• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.38B no.9
• /
• pp.765-774
• /
• 2013

In this paper, we present a cooperative compressed spectrum sensing scheme for correlated signals in decentralized wideband cognitive radio networks. Compressed sensing is a signal processing technique that can recover signals which are sampled below the Nyquist rate with high probability, and can solve the necessity of high-speed analog-to-digital converter problem for wideband spectrum sensing. In compressed sensing, one of the main issues is to design recovery algorithms which accurately recover original signals from compressed signals. In this paper, in order to achieve high recovery performance, we consider the multiple measurement vector model which has a sequence of compressed signals, and propose a cooperative sparse Bayesian recovery algorithm which models the temporal correlation of the input signals.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.31 no.3 s.258
• /
• pp.395-402
• /
• 2007

This paper considers about the tilt measurement of lens module with multiple lenses. The tilt between lenses in lens module and barrel or between image sensor and barrel can be measured precisely with the proposed algorithm. The magnitude and direction of the tilt vector of lens and image sensor can be measured from the best focal surface. The selecting and setting of image sensor, test chart, image sensor centering to lens module, axis align, focus measure method are also explained to get highly precise tilt results. The proposed algorithm is verified with the lens module inspection system we developed, and the experimental results show that the tilt measure proposed in this paper is robust and precise. With the proposed tilt measurement algorithm, the tilt of an image sensor and any other lens which intermediates light can be measured.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.10
• /
• pp.2252-2258
• /
• 2013

In this paper, parallel orthogonal matching pursuit (POMP) is proposed to supplement the simultaneous orthogonal matching pursuit (S-OMP) which has been widely used as a greedy algorithm for sparse signal recovery for multiple measurement vector (MMV) problem. The process of POMP is simple but effective: (1) multiple indexes maximally correlated with the observation vector are chosen at the first iteration, (2) the conventional S-OMP process is carried out in parallel for each selected index, (3) the index set which yields the minimum residual is selected for reconstructing the original sparse signal. Empirical simulations show that POMP for MMV outperforms than the conventional S-OMP both in terms of exact recovery ratio (ERR) and mean-squared error (MSE).

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.9
• /
• pp.4418-4437
• /
• 2017

In this paper a three-phase secure compressive sensing (CS) and received signal strength (RSS) based target localization approach is proposed to mitigate the effect of malicious node attack. RSS measurements are first arranged into a group of subsets where the same measurement can be included in multiple subsets. Intermediate target position estimates are then produced using individual subsets of RSS measurements and the CS technique. From the intermediate position estimates, the residual error vector and residual error square vector are formed. The least median of residual error square is utilized to define a verifier parameter. The selected residual error vector is utilized along with a threshold to determine whether a node or measurement is under attack. The final target positions are estimated by using only the attack-free measurements and the CS technique. Further, theoretical analysis is performed for parameter selection and computational complexity evaluation. Extensive simulation studies are carried out to demonstrate the advantage of the proposed CS-based secure localization approach over the existing algorithms.

• Proceedings of the KSME Conference
• /
• 2001.06e
• /
• pp.536-541
• /
• 2001

A high resolution digital cinematic Particle Image Velocimetry(PIV) has been developed. The system consists of a high speed CCD camera, a continuous Ar-ion laser and a computer with camera controller. To improve the spatial resolution, we adopt a Recursive Technique for velocity interrogation. At first, we obtain a velocity vector for a larger interrogation window size based on the conventional two-frame cross-correlation PIV analysis using the FFT algorithm. Based on the knowing velocity information, more spatially resolved velocity vectors are obtained in the next iteration step with smaller interrogation windows. The correct velocity vector at the first step is found to be critical, so we apply a Multiple Correlation Validation(MCV) technique in order to decrease the spurious vectors. The MCV technique turns out to improve SNR(Signal to Noise Ratio) of the correlation table. The developed cinematic PIV method has been applied to the measurement of the unsteady flow characteristics of a Rushton turbine mixer. A total of 3,245 instantaneous velocity vectors were successfully obtained with 4 ms time resolution. The acquired spatial resolution corresponds the performance of the conventional high resolution digital PIV system using a $1K{\times}1K$ CCD camera.

