• Structural Engineering and Mechanics
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• v.37 no.2
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• pp.131-147
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• 2011

The logarithmic decrement method has been long used to estimate damping ratios in systems with only one modal component such as linear single degree of freedom (SDOF) mechanical systems. This paper presents an application of a methodology that uses joint time-frequency distribution (JTFD) as input, instead of the raw signal, to systems with several vibration modes. A most important feature of the present approach is that it can be applied to a system with time-varying damping ratio. Initially the precision and robustness of the method is determined using a synthetic model with multiple harmonic components, one of them displaying a time-varying damping ratio, subsequently the results obtained from experiments with a reduced model are presented. A comparison is made between the results obtained with this methodology and those using the classical technique of Least Squares Complex Exponential Method (LSCE) in order to highlight the advantages of the former, such as, good precision, robustness and excellent performance in extreme cases, e.g., when very low frequency components and time varying damping ratio are present.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.5
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• pp.963-969
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• 2000

In this paper, we define two input-output gains of linear periodic time-varying systems. One is the ratio of output with worst-case l2-norm over all inputs with unit 12-norm. It denotes G($\iota_2,\iota_2$.The other is the ratio of output with worst-case RMS value over all inputs with unit RMS value. It denotes G(RMS, RMS) .It is fact that these two gains are equivalent for linear time-invariant system. In this paper, we prove these two gains are also equivalent for linear periodic time-varying system. In addition, the relationship between two method of obtaining the generalized frequency responses for linear periodic time-varying system is derived. Finally, we apply the defined input-output gains to M-channel filter-bank which is multi-rate signal Processing system, used to speech coding. In the filter-bank, generally, aliasing distortion, magnitude distortion, and phase distortion are present. It is shown that these are kept small if the filter-bank is designed by a method that optimizes the gain G($\iota_2,\iota_2$ of an error system.

• The Journal of the Acoustical Society of Korea
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• v.24 no.4E
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• pp.128-131
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• 2005

A new algorithm for speech signal segmentation is proposed. This algorithm is based on finding successive similar frames belonging to a segment and represents it by an average spectrum. The speech signal is a slowly time varying signal in the sense that, when examined over a sufficiently short period of time (between 10 and 100 ms), its characteristics are fairly stationary. Generally this approach is based on finding these fairly stationary periods. Advantages of the. algorithm are accurate border decision of segments and simple computation. The automatic segmentations using frame averaging show as much as $82.20\%$ coincided with manually verified segmentation of CMU ARCTIC corpus within time range 16 ms. More than $90\%$ segment boundaries are coincided within a range of 32 ms. Also it can be combined with many types of automatic segmentations (HMM based, acoustic cues or feature based etc.).

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.101-106
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• 2019

This paper propose the VSS-FC-MMA algorithm that is possible to improve the equalization performance based on varying step size to the FC-MMA adaptive equalization algorithm in order to reducing the intersymbol interference effect occurred in the nonconstant modulus signal transmission, and improved performance were confirmed. The FC-MMA is possible to improve the convergence speed, and degrades the steady state performance based on the fixed step size and modified dispersion constant considering the level number of signal symbol for obtain the error signal in adaptive equalization compared to MMA. The proposed VSS-FC-MMA uses varying step size and current FC-MMA possible to improve the steady state equalization performance, it was confirmed by computer simulation. For this, the signal recovery capabilities and residual isi, MSE, SER were applied for performance comparison index in the same channel and signal to noise ratio. As a result of computer simulation, the proposed VSS-FC-MMA improve the risidual value in steady state and SER performance than the FC-MMA, but has 1.7 times slow convergence time by using varying step size.

