• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.12 no.1
• /
• pp.211-216
• /
• 2012

Control Theory for continuous-time system has been well developed. Due to the development of computer technology, digital control scheme are employed in many areas. When delays are in control systems, it is hard to control the system efficiently. Delays by controller-to-actuator and sensor-to-controller deteriorate control performance and could possibly destabilize the overall system. In this paper, a new approximated discretization method and digital design for control systems with multiple state, input and output delays and a generalized bilinear transformation method with a tunable parameter are also provided, which can re-transform the integer time-delayed discrete-time model to its continuous-time model. Illustrative example is given to demonstrate the effectiveness of the developed method.

• Journal of the Korean Data and Information Science Society
• /
• v.26 no.6
• /
• pp.1259-1269
• /
• 2015

Recently, big data is positioning as a keyword in the academic circles. And usefulness of big data is carried into government, a local public body and enterprise as well as academic circles. Also they are endeavoring to obtain useful information in big data. This research mainly deals with analyses of box office success or failure of films using text mining. For data, it used a portal site 'D' and film review data, grade point average and the number of screens gained from the Korean Film Commission. The purpose of this paper is to propose a model to predict whether a film is success or not using these data. As a result of analysis, the correct classification rate by the prediction model method proposed in this paper is obtained 95.74%.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.33 no.1A
• /
• pp.74-84
• /
• 2008

UWB radio systems have drawn attention during the last few years. These systems are the core technique for ubiquitous home and enable to co-exist with other narrow band systems over the same frequency without interfering them. But UWB signals have a very low power per pulse, so they are affected by strong narrow band interferences. Specially, IEEE 802.11a systems which operate around 5GHz overlap the band of UWB signals and they will interfere with UWB systems significantly. In this paper, we propose a novel narrow band interference suppression method based on singular value decomposition(SVD) algorithm for DS-UWB in IEEE 802.15.4a channel model. The proposed method is very effective and robust for both a single user DS-UWB system and a multiuser DS-UWB system to reduce the narrow band interference.

• Journal of the Korean Data and Information Science Society
• /
• v.28 no.4
• /
• pp.721-731
• /
• 2017

In this study, principal component analysis methods using Lasso penalty are introduced. There are two popular methods that apply Lasso penalty to principal component analysis. The first method is to find an optimal vector of linear combination as the regression coefficient vector of regressing for each principal component on the original data matrix with Lasso penalty (elastic net penalty in general). The second method is to find an optimal vector of linear combination by minimizing the residual matrix obtained from approximating the original matrix by the singular value decomposition with Lasso penalty. In this study, we have reviewed two methods of principal components using Lasso penalty in detail, and shown that these methods have an advantage especially in applying to data sets that have more variables than cases. Also, these methods are compared in an application to a real data set using R program. More specifically, these methods are applied to the crime data in Ahamad (1967), which has more variables than cases.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.53 no.3
• /
• pp.99-106
• /
• 2016

In this paper, we will discuss about correction method of missing data on noisy observation matrix and uncertainty analysis for the potential noise. In situations without missing data in an observation matrix, this solution is known to be accurately induced by SVD (Singular Value Decomposition). However, usually the several entries of observation matrix have not been observed and other entries have been perturbed by the influence of noise. In this case, it is difficult to find the solution as well as cause the 3D reconstruction error. Therefore, in order to minimize the 3D reconstruction error, above all things, it is necessary to correct reliably the missing data under noise distribution and to give a quantitative evaluation for the corrected results. This paper focuses on a method for correcting missing data using geometrical properties between 2D projected object and 3D reconstructed shape and for estimating a noise level of the observation matrix using ranks of SVD in order to quantitatively evaluate the performance of the correction algorithm.

• Smart Structures and Systems
• /
• v.18 no.3
• /
• pp.501-523
• /
• 2016

Electromechanical impedance (EMI) based structural health monitoring is performed by measuring the variation in the impedance due to the structural local damage. The impedance signals are acquired from the piezoelectric patches that are bonded on the structural surface. The impedance variation, which is directly related to the mechanical properties of the structure, indicates the presence of local structural damage. Two traditional EMI-based damage detection methods are based on calculating the difference between the measured impedance signals in the frequency domain from the baseline and the current structures. In this paper, a new structural damage detection approach by analyzing the time domain impedance responses is proposed. The measured time domain responses from the piezoelectric transducers will be used for analysis. With the use of the Time Frequency Autoregressive Moving Average (TFARMA) model, a damage index based on Singular Value Decomposition (SVD) is defined to identify the existence of the structural local damage. Experimental studies on a space steel truss bridge model in the laboratory are conducted to verify the proposed approach. Four piezoelectric transducers are attached at different locations and excited by a sweep-frequency signal. The impedance responses at different locations are analyzed with TFARMA model to investigate the effectiveness and performance of the proposed approach. The results demonstrate that the proposed approach is very sensitive and robust in detecting the bolt damage in the gusset plates of steel truss bridges.

