• 제어로봇시스템학회:학술대회논문집
• /
• 1994.10a
• /
• pp.364-368
• /
• 1994

Algebraic matrix Riccati equations of the form, FP+PF$^{T}$ -PRP+Q=0. are analyzed with reference to the stability of closed-loop system F-PR. Here F, R and Q are n * n real matrices with R=R$^{T}$ and Q=Q$^{T}$ .geq.0 (nonnegative-definite). Such equations have been playing key roles in optimal control and filtering problems with R .geq. 0. and also in the solutions of in H$_{\infty}$ control problems with R taking the form R=H$_{1}$$^{T}$ H$_{1}$-H$_{2}$$^{T}$ H$_{2}$. In both cases an existence of stabilizing solution, i.e. the solution yielding asymptotically stable closed-loop system, is an important problem. First, we briefly review the typical results when R is of definite form, namely either R .geq. 0 as in LQG problems or R .leq. 0. They constitute two extrence cases of Riccati to the cases H$_{2}$=0 and H$_{1}$=0. Necessary and sufficient conditions are shown for the existence of nonnegative-definite or positive-definite stabilizing solution. Secondly, we focus our attention on more general case where R is only assumed to be symmetric, which obviously includes the case for H$_{\infty}$ control problems. Here, necessary conditions are established for the existence of nonnegative-definite or positive-definite stabilizing solutions. The results are established by employing consistently the so-called algebraic method based on an eigenvalue problem of a Hamiltonian matrix.x.ix.x.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.18 no.2
• /
• pp.272-277
• /
• 2008

Symmerge is a stable minimum storage merging algorithm that needs $O(m{\log}{\frac{n}{m}})$ element comparisons, where in and n are the sizes of the input sequences with $m{\leq}n$. Hence, according to the lower bound for merging, the algorithm is asymptotically optimal regarding the number of comparisons. The Symmerge algorithm is based on the standard recursive technique of "divide and conquer". The objective of this paper is to consider the relationship between m and n for the degenerated case where the recursion depth reaches m-1.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.45 no.6
• /
• pp.64-69
• /
• 2008

This paper discusses low resolution face recognition using the photon-counting linear discriminant analysis (LDA). The photon-counting LDA asymptotically realizes the Fisher criterion without dimensionality reduction since it does not suffer from the singularity problem of the fisher LDA. The linear discriminant function for optimal projection is determined in high dimensional space to classify unknown objects, thus, it is more efficient in dealing with low resolution facial images as well as conventional face distortions. The simulation results show that the proposed method is superior to Eigen face and Fisher face in terms of the accuracy and false alarm rates.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37A no.12
• /
• pp.1133-1139
• /
• 2012

In this paper, hybrid mode beamforming (HMB) which allows simultaneous transmission of joint beamforming and disjoint beamforming is proposed. HMB is proven to be asymptotically optimal beamforming for sum rate growth. Extensive simulations show that HMB achieves nearly the same performance as joint encoding (JE) in symmetric interference channel. It is also shown that it outperforms JE in a more realistic asymmetric interference channel environment, though it still experiences some performance degradation due to power inefficiency of joint beamforming in asymmetric channel.

• Quantitative Bio-Science
• /
• v.37 no.2
• /
• pp.133-141
• /
• 2018

Graphical lasso is one of the most popular methods to estimate a sparse precision matrix, which is an inverse of a covariance matrix. The objective function of graphical lasso imposes an ${\ell}_1$-penalty on the (vectorized) precision matrix, where a tuning parameter controls the strength of the penalization. The selection of the tuning parameter is practically and theoretically important since the performance of the estimation depends on an appropriate choice of tuning parameter. While information criteria (e.g. AIC, BIC, or extended BIC) have been widely used, they require an asymptotically unbiased estimator to select optimal tuning parameter. Thus, the biasedness of the ${\ell}_1$-regularized estimate in the graphical lasso may lead to a suboptimal tuning. In this paper, we propose a two-staged bias-correction procedure for the graphical lasso, where the first stage runs the usual graphical lasso and the second stage reruns the procedure with an additional constraint that zero estimates at the first stage remain zero. Our simulation and real data example show that the proposed bias correction improved on both edge recovery and estimation error compared to the single-staged graphical lasso.

