• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.753-757
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• 1994

In control system design, whether the various subsystems are in discrete time or continuous time, the state space is usually regarded as a continuum. However, when the system is implemented, some subsystems may have a state space which is a subset of finite computer arithmetic. This is an important concern if a subsystem has chaotic behaviour, because it is theoretically possible for rich and varied motions in a continuum to collapse to trivial and degenerate behaviour in a finite and discrete state space [5]. This paper discusses new ways to describe these effects and reports on computer experiments which document and illustrate such collapsing behaviour.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.1009-1012
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• 1999

An analytical performance model that can predict the performance of a superscalar processor employing multiple branch prediction is introduced. The model is based on the conditional independence probability and the basic block size of instructions, with the degree of multiple branch prediction, the fetch rate, and the window size of a superscalar architecture. Trace driven simulation is performed for the subset of SPEC integer benchmarks, and the measured IPCs are compared with the results derived from the model. As the result, our analytic model could predict the performance of the superscalar processor using multiple branch prediction within 6.6 percent on the average.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.3
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• pp.275-282
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• 2014

One of the most widely used methods for dimensionality reduction is principal component analysis (PCA). However, the reduced dimensions from PCA do not provide a clear interpretation with respect to the original features because they are linear combinations of a large number of original features. This interpretation problem can be overcome by feature selection approaches that identifying the best subset of given features. In this study, we propose an unsupervised feature selection method based on the geometrical information of PCA loading vectors. Experimental results from a simulation study demonstrated the efficiency and usefulness of the proposed method.

• Communications for Statistical Applications and Methods
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• v.25 no.5
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• pp.453-470
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• 2018

We study how to distinguish the parameters of the sparse autoregressive (AR) process from zero using a non-convex penalized estimation. A class of non-convex penalties are considered that include the smoothly clipped absolute deviation and minimax concave penalties as special examples. We prove that the penalized estimators achieve some standard theoretical properties such as weak and strong oracle properties which have been proved in sparse linear regression framework. The results hold when the maximal order of the AR process increases to infinity and the minimal size of true non-zero parameters decreases toward zero as the sample size increases. Further, we construct a practical method to select tuning parameters using generalized information criterion, of which the minimizer asymptotically recovers the best theoretical non-penalized estimator of the sparse AR process. Simulation studies are given to confirm the theoretical results.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1960-1963
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• 2002

Transmit diversity schemes we an effective capacity improvement method for down link of wideband code division multiple access (W-CDMA) systems. In this paper, we propose to use transmit antenna subset selection scheme in conjunction with closed loop transmit adaptive array (TxAA). The proposed scheme selects N$\_$s/ optimum antennas among N$\_$${\gamma}$/(>N$\_$s/) transmit antennas in order to maximize diversity gain from selected antennas, and also reduces the cost of RE chains by employing two different types of RF modules fur the selected and the unselected antenna group, respectively. Computer simulation results show performance improvement by the proposed scheme over the conventional TxAA when considering up link control information feedback.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.2071-2074
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• 2002

This paper introduces an encoder design method of Turbo TCM (Trellis Coded Modulation) with symbol puncturing. TTCM consists of two simple trellis codes in parallel and modulator. To obtain an good encoder, we calculate the free distance by the assumption that the punctured symbol is transmitted from the subset that consist of signals with the same systematic bit at random. We develop a search program to find the component encoder which maximize the free distance. Especially, for 8-PSK with code rate 2/3, we search for the component codes. We find a new encoder which has better BER performance than that of Robertson′s encoder. We verify the results through the simulation."

• Journal of Communications and Networks
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• v.17 no.2
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• pp.157-161
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• 2015

A new block low-density parity-check (Block-LDPC) code based on quadratic permutation polynomials (QPPs) is proposed. The parity-check matrix of the Block-LDPC code is composed of a group of permutation submatrices that correspond to QPPs. The scheme provides a large range of implementable LDPC codes. Indeed, the most popular quasi-cyclic LDPC (QC-LDPC) codes are just a subset of this scheme. Simulation results indicate that the proposed scheme can offer similar error performance and implementation complexity as the popular QC-LDPC codes.

• ETRI Journal
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• v.42 no.4
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• pp.562-574
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• 2020

Quadrature spatial modulation (QSM) utilizes the in-phase and quadrature spatial dimensions to transmit the real and imaginary parts of a single signal symbol, respectively. The improved QSM (IQSM) transmits two signal symbols per channel use through a combination of two antennas for each of the real and imaginary parts. The main contributions of this study can be summarized as follows. First, we derive an upper bound for the error performance of the IQSM. We then design constellation sets that minimize the error performance of the IQSM for several system configurations. Second, we propose a double QSM (DQSM) that transmits the real and imaginary parts of two signal symbols through any available transmit antennas. Finally, we propose a parallel IQSM (PIQSM) that splits the antenna set into equal subsets and performs IQSM within each subset using the same two signal symbols. Simulation results demonstrate that the proposed constellations significantly outperform conventional constellations. Additionally, DQSM and PIQSM provide a performance similar to that of IQSM while requiring a smaller number of transmit antennas and outperform IQSM with the same number of transmit antennas.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.3
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• pp.42-48
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• 2002

Multiple description coding Is source coding for multiple channels such that a decoder which receives an arbitrary subset of the channels may produce a useful reconstruction. This paper presents an efficient multiple description coder using a newly designed EZW coding method. We first propose EZW coder which has expanded threshold and two subordinate passes. And then we present multiple description coder which has two coding channels using the proposed EZW coders. To evaluate the performance of the proposed coder, we provide an image coding applications with two descriptions and compare multiple description image coding results reported to date. Simulation results show that the proposed method has a better performance than the polyphase transform method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1618-1637
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• 2018

By means of compressive sensing (CS) technique, this paper considers the collection of sensor data with spatiotemporal correlations in wireless sensor networks (WSNs). In energy-constrained WSNs, one-dimensional CS methods need a lot of data transmissions since they are less applicable in fully exploiting the spatiotemporal correlations, while the Kronecker CS (KCS) methods suffer performance degradations when the signal dimension increases. In this paper, an appropriate sensing matrix as well as an efficient sensing method is proposed to further reduce the data transmissions without the loss of the recovery performance. Different matrices for the temporal signal of each sensor node are separately designed. The corresponding energy-efficient data gathering method is presented, which only transmitting a subset of sensor readings to recover data of the entire WSN. Theoretical analysis indicates that the sensing structure could have the relatively small mutual coherence according to the selection of matrix. Compared with the existing spatiotemporal CS (CS-ST) method, the simulation results show that the proposed efficient measurement method could reduce data transmissions by about 25% with the similar recovery performance. In addition, compared with the conventional KCS method, for 95% successful recovery, the proposed sensing structure could improve the recovery performance by about 20%.