• Journal of Broadcast Engineering
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• v.19 no.1
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• pp.64-74
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• 2014

The primary and ambient signal decomposition of a stereo sound is a key step to the stereo upmix. The principal component analysis (PCA) is one of the most widely used methods of primary-ambient signal decomposition. However, previous PCA-based decomposition algorithms assume that stereo sound sources are only amplitude-panned without any consideration of phase difference. So it occurs some performance degradation in case of live recorded stereo sound. In this paper, we propose a new PCA-based stereo decomposition algorithm that can consider the phase difference between the channel signals. The proposed algorithm overcomes limitation of conventional signal model using PCA with phase alignment. The phase alignment is realized by using inter-channel phase difference (IPD) which is widely used in parametric stereo coding. Moreover, Enhanced Modified PCA(EMPCA) is combined to solve the problem of conventional PCA caused by Primary to Ambient energy Ratio(PAR) and panning angle dependency. The simulation results are presented to show the improvements of the proposed algorithm.

• The Transactions of the Korea Information Processing Society
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• v.2 no.5
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• pp.777-786
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• 1995

This paper describes several algorithms for technology mapping of logic functions into interesting and popular FPGAs that use look-up table memories. In order to improve the technology mapping for FPGA, some existing multi-level logic synthesis, decomposition reduction and packing techniques are analyzed and compared. And then new algorithms such as node-pair decomposition, merging fanin, unified reduction and multiple output decomposition which are used for combinational logic design, are proposed. The cost function is used to minimize the number of CLBs and edges of the network. The cost is a linear combination of each weight that is given by user. Finally we compare our new algorithm with previous logic design technique［8］. In an experimental comparison our algorithm requires 10% fewer CLB and nets than SIS-pga.

• Bulletin of the Korean Mathematical Society
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• v.53 no.3
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• pp.853-874
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• 2016

Based on a particular overlapping domain decomposition technique, a parallel finite element discretization algorithm for the generalized Stokes equations is proposed and investigated. In this algorithm, each processor computes a local approximate solution in its own subdomain by solving a global problem on a mesh that is fine around its own subdomain and coarse elsewhere, and hence avoids communication with other processors in the process of computations. This algorithm has low communication complexity. It only requires the application of an existing sequential solver on the global meshes associated with each subdomain, and hence can reuse existing sequential software. Numerical results are given to demonstrate the effectiveness of the parallel algorithm.

• Journal of the Korea Society for Simulation
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• v.13 no.1
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• pp.11-23
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• 2004

The decomposition of a structuring element for a morphological operation reduces the amount of the computation required for executing the operation. In this paper, we present a new technique for the decomposition of convex structuring elements for morphological operations. We formulated the linear constraints for the decomposition of a convex polygon in discrete space, then the constraints are applied to the decomposition of a convex structuring element. Also, a cost function is introduced to represent the optimal criteria for decomposition. We use linear integer programming technique to find the combination of basis structuring elements which minimizes the amount of the computation required for executing the morphological operation. Formulating different cost functions for different implementation methods and computer architectures, we can determine the optimal decompositions which guarantee the minimal amounts of computation on different computing environment.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.4
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• pp.419-424
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• 2019

In this paper, we proposed an algorithm to estimate the desired target in wideband jamming signal environment. In order to suppress the jamming signal, we use the spatial time adaptive algorithm and QR decomposition to obtain the optimal weight. The spatial time adaptive algorithm of adaptive array antenna system multiplies the tap delay signal by a complex weight to obtain a weight. In order to minimize the power consumption because of the inverse matrix, optimal weight is obtained by using QR decomposition. Through simulation, we compare and analyze the performance of the proposed algorithm and the existing algorithm. In the target estimation of [-40o,0o,+40o], the proposed algorithm estimated all three targets, but the existing algorithm estimated only [0o] due to of the jamming signal. We prove that the proposed algorithm improves performance by removing the jamming signal and estimating the target accurately.

