• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.2112-2115
• /
• 2005

This paper considers the synthesis of non-fragile $H_{\infty}$ state feedback controllers for singular systems and static state feedback controller with multiplicative uncertainty. The sufficient condition of controller existence, the design method of non-fragile $H_{\infty}$ controller, and the measure of non-fragility in controller are presented via LMI(linear matrix inequality) technique. Also, through singular value decomposition, some changes of variables, and Schur complements, the sufficient condition can be rewritten as LMI form in terms of transformed variables. Therefore, the obtained non-fragile $H_{\infty}$ controller guarantees the asymptotic stability and disturbance attenuation of the closed loop singular systems within a prescribed degree. Finally, a numerical example is given to illustrate the design method.

• 한국데이터정보과학회:학술대회논문집
• /
• 2003.05a
• /
• pp.133-133
• /
• 2003

• ETRI Journal
• /
• v.40 no.4
• /
• pp.421-434
• /
• 2018

The application of deep neural networks (DNNs) to connect the world with cyber physical systems (CPSs) has attracted much attention. However, DNNs require a large amount of memory and computational cost, which hinders their use in the relatively low-end smart devices that are widely used in CPSs. In this paper, we aim to determine whether DNNs can be efficiently deployed and operated in low-end smart devices. To do this, we develop a method to reduce the memory requirement of DNNs and increase the inference speed, while maintaining the performance (for example, accuracy) close to the original level. The parameters of DNNs are decomposed using a hybrid of canonical polyadic-singular value decomposition, approximated using a tensor power method, and fine-tuned by performing iterative one-shot hybrid fine-tuning to recover from a decreased accuracy. In this study, we evaluate our method on frequently used networks. We also present results from extensive experiments on the effects of several fine-tuning methods, the importance of iterative fine-tuning, and decomposition techniques. We demonstrate the effectiveness of the proposed method by deploying compressed networks in smartphones.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.15 no.5
• /
• pp.39-49
• /
• 2015

Some characters and construction theorems of Pseudo Jacket Matrix which is generalized from Jacket Matrix introduced by Jacket Matrices: Construction and Its Application for Fast Cooperative Wireless signal Processing[27] was announced. In this paper, we proposed some examples of Pseudo inverse Jacket matrix, such as $2{\times}4$, $3{\times}6$ non-square matrix for the MIMO channel. Furthermore we derived MIMO singular value decomposition (SVD) pseudo inverse channel and developed application to utilize SVD based on channel estimation of partitioned antenna arrays. This can be also used in MIMO channel and eigen value decomposition (EVD).

• Journal of Korea Society of Industrial Information Systems
• /
• v.13 no.3
• /
• pp.1-8
• /
• 2008

In the event of a traffic accident, a fire accident, or a criminal act, anyone will be able to capture these important moments and use authentic photographs for evidence purposes. Digital watermarking is able to ensure that the digital photographs taken from a particular camera-phone are authentic and indeed. This paper presents a blind image watermarking technique for digital phone camera. This method is based on singular value decomposition (SVD) and wavelet decomposition. Experimental results show that the proposed technique performs well in security and robustness against JPEG compression.

• Proceedings of the IEEK Conference
• /
• 2001.06c
• /
• pp.47-50
• /
• 2001

This paper took advantage of SVD (Singular value Decomposition) techniques of LSI(Latent Semantic Indexing) to grasp easily terminology distribution. Existent LSI did to static database, propose that apply to dynamic database in this paper. But, if dynamic applies LSI to database, updating problem happens. Existent updating way is Recomputing method, Folding-in method, SVD-updating method. Proposed QR decomposition method to show performance improvement than existent three methods in this paper.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.40 no.3
• /
• pp.99-108
• /
• 2003

This paper is concerned with the problem of designing a guaranteed cost state feedback controller for singular systems with time-varying delays. The sufficient condition for the existence of guaranteed cost controller, the controller design method, and the optimization problem to get the upper bound of guaranteed cost function are proposed by LMI(linear matrix inequality), singular value decomposition, Schur complements, and change of variables. Since the obtained sufficient conditions can be changed to LMI form, all solutions including controller gain and the upper bound of guaranteed cost function can be obtained simultaneously. Moreover, the proposed controller design method can be extended to the problem of robust guaranteed cost controller design method for singular systems with parameter uncertainties and time-varying delays. The validity of the proposed design algorithm is investigated through a numerical example.

• Journal of Electrical Engineering and Technology
• /
• v.10 no.3
• /
• pp.766-776
• /
• 2015

It is well known that series arc faults in Low Voltage DC (LVDC) distribution system occur at unintended points of discontinuity within an electrical circuit. These faults can make circuit breakers not respond timely due to low fault current. It, therefore, is needed to detect the series fault for protecting circuits from electrical fires. This paper proposes a novel scheme to detect the series arc fault using Wavelet Singular Value Decomposition (WSVD) and state diagram. In this paper, the fault detector developed is designed by using three criterion factors based on the RMS value of Singular value of Approximation (SA), Sum of the absolute value of Detail (SD), and state diagram. LVDC distribution system including AC/DC and DC/DC converter is modeled to verify the proposed scheme using ElectroMagnetic Transient Program (EMTP) software. EMTP/MODELS is also utilized to implement the series arc model and WSVD. Simulation results according to various conditions clearly show the effectiveness of the proposed scheme.

• Journal of Broadcast Engineering
• /
• v.13 no.3
• /
• pp.289-298
• /
• 2008

We propose an SNR-scalable coding algorithm for three-dimensional mesh sequences based on singular value decomposition (SVD). SVD achieves a coding gain by representing a mesh sequence with a small number of basis vectors and singular values. First, we introduce a bit plane coding scheme and derive a quantitative relationship between each bit plane and the reconstructed image quality. Using the relationship, we develop a rate-distortion (RD) optimized coding algorithm. Moreover, we propose prediction techniques to exploit the spatio-temporal correlations in real mesh sequences. Simulation results demonstrate that the proposed algorithm provides significantly better RD performance than conventional SVD coders.

• Structural Engineering and Mechanics
• /
• v.22 no.4
• /
• pp.401-418
• /
• 2006

Solutions to the problems of structural parameter estimation from modal response using leastsquares minimization of force or displacement residuals are generally sensitive to noise in the response measurements. The sensitivity of the parameter estimates is governed by the physical characteristics of the structure and certain features of the noisy measurements. It has been shown that the regularization method can be used to reduce effects of the measurement noise on the estimation error through adding a regularization function to the parameter estimation objective function. In this paper, we adopt the regularization function as the Euclidean norm of the difference between the values of the currently estimated parameters and the a priori parameter estimates. The effect of the regularization function on the outcome of parameter estimation is determined by a regularization factor. Based on a singular value decomposition of the sensitivity matrix of the structural response, it is shown that the optimal regularization factor is obtained by using the maximum singular value of the sensitivity matrix. This selection exhibits the condition where the effect of the a priori estimates on the solutions to the parameter estimation problem is minimal. The performance of the proposed algorithm is investigated in comparison with certain algorithms selected from the literature by using a numerical example.