• The Journal of Korea Robotics Society
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• v.5 no.1
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• pp.70-76
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• 2010

This paper addresses a design issue of "model complexity and performance trade-off" in the application of bandwidth extension (BWE) methods to the intra-frame predictivevector quantization problem of wideband speech. It discusses model-based linear and non-linear prediction methods and presents a comparative study of them in terms of prediction gain. Through experimentation, the general trend of saturation in performance (with the increase in model complexity) is observed. However, specifically, it is also observed that there is no significant difference between HMM and GMM-based BWE functions.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.1
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• pp.109-116
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• 2001

The detection of corporate failures is a subject that has been particularly amenable to cross-sectional financial ratio analysis. In most of firms, however, the financial data are available over past years. Because of this, a model utilizing these longitudinal data could provide useful information on the prediction of bankruptcy. To correctly reflect the longitudinal and firm-specific data, the generalized linear model with assuming the first order AR(autoregressive) process is proposed. The method is motivated by the clinical research that several characteristics are measured repeatedly from individual over the time. The model is compared with several other predictive models to evaluate the performance. By using the financial data from manufacturing corporations in the Korea Stock Exchange (KSE) list, we will discuss some experiences learned from the procedure of sampling scheme, variable transformation, imputation, variable selection, and model evaluation. Finally, implications of the model with repeated measurement and future direction of research will be discussed.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.6
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• pp.765-770
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• 2005

This paper presents a new intelligent digital redesign (IDR) method via the compensated bilinear transformation to design the digital controller such that the digital fuzzy system is equivalent to the analog fuzzy system in the sense of the state-matching. This paper especially consider a multirate control scheme with a predictive feature, where the digital control input is held constant N times between the sampling points. More precisely, the multirate control scheme is proposed that utilizes a numerical integration scheme to approximately predict the current state from the state measured at the sampling points, the delayed measurements. For this system, the IDR conditions incorporated with stabilizability in the format of the linear matrix inequalities (LMIs) are derived. The superiority of the proposed technique is convincingly visualized through a numerical example.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.8 s.251
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• pp.880-888
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• 2006

This paper presents the sliding mode control with the perturbation estimator for a nonlinear control system in the presence of perturbations including external disturbances, unpredictable parameter variations, ana unstructured dynamics. The proposed perturbation estimator is based on the Recursive Linear Smoothed Newton predictive algorithm so that it is effective to attenuate an undesired noise in high frequency band and to predict the present perturbation signal from the previous ones. Compared to conventional sliding mode control (SMC) and sliding mode control with perturbation estimation (SMCPE) introduced by Elmali and Olgac, the control algorithm proposed in this study can offer better tracking control performances and more feasible estimation characteristics. The effectiveness and superiority of the proposed control strategy are demonstrated by a series of simulations on the position tracking control of a simple two-link robot manipulator subject to velocity feedback signals including white noises.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3257-3269
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• 2020

Articulation disorders are characterized by an inability to achieve clear pronunciation due to misuse of the articulators. In this paper, a method of detecting such disorders by comparing to the standard pronunciations is proposed. This method defines the standard pronunciations from the speeches of normal children by clustering them with three features which are the Linear Predictive Cepstral Coefficient (LPCC), the Mel-Frequency Cepstral Coefficient (MFCC), and the Relative Spectral Analysis Perceptual Linear Prediction (RASTA-PLP). By calculating the distance between the centroid of the standard pronunciation and the inputted pronunciation, disordered speech whose features locates outside the cluster is detected. 89 children (58 of normal children and 31 of children with disorders) were recruited. 35 U-TAP test words were selected and each word's standard pronunciation is made from normal children and compared to each pronunciation of children with disorders. In the experiments, the pronunciations with disorders were successfully distinguished from the standard pronunciations.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.3
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• pp.148-157
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• 1996

Availability of input trajectories corresponding to desired output trajectories is often important in designing control systems for batch and other transient processes. In this paper, we propose a predictive control-type model-based iterative learning algorithm which is applicable to finding the nominal input trajectories of a linear time-invariant batch process. Unlike the other existing learning control algorithms, the proposed algorithm can be applied to nonsquare systems and has an ability to adjust noise sensitivity as well as convergence rate. A simple model identification technique with which performance of the proposed learning algorithm can be significantly enhanced is also proposed. Performance of the proposed learning algorithm is demonstrated through numerical simulations.

• International Journal of Aeronautical and Space Sciences
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• v.5 no.2
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• pp.35-42
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• 2004

Among other critical conditions in rotor svstems the large non-linearvibration excited by bearing non-linearity causes the rotor failure. For reducing thiscatastrophic failure and predictive analysis of this phenomena the identificationanalysis of bearing non-linearity in an anisotropic rotor system using the higherorder dFRFs are developed and are shown to be theoretically feasible as innon-rotating structures. For the identification of the anisotropic rotor withanisotropic bearing non-linearity expressed by the displacement in polynomial form,the higher order dFRFs based upon the Volterra series are investigated and depicttheir features by using the simple forms of the normal and reverse dFRFs. Theyproduce additional sub-harmonic resonant peaks, which indicate the existence ofhigher order non-linearties, and show the energy transfer such that the modes fornormal and reuerse dFRFs are exchanged, which are the fundamental differencesfrom what we can expect in linear ones.

• The Journal of the Acoustical Society of Korea
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• v.1 no.1
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• pp.45-53
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• 1982

A robust linear predictive coding method that can be used in noisy as well as quiet environment has been studied. In this method, noise autocorrelation coeffieients are first obtained and updated during nonspeech periods. Then, the effect of additive noise in the input speech is removed by subtracting values of the noise autocorrelation coefficients of corrupted speech in the course of computation of linear prediction coefficients. When signal-to-noise ratio of the input speech ranges from 0 to 10 dB, a performance improvement of about 5 dB can be gained by using this method. The proposed method is computationally very efficient and requires a small storage area.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.405-408
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• 2002

LSP(Line Spectrum Pairs) Parameter is used for speech analysis in vocoders or recognizers since it has advantages of constant spectrum sensitivity. low spectrum distortion and easy linear interpolation. However the method of transforming LPC(Linear Predictive Coding) into LSP is so complex that it takes much time to compute. Among conventional methods, the real root method is considerably simpler than others, but nevertheless, it still suffers from its jndeterministic computation time because the root searching is processed sequentially in frequency region. We suggest a method of reducing the LSP transformation time using voice characteristics The proposed method is to apply search order and interval differently according to the distribution of LSP parameters. in comparison with the conventional real root method, the proposed method results in about 46.5% reduction. And, the total computation time is reduce to about 5% in the G.723.1 vocoder.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.6
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• pp.786-796
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• 2014

This paper presents a new approach to design a robust tracking controller for linear time-invariant systems with uncertain time-delay. By introducing the model following control (MFC) structure which consists of two loops in nature, we show that the controller is capable of having a predictive control action and effectively tracking the reference output with a desired transient response as well. Three design techniques to achieve good tracking performance are suggested. It is also analytically shown that the tracking performance of the proposed scheme is more robust than that of typical single-loop feedback structure. An illustrative example is given to compare the tracking performances of the proposed methods with a single loop method.