
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    • pp.293-299
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    • 1994
  • A new approach to deal with the model matching problem for square plants is suggested. Admissibility conditions of the model matching error are derived in terms of state-space parameters and the derived formulas are exploited to obtain the solution to the model matching problem in H$_{2}$ norm.

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An improved sparsity-aware normalized least-mean-square scheme for underwater communication

  • Anand, Kumar;Prashant Kumar
    • ETRI Journal
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    • v.45 no.3
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    • pp.379-393
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    • 2023
  • Underwater communication (UWC) is widely used in coastal surveillance and early warning systems. Precise channel estimation is vital for efficient and reliable UWC. The sparse direct-adaptive filtering algorithms have become popular in UWC. Herein, we present an improved adaptive convex-combination method for the identification of sparse structures using a reweighted normalized leastmean-square (RNLMS) algorithm. Moreover, to make RNLMS algorithm independent of the reweighted l1-norm parameter, a modified sparsity-aware adaptive zero-attracting RNLMS (AZA-RNLMS) algorithm is introduced to ensure accurate modeling. In addition, we present a quantitative analysis of this algorithm to evaluate the convergence speed and accuracy. Furthermore, we derive an excess mean-square-error expression that proves that the AZA-RNLMS algorithm performs better for the harsh underwater channel. The measured data from the experimental channel of SPACE08 is used for simulation, and results are presented to verify the performance of the proposed algorithm. The simulation results confirm that the proposed algorithm for underwater channel estimation performs better than the earlier schemes.

Application of Response Spectrum Method to a Bridge subjected to Multiple Support Excitation (다지점(多支點) 지진하중(地震荷重) 받는 교량(橋梁)에 대한 응답(應答) 스펙트럼법(法)의 적용(適用))

  • Kang, Kee Dong
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.10 no.3
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    • pp.1-6
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    • 1990
  • The dynamic behaviour of a four-span continuous girder railway bridge subjected to multiple support excitations is investigated using the response spectrum method. Small-amplitude oscillations and linear-elastic material behaviour are assumed. Soil-structure interaction effects are disregarded and only the out-of-plane response of the bridge is considered. The results of the response spectrum analysis are compared with those from a time history analysis. Different combination rules for the superposition of modal maxima as well as supports are employed, such as square-root-of-sum-squares, double sum and p-norm methods.

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Detection of tonal frequency of underwater radiated noise via atomic norm minimization (Atomic norm minimization을 통한 수중 방사 소음 신호의 토널 주파수 탐지)

  • Kim, Junhan;Kim, Jinhong;Shim, Byonghyo;Hong, Jungpyo;Kim, Seongil;Hong, Wooyoung
    • The Journal of the Acoustical Society of Korea
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    • v.38 no.5
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    • pp.543-548
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    • 2019
  • The tonal signal caused by the machinery component of a vessel such as an engine, gearbox, and support elements, can be modeled as a sparse signal in the frequency domain. Recently, compressive sensing based techniques that recover an original signal using a small number of measurements in a short period of time, have been applied for the tonal frequency detection. These techniques, however, cannot avoid a basis mismatch error caused by the discretization of the frequency domain. In this paper, we propose a method to detect the tonal frequency with a small number of measurements in the continuous domain by using the atomic norm minimization technique. From the simulation results, we demonstrate that the proposed technique outperforms conventional methods in terms of the exact recovery ratio and mean square error.

A study on the determination of Ultrasonic Travel Time by Norm Phase-Time Method (위상시간법에 의한 초음파전파시간의 결정에 관한 연구)

  • 이은방
    • Journal of the Korean Institute of Navigation
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    • v.18 no.4
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    • pp.137-146
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    • 1994
  • In this paper, a new algorithm to measure the ultrasonic travel time is proposed, which is fundamental to estimate distance depth and volume in several media. Pulse wave has been used to measure travel time of transmitted signal. However, due to the characteristic of transducer and propagation, the received signal is so distorted that it is difficult to measure travel time, which is propagation, the received signal is so distorted that it is difficult to measure travel time, which is to be time difference between transmitted and received signals. In this proposed method, transmitted and received signal are transformed respectively into norm phase newly designed by this paper and displayed on phase-time curve. And travel time is simply determined by the arithmetic numerical mean of time difference at the identical norm phase on the phase-time curves of transmitted and received signals. This method has several features; firstly, travel time is calculated analytically with high accuracy by least square error method, secondly, it is useful to compare the difference of signal magnitude for time information, thirdly, noise and discrete errors are relatively small, finally, the measurement accuracy is not influenced by D.C. bias. In particular, this method is useful and applicable to measuring very short distance and sound speed with high accuracy.

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A Study on the Sparse Channel Estimation Technique in Underwater Acoustic Channel (수중음향채널에서 Sparse 채널 추정 기법에 관한 연구)

  • Gwun, Byung-Chul;Lee, Oi-Hyung;Kim, Ki-Man
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.5
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    • pp.1061-1066
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    • 2014
  • Transmission characteristics of the sound propagation is very complicate and sparse in shallow water. To increase the performance of underwater acoustic communication system, lots of channel estimation technique has been proposed. In this paper, we proposed the channel estimation based on LMS(Least Mean Square) algorithm which has faster convergence speed than conventional sparse-aware LMS algorithms. The proposed method combines $L_p$-norm LMS with soft decision process. Simulation was performed by using the sound velocity profile which acquired in real sea trial. As a result, we confirmed that the proposed method shows the improved performance and faster convergence speed than conventional methods.