• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.3
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• pp.16-23
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• 1998

In this paper, we present a fast and efficient Iterative Improvement Partitioning(IIP) technique for VLSI circuits and hybrid bucket structures on its implementation. The IIP algorithms are very widely used in VLSI circuit partition due to their time efficiency. As the performance of these algorithms depends on choices of moving cell, various methods have been proposed. Specially, Cluster-Removal algorithm by S. Dutt significantly improved partition quality. We indicate the weakness of previous algorithms wjere they used a uniform method for choice of cells during for choice of cells during the improvement. To solve the problem, we propose a new IIP technique that selects the method for choice of cells according to the improvement status and present hybrid bucket structures for easy implementation. The time complexity of proposed algorithm is the same with FM method and the experimental results on ACM/SIGDA benchmark circuits show improvment up to 33-44%, 45%-50% and 10-12% in cutsize over FM, LA-3 and CLIP respectively. Also with less CUP tiem, it outperforms Paraboli and MELO represented constructive-partition methods by about 12% and 24%, respectively.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.71-77
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• 1995

In this paper are proposed robust iterative learning control(ILC) algorithms for both linear continuous time-invariant system and linear discrete-time system. In contrast to conventional methods, the proposed learning algorithms are constructed based on both time domain performance and iteration-domain performance. The convergence of the proposed learning algorithms is proved. Also, it is shown that the proposed method has robustness in the presence of external disturbances and the convergence accuracy can be improved. A numerical external disturbances and the convergence accuracy can be improved. A numerical example is provided to show the effectiveness of the proposed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.4160-4176
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• 2015

Data compression like image and video compression has come a long way since the introduction of Compressive Sensing (CS) which compresses sparse signals such as images, videos etc. to very few samples i.e. M < N measurements. At the receiver end, a robust and efficient recovery algorithm estimates the original image or video. Many prominent algorithms solve least squares problem (LSP) iteratively in order to reconstruct the signal hence consuming more processing time. In this paper non-iterative threshold based recovery algorithm (NITRA) is proposed for the recovery of images and videos without solving LSP, claiming reduced complexity and better reconstruction quality. The elapsed time for images and videos using NITRA is in ㎲ range which is 100 times less than other existing algorithms. The peak signal to noise ratio (PSNR) is above 30 dB, structural similarity (SSIM) and structural content (SC) are of 99%.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.180-191
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• 2008

An Adaptive Random Testing (ART) is one of test case generation algorithms that are designed to detect common failure patterns within input domain. The ART algorithm shows better performance than that of pure Random Testing (RT). Distance-bases ART (D-ART) and Restriction Random Testing (RRT) are well known examples of ART algorithms which are reported to have good performances. But significant drawbacks are observed as quadratic runtime and non-uniform distribution of test case. They are mainly caused by a huge amount of distance computations to generate test case which are distance based method. ART through Iterative Partitioning (IP-ART) significantly reduces the amount of computation of D-ART and RRT with iterative partitioning of input domain. However, non-uniform distribution of test case still exists, which play a role of obstacle to develop a scalable algerian. In this paper we propose a new ART method which mitigates the drawback of IP-ART while achieving improved fault-detection capability. Simulation results show that the proposed one has about 9 percent of improved F-measures with respect to other algorithms.

• Journal of the Korean Society of Radiology
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• v.13 no.3
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• pp.465-472
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• 2019

To investigate the effects of iterative reconstruction algorithms on fat measurements using computed tomography (CT), we comparatively and quantitatively analyzed the ratios of visceral, subcutaneous, and visceral-subcutaneous fat areas as well as the variations of HU and noise of visceral and subcutaneous fat using ADMIRE strength and attempted to identify any difference between them. Experimental results showed that no statistically significant difference existed among the visceral, subcutaneous, and visceral-subcutaneous fat area ratios HU of visceral fat area and HU of subcutaneous fat area when applying ADMIRE as compared with existing conventional filtered back projection algorithms. However, as the ADMIRE strength increases, the noise of visceral and subcutaneous fat decreases by up to 12.1% and 19.2%, respectively. In conclusion, iterative reconstruction algorithms have no effect on the visceral, subcutaneous, and visceral-subcutaneous fat area ratios, which are indicators of fat measurement using CT.

