• Journal of Information Processing Systems
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• v.10 no.2
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• pp.163-175
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• 2014

This paper will focus on improving the performance of orthogonal frequency division multiplexing (OFDM) in Rayleigh fading environments. The proposed technique will use a previously published method that has been shown to improve OFDM performance in independent fading, based on ordered sub-carrier selection. Then, a simple non-iterative method for finding the optimal bit-loading allocation was proposed. It was also based on ordered sub-carrier selection. We compared both of these algorithms to an optimal bit-loading solution to determine their effectiveness in a correlated fading environment. The correlated fading was simulated using the JTC channel models. Our intent was not to create an optimal solution, but to create a low complexity solution that can be used in a wireless environment in which the channel conditions change rapidly and that require a simple algorithm for fast bit loading.

• The Transactions of the Korean Institute of Power Electronics
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• v.23 no.6
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• pp.415-423
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• 2018

This study uses a level selection algorithm with fixed sampling frequency for modular multilevel converter (MMC) systems. Theoretically, the proposed method increases the level infinitely while the sampling time remains the same. The proposed method called cluster stream buffer (CSB) consists of several clusters, wherein each cluster is composed of 32 submodules that depend on the level of the submodules in the MMC system. To increase the level of the MMC system, additional clusters are used, and the sampling time between clusters is determined from the sampling time between levels needed for utilizing the entire level from the MMC system. This method is crucial in the control of MMC-type HVDC systems because it improves scalability and precision.

• Journal of Advanced Marine Engineering and Technology
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• v.26 no.4
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• pp.415-424
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• 2002

In this paper, a robust fuzzy precompensated PID controller using immune algorithm for load frequency control of 2-area power system is proposed. Here, a fuzzy precompensated PID controller is designed as a fuzzy logic based precompensation approach for PID controller. This scheme is easily implemented by adding a fuzzy precompensator to an existing PID controller. We optimize the fuzzy precompensator with an immune algorithm for complementing the demerit such as the difficulty of the component selection of fuzzy controller, namely, scaling factor, membership function and fuzzy rules. Simulation results show that the proposed robust load frequency controller can achieve good performance even in the presence of generation rate constraints.

• Journal of Ocean Engineering and Technology
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• v.27 no.5
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• pp.36-42
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• 2013

We present the optimum design for the cross-sectional(sizing) and shape optimization of truss structures with natural frequency constraints. The optimum design method used in this paper employs continuous design variables and the Harmony Search Algorithm(HSA). HSA is a meta-heuristic search method for global optimization problems. In this paper, HSA uses the method of random number selection in an update process, along with penalty parameters, to construct the initial harmony memory in order to improve the fitness in the initial and update processes. In examples, 10-bar and 72-bar trusses are optimized for sizing, and 37-bar bridge type truss and 52-bar(like dome) for sizing and shape. Four typical truss optimization examples are employed to demonstrate the availability of HSA for finding the minimum weight optimum truss with multiple natural frequency constraints.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2209-2212
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• 2003

In this paper, we propose the method to extract the important frequency bands from the EMG signal, and for generation of feature vector using the important frequency bands. The EMG signal is measured with 4 sensor and is recorded as 4 channel’s time series data. The same frequency bands from 4 channel’s frequency components are selected as the important frequency bands. The feature vector is calculated by the function formed using the combination of selected same important frequency bands. The EMG signals acquired from seven wrist motion type are recognized by changing into the feature vector formed. Then, the extraction and generation is performed by using the double combination of the genetic algorithm (GA) and the neural network (NN). Finally, in order to illustrate the effectiveness of the proposed method, computer simulations are done.

• The Journal of the Acoustical Society of Korea
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• v.14 no.1E
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• pp.46-55
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• 1995

In this paper, we present a new wavelet transform-based CELP coder, called band selection wavelet transform CELP (BS-WTCELP) operated at 4.8 kbps. The proposed algorithm uses a band selection scheme of frequency bands of wavelet transform and selective vector quantization (VQ). The band selection and selective VQ structure is implemented by using a classified VQ structure. The proposed algorithm has about 0.5-1.0 dB improvement in segmental SNR compared with the conventional CELP that uses the random codebook search, while is has significantly reduced computational and storage complexity. Many experimental results have shown that the proposed algorithm is more suitable for most real-applications than the conventional CELP and wavelet transform CELP.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.854-857
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• 2015

As the number of devices integrated on system-on-chip(SoC) increases exponentially, energy reduction technology is essential. Dynamic Voltage and Frequency Scaling (DVFS) is a very effective technique for reducing power consumption. Since it requires complex voltage regulators and PLL circuits, DVFS tends to have significant overheads. In this paper, we propose a new voltage selection algorithm to minimize transition overhead for multiprocessor SoC (MPSoC). Simulation results show that proposed algorithm appears less energy consumption with transition overhead even though maintains performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.239-245
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• 2012

This paper proposes a novel optimum design method for the PID controller of magnetic levitation-based Rail-Guided Vehicle(RGV) by a genetic algorithm using clone selection method and a new performance index function with performances of both time and frequency domain. Generally, since an attraction type levitation system is intrinsically unstable and requires a delicate controller that is designed considering overshoot and settling time, it is difficult to completely satisfy the desired performance through the methods designed by conventional performance indexes. In the paper, the conventional performance indexes are analyzed and then a new performance index for Maglev-based RGV is proposed. Also, an advanced genetic algorithm which is designed using clonal selection algorithm for performance improvement is proposed. To verify the proposed algorithm and the performance index, we compare the proposed method with a simple genetic algorithm and particle swarm optimization. The simulation results show that the proposed method is more effective than conventional optimization methods.

• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.489-498
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• 2006

Clustering results differ according to the datasets and the performance worsens even while using web documents which are manually processed by an indexer, because although representative clusters for a feature can be obtained by statistical feature selection methods, irrelevant features(i.e., non-obvious features and those appearing in general documents) are not eliminated. Those irrelevant features should be eliminated for improving clustering performance. Therefore, this paper proposes three feature-filtering algorithms which consider feature values per document set, together with distribution, frequency, and weights of features per document set: (l) features filtering algorithm in a document (FFID), (2) features filtering algorithm in a document matrix (FFIM), and (3) a hybrid method combining both FFID and FFIM (HFF). We have tested the clustering performance by feature selection using term frequency and expand co link information, and by feature filtering using the above methods FFID, FFIM, HFF methods. According to the results of our experiments, HFF had the best performance, whereas FFIM performed better than FFID.

• Structural Engineering and Mechanics
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• v.58 no.1
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• pp.163-179
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• 2016

The Cuckoo search (CS) algorithm is a simple and efficient global optimization algorithm and it has been applied to figure out large range of real-world optimization problem. In this paper, a new formula is introduced to the discovering probability process to improve the convergence rate and the Tournament Selection Strategy is adopted to enhance global search ability of the certain algorithm. Then an approach for structural damage identification based on modified Cuckoo search (MCS) is presented. Meanwhile, we take frequency residual error and the modal assurance criterion (MAC) as indexes of damage detection in view of the crack damage, and the MCS algorithm is utilized to identifying the structural damage. A simply supported beam and a 31-bar truss are studied as numerical example to illustrate the correctness and efficiency of the propose method. Besides, a laboratory work is also conducted to further verification. Studies show that, the proposed method can judge the damage location and degree of structures more accurately than its counterpart even under measurement noise, which demonstrates the MCS algorithm has a higher damage diagnosis precision.