• Journal of international Conference on Electrical Machines and Systems
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• v.3 no.3
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• pp.272-275
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• 2014

An improved fuzzy Kalman filtering speed estimation scheme was proposed by means of measuring stator side voltage and current value based on vector control state equation of induction motor. The designed fuzzy adaptive controller conducted recursive online correction of measurement noise covariance matrix by monitoring the ratio of theory residuals and actual residuals to make it approach real noise level gradually, allowing the filter to perform optimal estimation to improve estimation accuracy of EKF. Meanwhile, co-simulation scheme based on MATLAB and Ansoft was proposed in order to improve simulation accuracy. Field-circuit coupling problems of induction motor under the action of vector control were solved and the parameter optimization accuracy was improved dramatically. The simulation and experimental results show that this algorithm has a strong ability to inhibit the random measurement noise. It is able to estimate motor speed accurately, and has superior static and dynamic characteristics.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1245-1255
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• 2017

The online learning is a process of obtaining the solution for a given objective function where the data is accumulated in real time or in batch units. The stochastic gradient descent method is one of the most widely used for the online learning. This method is not only easy to implement, but also has good properties of the solution under the assumption that the generating model of data is homogeneous. However, the stochastic gradient method could severely mislead the online-learning when the homogeneity is actually violated. We assume that there are two heterogeneous generating models in the observation, and propose the a new stochastic gradient method that mitigate the problem of the heterogeneous models. We introduce a robust mini-batch optimization method using statistical tests and investigate the convergence radius of the solution in the proposed method. Moreover, the theoretical results are confirmed by the numerical simulations.

• The Journal of the Acoustical Society of Korea
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• v.24 no.1
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• pp.52-57
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• 2005

The adaptive multirate wideband (AMR-WB) speech coder has an extended audio bandwidth from 50 Hz to 7 kBz and operates on nine speech coding bit-rates from 6.6 to 23.85 kbit/s. In this Paper, we present the real-time implementation of AMR-WB speech coder using 16bit fixed-point TMS320C5509 that has dual MAC units. Firstly, We implemented AMR-WB speech coder in C 1anguage level using intrinsics, and then performed optimization in assembly language. The computational complexity of the implemented AMR-WB coder at 23.85 kbit/s is 42.9 Mclocks. And this coder needs the program memory of 15.1 kwords, data ROM of 9.2 kwords and data RAM of 13.9 kwords.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.5
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• pp.360-370
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• 2009

Using solar power in wireless sensor networks requires a different approach to energy optimization from networks with battery-based nodes. Solar energy is an inexhaustible supply which can potentially allow a system to run forever, but there are several issues to be considered such as the uncertainty of energy supply and the constraint of rechargeable battery capacity. In this paper, we present SolarSS: a reliable storage system for solar-powered sensor networks, which provides a set of functions, in separate layers, such as sensory data collection, replication to prevent failure-induced data loss, and storage balancing to prevent depletion-induced data loss. SolarSS adapts the level of layers activated dynamically depending on solar energy availability, and provides an efficient resource allocation and data distribution scheme to minimize data loss.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.1
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• pp.12-18
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• 2012

Stereo correspondence is the central problem of stereo vision. In this paper, we propose a stereo matching scheme based on a genetic algorithm using a multi-resolution method and AD-Census. The proposed approach considers the matching environment as an optimization problem and finds the disparity by using a genetic algorithm And adaptive chronosome structure using edge pixels and crossover mechanism are employed in this technique. A cost function is composes of certain constraints whice are commonly used in stereo matching. AD-Census measure is applied to reduce disparity error. To increase the efficiency of process, we apply image pyramid method to stereo matching and calculate the initial disparity map at the coarsest resolution. Then initial disparity map is propagated to the next finer resolution, interpolated and performed disparity refinement using local feature vector. We valid our method not only reduces the search time for correspondence compared with conventional GA-based method but also ensures the validity of matching.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.504-521
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• 2016

