• Journal of Communications and Networks
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• v.8 no.3
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• pp.290-296
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• 2006

In this paper, a generalized blind adaptive algorithm is introduced for multi-user detection of direct sequence code division multiple access (OS-COMA) wireless communication systems. The main property of the proposed algorithm is its ability to resolve the multipath fading channel resulting in inter symbol interference (ISI) as well as multiple access interference (MAI). Other remarkable properties are its low complexity and mitigation to the near-far problem as well as its insensitivity to asynchronous transmission. The proposed system is based on the minimization of the output energy and convergence to the minimum mean square error (MMSE) detector. It is blind in the sense that it needs no knowledge of the other users' signatures, only the intended user signature and timing are required. Furthermore, the convergence of the minimum output energy (MOE) detector to the MMSE detector is analytically proven in case of M-ary PSK. Depicted results show that the performance of the generalized system dominates those previously considered. Further improvements are obtained when multiple input multiple output (MIMO) technique is employed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1C
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• pp.33-39
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• 2010

Correntropy is a generalized correlation function that contains higher order moments of the probability density function (PDF) than the conventional moment expansions. The criterion maximizing cross-correntropy (MCC) of two different random variables has yielded superior performance particularly in nonlinear, non-Gaussian signal processing comparing to mean squared error criterion. In this paper we propose a new blind equalization algorithm based on cross-correntropy criterion which uses, as two variables, equalizer output PDF and Parzen PDF estimate of a set of randomly generated symbols that complies with the transmitted symbol PDF. The performance of the proposed algorithm based on MCC is compared with the Euclidian distance minimization.

• Journal of Communications and Networks
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• v.9 no.2
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• pp.112-117
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• 2007

In this paper, we focus on the total transmission power minimization problem for downlink beamforming multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems while ensuring each user's QoS requirement. Although the linear integer programming (LIP) solution we formulate provides the performance upper bound of the margin adaptive (MA) optimization problem, it is hard to be implemented in practice due to its high computational complexity. By regarding each user's equivalent channel gain as approximate independent values and using iterative descent method, we present a heuristic MA resource allocation algorithm. Simulation results show that the proposed algorithm efficiently converges to the local optimum, which is very close to the performance of the optimal LIP solution. Compared with existing space division multiple access (SDMA) OFDM systems with or without adaptive resource allocation, the proposed algorithm achieves significant performance improvement by exploiting the frequency diversity and multi-user diversity in downlink multiple-input single-output (MISO) OFDM systems.

• The Transactions of the Korean Institute of Power Electronics
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• v.11 no.6
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• pp.551-557
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• 2006

The electrical frequency synchronized periodic torque ripple exits in the AC motor. There are various sources of torque ripple in AC motor such as current measurement error, dead time, etc. This paper proposes a compensation algorithm which suppresses undesired side effect known as the periodic torque ripple of AC motor. The torque ripple compensation classified as the speed ripple detector and torque ripple compensator. This paper proves a speed ripple minimization at steady state by analysis of torque ripple compensator. A new speed ripple detector improves the performance of torque ripple compensation algorithm. The simulation and experimental results show that the compensation algorithm is effective and the torque ripple compensation method improves the performance of speed ripple detector by eliminating torque ripples effectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.7
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• pp.1312-1320
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• 2009

This paper presents an efficient design method of 2-D infinite impulse response(IIR) digital filter based on a particle swarm optimization(PSO) algorithm. The design task is reformulated as a constrained minimization problem and is solved by our newly developed PSO algorithm. To ensure the stability of the designed 2-D IIR digital filters, a new stability strategy is embedded in the basic PSO algorithm. The superiority of the proposed method is demonstrated by several experiments. The results show that the approximation error of the resultant filters are better than those of the digital filters which designed by recently published filter design methods. The proposed design method can also obtain the stable2-D IIR digital filters.