• Journal of applied mathematics & informatics
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• v.7 no.1
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• pp.101-113
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• 2000

In this paper, we introduce and study a new class of variational inclusions, called the set-valued quasi variational inclusions. The resolvent operator technique is used to establish the equivalence between the set-valued variational inclusions and the fixed point problem. This equivalence is used to study the existence of a solution and to suggest a number of iterative algorithms for solving the set-valued variational inclusions. We also study the convergence criteria of these algorithms.

• Journal of applied mathematics & informatics
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• v.27 no.1_2
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• pp.37-48
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• 2009

In the theory and the applications of Numerical Linear Algebra, the class of H-matrices is very important. In recent years, many appeared works have proposed iterative criterion for H-matrices. In this paper, we provide a new type of interleaved iterative algorithm, which is always convergent in finite steps for H-matrices and needs fewer iterations than those proposed in the related works, and a corresponding algorithm for general matrix, which eliminates the redundant computations when the given matrix is not an H-matrix. Finally, several numerical examples are presented to show the effectiveness of the proposed algorithms.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.50
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• pp.333-340
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• 1999

An ideal traffic control system should consider simultaneously both route guidance of vehicles and signal policies at intersection of a traffic network. It is known that an iterative procedure gives an optimal route to each vehicle in the network. This paper presents an iterative procedure to find an optimal signal plan for the network. We define the optimal solution as a signal equilibrium. From the definition of signal equilibrium, we prove that the fixed point solution of the iterative procedure is a signal equilibrium, when optimal signal algorithms are implemented at each intersection of the network. A combined model of route guidance and signal planning is also suggested by relating the route guidance procedure and the signal planning procedure into a single loop iterative procedure.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.6
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• pp.579-583
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• 2012

The purpose of this paper is to suggest IDE (Incremental Displacement Estimation) algorithm for the previously proposed visually servoed paired structured light system. The system is composed of two sides facing with each other, each with one or two lasers with a 2-DOF manipulator, a camera, and a screen. The 6-DOF displacement between two sides can be estimated by calculating the positions of the projected laser beams and rotation angles of the manipulators. In the previous study, Newton-Raphson or EKF (Extended Kalman Filter) has been used as an estimation algorithm. Although the various experimental tests have validated the performance of the system and estimation algorithms, the computation time is relatively long since aforementioned algorithms are iterative methods. Therefore, in this paper, a non-iterative incremental displacement estimation algorithm which updates the previously estimated displacement with a difference of the previous and the current observed data is introduced. To verify the performance of the algorithm, experimental tests have been performed. The results show that the proposed non-iterative algorithm estimates the displacement with the same level of accuracy compared to the EKF with multiple iterations with significantly less computation time.

• Journal of Biomedical Engineering Research
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• v.35 no.5
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• pp.142-150
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• 2014

The key to model-based iterative reconstruction (MBIR) algorithms for transmission computed tomography lies in the ability to accurately model the data formation process from the emitted photons produced in the transmission source to the measured photons at the detector. Therefore, accurately modeling the system matrix that accounts for the data formation process is a prerequisite for MBIR-based algorithms. In this work we compared quantitative performance of the three representative ray-driven methods for calculating the system matrix; the ray-tracing method (RTM), the distance-driven method (DDM), and the strip-area based method (SAM). We implemented the ordered-subsets separable surrogates (OS-SPS) algorithm using the three different models and performed simulation studies using a digital phantom. Our experimental results show that, in spite of the more advanced features in the SAM and DDM, the traditional RTM implemented in the OS-SPS algorithm with an edge-preserving regularizer out-performs the SAM and DDM in restoring complex edges in the underlying object. The performance of the RTM in smooth regions was also comparable to that of the SAM or DDM.