• Journal of the Korea Society of Computer and Information
• /
• v.21 no.1
• /
• pp.107-113
• /
• 2016

In this paper, by managing the biometric data is changed with the passage of time, a systematic and scientifically propose a framework to increase the bio-vector generation efficiency of the smart health care. Increasing the development of human life as a medicine and has emerged smart health care according to this. Organic and efficient health management becomes possible to generate a vector when the biological domain to the wireless communication infrastructure based on the measurement of the health status and to take action in accordance with the change of the physical condition. In this paper, we propose a framework to create a bio-vector that contains information about the current state of health of the person. In the proposed framework, Bio vectors may be generated by collecting the biometric data such as blood pressure, pulse, body weight. Biometric data is the raw data from the bio-vector. The scope of the primary data can be set to active. As the collecting biometric data from multiple items of the bio-recognition vectors may increase. The resulting bio-vector is used as a measure to determine the current health of the person. Bio-vector generating the proposed framework, it can aid in the efficiency and systemic health of healthcare for the individual.

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.5
• /
• pp.1500-1510
• /
• 2000

In this paper, a CDMA (Code Division Multiple Access) field engineering system is designed and implemented for managing cellular telecommunication base stations. For high quality of CDMA service, optimized cell planning is crucial. For such cell planning, base stations must be managed based on analysis of CDMA field dta. The proposed system consists of two modules: a measurement module and au analysis of CDMA field dta. eh proposed system consists of tow modules; a measurement module and an analysis module. The measurement module collects various CDMA field dta and displays them on a vector map in a real-time manner. The analysis module associates measured data with various related information, e.g. base station information, and process them statistically. The proposed system can drastically reduce base station management cost.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.25 no.11
• /
• pp.1535-1542
• /
• 2001

A high resolution digital cinematic Particle Image Velocimetry(PIV) has been developed. The system consists of a high speed CCD camera, a continuous Ar-ion laser and a computer with camera controller. To improve the spatial resolution, we adopt a Recursive Technique for velocity interrogation. At first, we obtain a velocity vector fur a larger interrogation window size based on the conventional two-frame cross-correlation PIV analysis using the FFT algorithm. Based on the knowing velocity information, more spatially resolved velocity vectors are obtained in the next iteration step with smaller interrogation windows. When the correct velocity vector at the first step is found to be critical, a Multiple Correlation Validation(MCV) technique is applied to decrease the spurious vectors. The MCV technique turns out to improve SNR(Signal to Noise Ratio) of the correlation table. The developed cinematic PIV method has been applied to the measurement of the unsteady flow characteristics of a Rushton turbine mixer. A total of 3,245 instantaneous velocity vectors were successfully obtained with 4 ms time resolution. The acquired spatial resolution corresponds to the conventional high resolution digital PIV system using a 1K ${\times}$ 1K CCD camera.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.16 no.5
• /
• pp.223-229
• /
• 2023

This Paper propose the method that measure main system parameters for PI(proportional-integral) current control of a.c. motor adopting the vector control technique. For current control, the PI control input is could be tuning by several selective methods. Among the several methods, the method that using the main system parameters, wire resistance and inductance, are frequently used. In this study, the technique to dissect and measure these two system parameters through the results of simple feedback control. This analytic measurement method is measuring parameters step by step dissecting the results of P control using simple proportional feedback gain about the unit step or multiple step reference command. This strategy is an real time analytic measurement method that calculate current control gains of torque component and flux component both for vector control of A.C. motor without introducing the further measurement circuits and complex measuring algorithms.

• Structural Engineering and Mechanics
• /
• v.15 no.3
• /
• pp.299-314
• /
• 2003

This investigation presents an efficient method for identifying modal characteristics from the measured displacement, velocity and acceleration signals of multiple channels on structural systems. A Vector Backward Auto-Regressive model (VBAR) that describes the relationship between the output information in different time steps is used to establish a backward state equation. Generally, the accuracy of the identified dynamic characteristics can be improved by increasing the order of the Auto-Regressive model (AR) in cases of measurement of data under noisy circumstances. However, a higher-order AR model also induces more numerical modes, only some of which are the system modes. The proposed VBAR model provides a clear characteristic boundary to separate the system modes from the spurious modes. A numerical example of a lumped-mass model with three DOFs was established to verify the applicability and effectiveness of the proposed method. Finally, an offshore platform model was experimentally employed as an application case to confirm the proposed VBAR method can be applied to real-world structures.