• Wind and Structures
• /
• v.38 no.3
• /
• pp.161-170
• /
• 2024

In recent years, there have been an increasing number of experimental studies showing the need to include robustness criteria in the design process to develop complex active control designs for practical implementation. The paper investigates the crosswind aerodynamic parameters after the blocking phase of a two-dimensional square cross-section structure by measuring the response in wind tunnel tests under light wind flow conditions. To improve the accuracy of the results, the interpolation of the experimental curves in the time domain and the analytical responses were numerically optimized to finalize the results. Due to this combined effect, the three aerodynamic parameters decrease with increasing wind speed and asymptotically affect the upper branch constants. This means that the aerodynamic parameters along the density distribution are minimal. Taylor series are utilized to describe the fuzzy nonlinear plant and derive the stability analysis using polynomial function for analyzing the aerodynamic parameters and numerical simulations. Due to it will yield intricate terms to ensure stability criterion, therefore we aim to avoid kinds issues by proposing a polynomial homogeneous framework and utilizing Euler's functions for homogeneous systems. Finally, we solve the problem of stabilization under the consideration by SOS (sum of squares) and assign its fuzzy controller based on the feasibility of demonstration of a nonlinear system as an example.

• The Journal of the Acoustical Society of Korea
• /
• v.11 no.1
• /
• pp.22-34
• /
• 1992

There exists a transform trellis code that is optimal for stationary Gaussian sources and the squared-error distortion measure at all rates. In this paper, we train an asymptotically optimal version of such a code to obtain one which is matched better to the statistics of real world data. The training algorithm uses the M algorithm to search the trellis codebook and the LBG algorithm to update the trellis codebook. We investigate the trained transform trellis coding scheme for the first-order AR(autoregressive) Gaussian source whose correlation coefficient is 0.9 and actual speech sentences. For the first-order AR source, the achieved SNR for the test sequence is from 0.6 to 1.4 dB less than the maximum achievable SNR as given by Shannon's rate-distortion function for this source, depending on the rate and surpasses all previous known results for this source. For actual speech data, to achieve improved performance, we use window functions and gain adaptation at rate 1.0 bits/sample.

• Journal of Korea Spatial Information System Society
• /
• v.7 no.2 s.14
• /
• pp.57-66
• /
• 2005

The Interconnecting Highways problem is an abstract of many practical Layout Design problems in the areas of VLSI design, the optical and wired network design, and the planning for the road constructions. For the road constructions, the shortest-length road layouts that interconnect existing positions will provide many more economic benefits than others. That is, finding new road layouts to interconnect existing roads and cities over a wide area is an important issue. This paper addresses an approximation scheme that finds near optimal road layouts for the Interconnecting Highways problem which is NP-hard. As long as computational resources are provided, the near optimality can be acquired asymptotically. This implies that the result of the scheme can be regarded as the optimal solution for the problem in practice. While other approximation schemes can be made for the problem, this proposed scheme provides a big merit that the algorithm designed by this scheme fits well to given problem instances.

• Journal of the Korea Society of Computer and Information
• /
• v.17 no.12
• /
• pp.149-158
• /
• 2012

Proposed is a hybrid randomizing function using two asymptotically optimal randomizing functions: Elias function and Peres function. Randomizing function is an mathematical abstraction of producing a uniform random bits from a source of randomness with bias. It is known that the output rate of Elias function and Peres function approaches to the information-theoretic upper bound. Especially, for each fixed input length, Elias function is optimal. However, its computation is relatively complicated and depends on input lengths. On the contrary, Peres function is defined by a simple recursion. So its computation is much simpler, uniform over the input lengths, and runs on a small footprint. In view of this tradeoff between computational complexity and output efficiency, we propose a hybrid randomizing function that has strengths of the two randomizing functions and analyze it.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.49 no.9
• /
• pp.67-75
• /
• 2012

Optimal quantizers in conducting the entropy-constrained quantization for high bit rates have the lattice structure. The quantization process is simple due to the regular structure, and various quantization algorithms are proposed depending on the lattice. Such a lattice vector quantizer (VQ) can be implemented by using the sample-adaptive product quantizer (SAPQ) and its output can also be easily entropy encoded. In this paper, the entropy encoding scheme for the lattice VQ is proposed based on SAPQ, and the performance of the proposed lattice VQ, which is based on SAPQ with the entropy coder, is asymptotically compared as the rate increases. It is shown by experiment that the gain for the memoryless Gaussian source also approaches the theoretic gain for the uniform density case.