• The KIPS Transactions:PartA
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• v.9A no.3
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• pp.363-370
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• 2002

OPKFDD (Ordered Pseudo-Kronecker Functional Decision Diagram) is one of ordered-DDs (Decision Diagrams) in which each node can take one of three decomposition types : Shannon, positive Davio and negative Davio decompositions. Whereas OBDD (Ordered Binary Decision Diagram) uses only the Shannon decomposition in each node, OPKFDD uses the three decompositions and generates representations of functions with smaller number of nodes than other DDs. However, this leads to the extreme difficulty of getting an optimal solution for the minimization of OPKFDD. Since an appropriate decomposition type has to be chosen for each node, the size of the representation is decided by the selection of the decomposition type. We propose a heuristic method to generate OPKFDD efficiently from the OBDD of the given function and the algorithm of the decision of decomposition type for a given variable ordering. Experimental results demonstrate the performance of the algorithm.

• Journal of Communications and Networks
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• v.11 no.1
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• pp.20-25
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• 2009

The maximum likelihood detection with QR decomposition and M-algorithm (QRM-MLD) has been presented as a suboptimum multiple-input multiple-output (MIMO) detection scheme which can provide almost the same performance as the optimum maximum likelihood (ML) MIMO detection scheme but with the reduced complexity. However, due to the lack of parallelism and the regularity in the decoding structure, the conventional QRM-MLD which uses the tree-structure still has very high complexity for the very large scale integration (VLSI) implementation. In this paper, we modify the tree-structure of conventional QRM-MLD into trellis-structure in order to obtain high operational parallelism and regularity and then apply the Viterbi algorithm to the QRM-MLD to ease the burden of the VLSI implementation.We show from our selected numerical examples that, by using the QRM-MLD with our proposed trellis-structure, we can reduce the complexity significantly compared to the tree-structure based QRM-MLD while the performance degradation of our proposed scheme is negligible.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.2
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• pp.33-40
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• 2000

In this study, a shape decomposition method using morphological operations is studied for decomposing the complex shape in 2-D image into its simple primitive elements. The serious drawback of conventional shape representation algorithm is that primitive elements are extracted too much to represent and to describe the shape. To solve these problems, a new shape decomposition algorithm using primitive elements that are similar to the geometrical characteristics of shape and 4 scan modes is proposed in this study. The multiple primitive elements as circle, square, and rhombus are extracted by using multiscan modes in a new algorithm. This algorithm have the characteristics that description error and number of primitive elements is reduced. Then, description efficiency is improved. The procedures is also simple and the processing time is reduced.

• The Journal of Natural Sciences
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• v.7
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• pp.27-35
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• 1995

This paper introduces a VLSI (Very Large Scale Integrated Circuit) implementation of the 2-D Discrete Cosine Transform (DCT) with an application to image and video coding. This implementation, which is based upon a state space model, uses both algorithm and data partitioning to achieve high efficiency. With this implementation, the amount of data transfers between the processing elements (PEs) are reduced and all the data transfers are limitted to be local. This system accepts the input as a progressively scanned data stream which reduces the hardware required for the input data control module. With proper ordering of computations, a matrix transposition between two matrix by matrix multiplications, which is required in many 2-D DCT systems based upon a row-column decomposition, can be also removed. The new implementation scheme makes it feasible to implement a single 2-D DCT VLSI chip which can be easily expanded for a larger 2-D DCT by cascading these chips.

• The Transactions of the Korea Information Processing Society
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• v.4 no.11
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• pp.2923-2930
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• 1997

This paper describes two algorithms for technology mapping of multiple output functions into interesting and popular FPGAs (Field Programmable Gate Arrays) that lise look-up table memories. For improvement of technology mapping for FPGA, we use the functional decomposition method for multiple output functions. Two algorithms are proposed. The one is the Roth-Karp algorithm extended for multiple output functions. The other is the novel and efficient algorithm which looks for common decomposition functions through the decomposition procedure. The cost function is used to minimize the number of CLBs and nets and to improve performance of the network. Finally we compare our new algorithm with previous logic design technique. Experimental results show significant reduction in the number of CLBs and nets.