• The Korean Journal of Applied Statistics
• /
• v.34 no.6
• /
• pp.945-956
• /
• 2021

In this study, we considered the algorithm of Legendre and Legendre (2012), which derives canonical correspondence analysis from weighted principal component analysis. And, it was proved that the canonical correspondence analysis based on the weighted principal component analysis is exactly the same as Ter Braak's (1986) canonical correspondence analysis based on the Gaussian response model. Ter Braak (1986)'s canonical correspondence analysis derived from a Gaussian response curve that can explain the abundance of species in ecology well uses the basic assumption of the species packing model and then conducts generalized linear model and canonical correlation analysis. It is derived by way of binding. However, the algorithm of Legendre and Legendre (2012) is calculated in a method quite similar to Benzecri's correspondence analysis without such assumptions. Therefore, if canonical correspondence analysis based on weighted principal component analysis is used, it is possible to have some flexibility in using the results. In conclusion, this study shows that the two methods starting from different models have the same site scores, species scores, and species-environment correlations.

• Investigative Magnetic Resonance Imaging
• /
• v.25 no.3
• /
• pp.141-155
• /
• 2021

Purpose: To develop a 3D magnetic resonance fingerprinting (MRF) method for application in high resolution knee cartilage PD, T₁, T₂ mapping. Materials and Methods: A novel 3D acquisition trajectory with golden-angle rotating radial in k_xy direction and interleaved echo planar imaging (EPI) acquisition in the k_z direction was implemented in the MRF framework. A centric order was applied to the interleaved EPI acquisition to reduce Nyquist ghosting artifact due to field inhomogeneity. For the reconstruction, singular value decomposition (SVD) compression method was used to accelerate reconstruction time and conjugate gradient sensitivity-encoding (CG-SENSE) was performed to overcome low SNR of the high resolution data. Phantom experiments were performed to verify the proposed method. In vivo experiments were performed on 6 healthy volunteers and 2 early osteoarthritis (OA) patients. Results: In the phantom experiments, the T₁ and T₂ values of the proposed method were in good agreement with the spin-echo references. The results from the in vivo scans showed high quality proton density (PD), T₁, T₂ map with EPI echo train length (N_ETL = 4), acceleration factor in through plane (R_z = 5), and number of radial spokes (N_spk = 4). In patients, high T₂ values (50-60 ms) were seen in all transverse, sagittal, and coronal views and the damaged cartilage regions were in agreement with the hyper-intensity regions shown on conventional turbo spin-echo (TSE) images. Conclusion: The proposed 3D MRF method can acquire high resolution (0.5 mm³) quantitative maps in practical scan time (~ 7 min and 10 sec) with full coverage of the knee (FOV: 160 × 160 × 120 mm³).

• The Journal of the Korea institute of electronic communication sciences
• /
• v.16 no.1
• /
• pp.125-134
• /
• 2021

With the rapid development of the film industry, the number of films is significantly increasing and movie recommendation system can help user to predict the preferences of users based on their past behavior or feedback. This paper proposes a movie recommendation system based on the latent factor model with the adjustment of mean and bias in rating. Singular value decomposition is used to decompose the rating matrix and stochastic gradient descent is used to optimize the parameters for least-square loss function. And root mean square error is used to evaluate the performance of the proposed system. We implement the proposed system with Surprise package. The simulation results shows that root mean square error is 0.671 and the proposed system has good performance compared to other papers.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.4
• /
• pp.565-571
• /
• 2021

In this paper, a compensation scheme of frequency selective IQ mismatch for high-performance radar systems based on commercial RFIC's is proposed. Besides, an optimization model and its solution based on the dimension reduction scheme using singular value decomposition are also proposed to design the optimal IQ mismatch compensation digital filter with complex coefficients. The performance of the proposed method had been analyzed through experiments using the IQ mismatch measurement and compensation system implemented on an FPGA board with a target RFIC and compared with the previous method. The experiment result showed a performance improvement of the proposed method over the existing one without noticeable increments in complexities. These performance analysis results showed that the limitation of using commercial RFIC's in high-performance radar systems due to the undesirable maximum SNR cap caused by their IQ mismatches could be overcome by employing the proposed method.