• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.95.1-95
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• 2001

This paper is concerned with a novel S-stability (stochastic-stability) concept in linear time-invariant stochastic systems, where a stochastic mode in dynamics depends on both the external disturbance and the inner-parameter variations. This leads to an EAG (eigenstructure assignment gaussian) problem; that is, the problem of associating S-eigenvalues (stochastic-eigenvalues), S-eigenvectors (stochastic-eigenvectors), and their PDFs (probability density functions) with the stochastic information of the systems with the required stochastic specifications. These results explicitly characterize how S-eigenvalues, S-eigenvectors and their PDFs in the complex plane may impose S-stability on stochastic systems.

• The Journal of the Acoustical Society of Korea
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• v.19 no.2E
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• pp.27-31
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• 2000

Evaluating log-likelihood of Gaussian mixture density is major computational burden for the keyword spotting system using continuous HMM. In this paper, we employ the bucket box intersection (BBI) algorithm to reduce the computational complexity of keyword spotting. We make some modification in implementing BBI algorithm in order to increase the discrimination ability among the keyword models. According to our keyword spotting experiments, the modified BBI algorithm reduces 50% of log-likelihood computations without performance degradation, while the original BBI algorithm under the same condition reduces only 30% of log-likelihood computations.

• Proceedings of the Optical Society of Korea Conference
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• 2003.02a
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• pp.246-247
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• 2003

In recent years, soaring traffic volumes over optical communications networks lead to the rapid advances in information communications equipments. In backbone communications networks, there has been an advance in high-density transmission through DWDM, which can simultaneously transmit numerous signals with different wavelengths. When the channel spacing is narrower, the cross-talk between channels an important parameter that guarantees to the high performance of a whole system, becomes critical. (omitted)

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.4
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• pp.869-875
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• 1996

This paper investigates a method for dtermining a threshold value based on the probability distribution function for color image segmentation. Principal components of normalized color is nalyzed and found that there are effective color transforms for outdoor scents. We esplain the functional relationship of the treshold and the probability of a regiona detection, asuming bivarate Gaussian probability density function. Experimental results show that the probability of detection is proportional to the segmented area.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.7
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• pp.847-851
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• 2004

In the original mixture density network(MDN), which was introduced by Bishop and Nabney, the parameters of the conditional probability density function are represented by the output vector of a single multi-layer perceptron. Among the recent modification of the MDNs, there is the so-called modified mixture density network, in which each of the priors, conditional means, and covariances is represented via an independent multi-layer perceptron. In this paper, we consider a further simplification of the modified MDN, in which the conditional means are linear with respect to the input variable together with the development of the MATLAB program for the simplification. In this paper, we first briefly review the original mixture density network, then we also review the modified mixture density network in which independent multi-layer perceptrons play an important role in the learning for the parameters of the conditional probability, and finally present a further modification so that the conditional means are linear in the input. The applicability of the presented method is shown via an illustrative simulation example.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.7 s.337
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• pp.27-34
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• 2005

Iterative detection (ID) has proven to be a near-optimal solution for concatenated Finite State Machines (FSMs) with interleavers over an additive white Gaussian noise (AWGN) channel. When perfect channel state information (CSI) is not available at the receiver, an adaptive ID (AID) scheme is required to deal with the unknown, and possibly time-varying parameters. The basic building block for ID or AID is the soft-input soft-output (SISO) or adaptive SISO (A-SISO) module. In this paper, Reduced State SISO (RS-SISO) algorithms have been applied for complexity reduction of the A-SISO module. We show that serially concatenated CPM (SCCPM) with AID has turbo-like performance over fading ISI channels and also RS-A-SISO systems have large iteration gains. Various design options for RS-A-SISO algorithms are evaluated. Recently developed density evolution technique is used to analyze RS-A-SISO algorithms. We show that density evolution technique that is usually used for AWGN systems is also a good analysis tool for RS-A-SISO systems over frequency-selective fading channels.

• Journal of the Korean Society of Propulsion Engineers
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• v.3 no.2
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• pp.10-17
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• 1999

This paper investigates the linear stability of both uniform and non-uniform density plane mixing layers with special emphasis on the effect of the wake component in the velocity profile. Velocity and density profiles for laminar flows are obtained from analytic profiles. Mixing layers with wakes have two generalized inflection points and two unstable modes-sinuous and varicose modes. For uniform density mixing layers, sinuous modes are more unstable than varicose modes, which shows wakes will be destabilized by sinuous modes. For non-uniform density mixing layers with high density in high speed flows, sinuous modes are more unstable than varicose modes. For non-uniform density mixing layers with high density in low speed flows, varicose modes can be more unstable than sinuous modes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.3
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• pp.127-139
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• 2014

In this paper, we present two signal processing techniques for designing binary error correction codes for Multi-Level Cell(MLC) NAND flash memory. MLC NAND flash memory saves the non-binary symbol at each cell and shows asymmetric channel LLR l-density which makes it difficult to design soft-decision binary error correction codes such as LDPC codes and Polar codes. Therefore, we apply density mirroring and EM algorithm for approximating the MLC NAND flash memory channel to the binary-input memoryless channel. The density mirroring processes channel LLRs to satisfy roughly all-zero codeword assumption, and then EM algorithm is applied to l-density after density mirroring for approximating it to mixture of symmetric Gaussian densities. These two signal processing techniques make it possible to use conventional code design algorithms, such as density evolution and EXIT chart, for MLC NAND flash memory channel.

• ETRI Journal
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• v.29 no.3
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• pp.381-389
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• 2007

In this paper we propose a graph-theoretic method based on linear congruence for constructing low-density parity check (LDPC) codes. In this method, we design a connection graph with three kinds of special paths to ensure that the Tanner graph of the parity check matrix mapped from the connection graph is without short cycles. The new construction method results in a class of (3, ${\rho}$)-regular quasi-cyclic LDPC codes with a girth of 12. Based on the structure of the parity check matrix, the lower bound on the minimum distance of the codes is found. The simulation studies of several proposed LDPC codes demonstrate powerful bit-error-rate performance with iterative decoding in additive white Gaussian noise channels.

• International Journal of Aeronautical and Space Sciences
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• v.13 no.4
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• pp.499-506
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• 2012

In this paper, a dynamic modeling for the velocity and position information of a single frequency stand-alone GPS(Global Positioning System) receiver is described. In static condition, the position error dynamic model is identified as a first/second order transfer function, and the velocity error model is identified as a band-limited Gaussian white noise via non-parametric method of a PSD(Power Spectrum Density) estimation in continuous time domain. A Kalman filter is proposed considering both correlated/white measurements noise based on identified GPS error model. The performance of the proposed Kalman filtering method is verified via numerical simulation.