Recently, energy harvesting technology has been integrated into wireless sensor networks to ameliorate the nodes' energy limitation problem. In theory, the wireless sensor node equipped with an energy harvesting module can work permanently until hardware failures happen. However, due to the change of power supply, the traditional hierarchical network routing protocol can not be effectively adopted in energy harvesting wireless sensor networks. In this paper, we improve the Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol to make it suitable for the energy harvesting wireless sensor networks. Specifically, the cluster heads are selected according to the estimation of nodes' harvested energy and consumed energy. Preference is given to the nodes with high harvested energy while taking the energy consumption rate into account. The utilization of harvested energy is mathematically formulated as a max-min optimization problem which maximizes the minimum energy conservation of each node. We have proved that maximizing the minimum energy conservation is an NP-hard problem theoretically. Thus, a polynomial time algorithm has been proposed to derive the near-optimal performance. Extensive simulation results show that our proposed routing scheme outperforms previous works in terms of energy conservation and balanced distribution.

• The Journal of the Korea Contents Association
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• v.15 no.2
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• pp.1-10
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• 2015

In this paper, we propose an integral image compression method to improve the coding efficiency. As the characteristics of integral images are various according to the distance between a camera and objects, complexity of the objects and background, etc, the coding efficiency can be improved by applying a coding method adaptive to the characteristics. In addition, as the integral images are compressed by the unit of elemental images, the coding efficiency can be improved. by employing a coding method optimized to the coding direction of elemental images. Therefore, the proposed method remaps an integral image with six kinds of mapping rules, and then the conventional 3D-DCT based compression method is applied to the remapped images. Finally, we perform the rate-distortion optimization to choose the best of the mapping rules. Experimental results show that the proposed method yields high gains in image quality and bit-rate.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.9
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• pp.81-92
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• 1998

A new hybrid technique using several sub-populations having completely different evolutionary behaviors is proposed to increase the possibility to quickly find the global optimum of continuous optimization problem. It has three sub-populations. Two NPOSA algorithms showing good performance in the problem having a rugged fitness function are applied to two sub-populations and a self-adaptive evolutionary algorithm to the other sub-population. Sub-populations evolve in different manners and the interaction among these sub-populations lead to the global optimum quickly. The efficiency of this technique is verified through benchmark test functions. Finally, the algorithm with three sub-populations has been applied to seek for the optimal camera calibration parameters. After an error function has been defined using measured feature points of a calibration block, it has been shown that the algorithm searches for the camera parameters that minimize the error function.

• The KIPS Transactions:PartA
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• v.13A no.6 s.103
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• pp.501-510
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• 2006

The self-organizing super peer ring P2P search scheme improves search performance of the existing unstructured peer-to-peer systems, in which super peers with high capacity constitute a ring structure and all peer in the system utilize the ring for publishing or querying their keys. In this paper, we further improves the performance of the self-organizing ring by adaptively changing its super peer ratio according to the status of the entire system. By using PSO, the optimized super peer ratio can be maintained within the system. Through simulations, we show that our self-organizing super peer ring optimized by PSO outperforms not only the fixed super peer ring but also the self-organizing super ring with fixed ratio in the aspect of query success rate.

• Journal of the Korea Society of Computer and Information
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• v.15 no.6
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• pp.49-56
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• 2010

In this paper, a joint PHY-MAC layer optimized resource allocation scheme for OFDMA based micro base stations is investigated. We propose cross-layer optimized two-stage resource allocation scheme including cross-layer functional description and control information flow between PHY-MAC layers. The proposed two-stage resource allocation scheme consists of a user grouping stage and a resource allocation stage. In the user grouping stage, users are divided into a macro base station user group and a micro base station user group based on the PHY-MAC layer characteristics of each user. In the resource allocation stage, a scheduling scheme and an allotment of resources are determined. In the proposed scheme, diversity and adaptive modulation and coding (AMC) schemes are exploited as schedulers. Simulation results demonstrate that the proposed scheme increases the average cell throughput about 40~80 % compared to the conventional system without micro base stations.