• Smart Structures and Systems
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• v.30 no.1
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• pp.75-88
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• 2022

Engineering structures in operation essentially belong to time-varying or nonlinear structures and the resultant response signals are usually non-stationary. For such time-varying structures, it is of great importance to extract time-dependent dynamic parameters from non-stationary response signals, which benefits structural health monitoring, safety assessment and vibration control. However, various traditional signal processing methods are unable to extract the embedded meaningful information. As a newly developed technique, variational mode decomposition (VMD) shows its superiority on signal decomposition, however, it still suffers two main problems. The foremost problem is that the number of modal components is required to be defined in advance. Another problem needs to be addressed is that VMD cannot effectively separate non-stationary signals composed of closely spaced or overlapped modes. As such, a new method named generalized adaptive variational modal decomposition (GAVMD) is proposed. In this new method, the number of component signals is adaptively estimated by an index of mean frequency, while the generalized demodulation algorithm is introduced to yield a generalized VMD that can decompose mode overlapped signals successfully. After that, synchrosqueezing wavelet transform (SWT) is applied to extract instantaneous frequencies (IFs) of the decomposed mono-component signals. To verify the validity and accuracy of the proposed method, three numerical examples and a steel cable with time-varying tension force are investigated. The results demonstrate that the proposed GAVMD method can decompose the multi-component signal with overlapped modes well and its combination with SWT enables a successful IF extraction of each individual component.

• Journal of Biomedical Engineering Research
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• v.15 no.3
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• pp.305-316
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• 1994

All physical data in the real world are nonstationary signals that have the time varying statistical characteristics. Although few algorithms suitable to process the nonstationary signals have ever been suggested, these are treated the nonstationary signals under the assumption that the nonstationary signal is a piece-wise stationary signal. Recently, statistical analysis algorithms for the nonstationary signal have concentrated so much interest. In this paper, nonstationary EMG signals are mapped onto the orthogonal wavelet transform domain so that the eigenvalue spread of its autocorrelation matrix could be more smaller than that in the time domain. Then the model in the wavelet transform domain and an algorithm to estimate the model parameters are suggested. Also, an test signal generated by a white gaussian noise and the EMG signal are identified, and the algorithm performance is considered in the sense of the mean square error and the evaluation parameters.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2208-2211
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• 2003

In this paper, a variable bandwidth filter(VBF) is realized with the purpose of the decomposition of speech signals with time-varying instantaneous of frequencies. The proposed VBF can extract AM-FM components of a speech signal whose time-frequency representations(TFRs) are not overlapped in time-frequency domain

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2152-2154
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• 2004

A robust bending frequency tracker is proposed to design the adaptive notch filter which removes the time-varying missile structural mode from the sensor measurements. To design the bending frequency tracker, firstly, the signal model is derived from the input-output relationship of Nehorai notch filter structure. Also, the time-varying nature of the bending frequency is modelled as the norm-bounded uncertainty. Based on the uncertain signal model, it is shown that the design problem of robust bending frequency tracker can be casted into that of adaptive robust $H_{\infty}$ filter or equivalently robust LMS filter.

• Journal of Advanced Marine Engineering and Technology
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• v.20 no.3
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• pp.286-286
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• 1996

A neural predictive tracking system for the control of structure-unknown dynamic system is presented. The control system comprises a neural network modelling mechanism for the the forward and inverse dynamics of a plant to be controlled, a feedforward controller, feedback controller, and an error prediction mechanism. The feedforward controller, a neural network model of the inverse dynamics, generates feedforward control signal to the plant. The feedback control signal is produced by the error prediction mechanism. The error predictor adopts the neural network models of the forward and inverse dynamics. Simulation results are presented to demonstrate the applicability of the proposed scheme to predictive tracking control problems.

• Journal of Advanced Marine Engineering and Technology
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• v.20 no.3
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• pp.154-161
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• 1996

A neural predictive tracking system for the control of structure-unknown dynamic system is presented. The control system comprises a neural network modelling mechanism for the the forward and inverse dynamics of a plant to be controlled, a feedforward controller, feedback controller, and an error prediction mechanism. The feedforward controller, a neural network model of the inverse dynamics, generates feedforward control signal to the plant. The feedback control signal is produced by the error prediction mechanism. The error predictor adopts the neural network models of the forward and inverse dynamics. Simulation results are presented to demonstrate the applicability of the proposed scheme to predictive tracking control problems.