• The KIPS Transactions:PartB
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• v.15B no.1
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• pp.53-60
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• 2008

This paper proposes a new multiobjective optimization method for discriminative training of hidden Markov models (HMMs) used as the recognizer for automatic lipreading. While the conventional Baum-Welch algorithm for training HMMs aims at maximizing the probability of the data of a class from the corresponding HMM, we define a new training criterion composed of two minimization objectives and develop a global optimization method of the criterion based on simulated annealing. The result of a speaker-dependent recognition experiment shows that the proposed method improves performance by the relative error reduction rate of about 8% in comparison to the Baum-Welch algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.4
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• pp.662-674
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• 1997

In order to post process the vector-quantized images employing the theory of projections onto convex sets or the constrained minimization technique, the the projector onto QCS(quantization constraint set) as well as the filter that smoothes the lock boundaries should be investigated theoretically. The basic idea behind the projection onto QCS is to prevent the processed data from diverging from the original quantization region in order to reduce the blurring artifacts caused by a filtering operation. However, since the Voronoi regions in order to reduce the blurring artifacts caused by a filtering operation. However, since the Voronoi regions in the vector quantization are arbitrarilly shaped unless the vector quantization has a structural code book, the implementation of the projection onto QCS is very complicate. This paper mathematically analyzes the projection onto QCS from the viewpoit of minimizing the mean square error. Through the analysis, it has been revealed that the projection onto a subset of the QCS yields lower distortion than the projection onto QCS does. Searching for an optimal constraint set is not easy and the operation of the projector is complicate, since the shape of optimal constraint set is dependent on the statistical characteristics between the filtered and original images. Therefore, we proposed a hyper-cube as a constraint set that enables a simple projection. It sill be also shown that a proper filtering technique followed by the projection onto the hyper-cube can reduce the quantization distortion by theory and experiment.

• Advances in materials Research
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• v.9 no.2
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• pp.115-131
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• 2020

Limit elastic speed analysis of Al/SiC-based functionally graded annular disk of uniform thickness has been carried out for two cases, namely: metal-rich and ceramic rich. In the present study, the unknown field variable for radial displacement is solved using variational method wherein the solution was obtained by Galerkin's error minimization principle. One of the objectives was to identify the variation of induced stress in a functionally graded disk of uniform thickness at limit elastic speed using modified rule of mixture by comparing the induced von-Mises stress with the yield stress along the disk radius, thereby locating the yield initiation. Furthermore, limit elastic speed has been reported for a combination of varying grading index (n) and aspect ratios (a/b).Results indicate, limit elastic speed increases with an increase in grading indices. In case of an increase in aspect ratio, limit elastic speed increases up to a critical value beyond which it recedes. Also, the objective was to look at the variation of yield stress corresponding to volume fraction variation within the disk which later helps in material tailoring. The study reveals the qualitative variation of yield stress for FG disk with volume fraction, resulting in the possibility of material tailoring from the processing standpoint, in practice.

• Structural Engineering and Mechanics
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• v.70 no.3
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• pp.289-301
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• 2019

Hysteretic energy is defined as energy dissipated through inelastic deformations during a ground motion by the system. It includes frequency content and duration of ground motion as two remarkable parameters, while these characteristics are not seen in displacement spectrum. Since maximum displacement individually cannot be the appropriate criterion for damage assessment, hysteretic energy has been evaluated in this research as a more comprehensive seismic demand parameter. An innovative methodology has been proposed to establish a new equivalent linear model to estimate hysteretic energy spectrum for bilinear SDOF models under two different sets of earthquake excitations. Error minimization has been defined in the space of equivalent linearization concept, which resulted in equivalent damping and equivalent period as representative parameters of the linear model. Nonlinear regression analysis was carried out for predicting these equivalent parameter as a function of ductility. The results also indicate differences between seismic demand characteristics of far-field and near-field ground motions, which are not identified by most of previous equations presented for predicting seismic energy. The main advantage of the proposed model is its independency on parameters related to earthquake and response characteristics, which has led to more efficiency as well as simplicity. The capability of providing a practical energy based seismic performance evaluation is another outstanding feature of the proposed model.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.33-38
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• 2021

This paper presents a comparative study between the parameter-optimized Pacejka model and artificial neural network model for the tire force estimation. The two different approaches are investigated and compared in this study. First, offline optimization is conducted based on Pacejka Magic Formula model to determine the proper parameter set for the minimization of tire force error between the model and test data set. Second, deep neural network model is used to fit the model to the tire test data set. The actual tire forces are measured using MTS Flat-Track test platform and the measurements are used as the reference tire data set. The focus of this study is on the applicability of machine learning technique to tire force estimation. It is shown via the regression results that the deep neural network model is more effective in describing the tire force than the parameter-optimized Pacejka model.