• Journal of Communications and Networks
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• 제9권3호
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• pp.219-228
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• 2007

In this paper, we present a novel blind adaptive multiuser detector structure and three robust recursive filters to improve the performance in CDMA environments: Sigma point kalman filter (SPKF), particle filter (PF), and Gaussian mixture sigma point particle filter (GMSPPF). Our proposed robust recursive filters have superior performance over a conventional extended Kalman filter (EKF). The proposed multiuser detector algorithms initially use Kalman prediction form to estimated channel parameters, and unknown data symbol be predicted. Second, based on this predicted data symbol, the robust recursive filters (e.g., GMSPPF) is a refined estimation of joint multipaths and time delays. With these estimated multipaths and time delays, data symbol detection is carried out (Kalman correction form). Computer simulations show that the proposed algorithms outperform the conventional blind multiuser detector with the EKF. Also we can see it provides a more viable means for tracking time-varying amplitudes and time delays in CDMA communication systems, compared to that of the EKF for near-far ratio of 20 dB. For this reason, it is believed that the proposed channel estimators can replace well-known filter such as the EKF.

• Journal of Information Processing Systems
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• 제13권4호
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• pp.1000-1013
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• 2017

Clustering is a NP-hard problem that is used to find the relationship between patterns in a given set of patterns. It is an unsupervised technique that is applied to obtain the optimal cluster centers, especially in partitioned based clustering algorithms. On the other hand, cat swarm optimization (CSO) is a new meta-heuristic algorithm that has been applied to solve various optimization problems and it provides better results in comparison to other similar types of algorithms. However, this algorithm suffers from diversity and local optima problems. To overcome these problems, we are proposing an improved version of the CSO algorithm by using opposition-based learning and the Cauchy mutation operator. We applied the opposition-based learning method to enhance the diversity of the CSO algorithm and we used the Cauchy mutation operator to prevent the CSO algorithm from trapping in local optima. The performance of our proposed algorithm was tested with several artificial and real datasets and compared with existing methods like K-means, particle swarm optimization, and CSO. The experimental results show the applicability of our proposed method.

• Proceedings of the KIEE Conference
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• 대한전기학회 2009년도 제40회 하계학술대회
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• pp.1644_1645
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• 2009

본 논문은 비정상 시계열 예측을 위한 다중모델 퍼지 시스템과, 제안된 시스템의 최적화를 위한 유전 알고리즘의 응용을 다룬다. 일반적으로, 퍼지 예측시스템의 성능은 비선형 데이터가 가지고 있는 다양한 패턴이나 법칙성, 경향 등을 잘 분석하고 시스템에 반영함으로써 개선될 수 있다. 따라서, 본 논문은 원형 시계열의 특성을 보다 잘 반영할 수 있는 그들의 차분데이터를 시스템에 적용하며, 생성 가능한 차분 데이터들 중 원형 시계열의 특징에 가까운 일부를 추출하여 다중모델 퍼지 예측 시스템을 구현함으로써 다양한 원형시계열의 패턴이나 법칙성 등이 고려될 수 있도록 하였다. 다중 모델 퍼지 시스템의 각각의 예측기에는 구조가 간단한 k-means 클러스터링 기법을 적용하여 구현의 용이성을 꽤하였으며, 성능평가를 통해 선택된 최종 예측기는 RCGKA(real-coded genetic k-means clustering algorithms)를 통해 더욱 최적화된 규칙기반을 가지게 함으로써 예측성능이 개선될 수 있도록 하였다. 본 논문에 사용된 최적화 기법인 RCGKA에는 또한 성능이 우수한 다양한 유전연산자를 도입하여 더욱 예측기 성능이 강화될 수 있도록 하였으며, 시뮬레이션을 통해 제안된 예측시스템의 효용성을 증명하였다.

• Proceedings of the KIEE Conference
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.133-137
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• 2005

In this paper, we investigate visual and quantitative analysis of different tastes in the liquids using multi-array chemical sensor (MACS) based on the ion-selective electrodes (ISEs), which is so called the electronic tongue (E-Tongue) system. We apply the Fuzzy C-means (FCM) algorithm combined with Principal Component Analysis (PCA), which can be used to reduce multi-dimensional data to two- or three-dimensional data, to classify visually data patterns detected by E-Tongue system. The proposed technique can be determined the cluster centers and membership grade of patterns through the unsupervised way. The membership grade of an unknown pattern, which does not shown previously, can be visually and analytically determined. Throughout the experimental trails, the E-tongue system combined with the proposed algorithms is demonstrated robust performance for visual and quantitative analysis for different tastes in the liquids.

• The Transactions of The Korean Institute of Electrical Engineers
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• 제62권4호
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• pp.554-561
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• 2013

In this paper, we introduce a modeling and a process simulator developed with the aid of pRBFNNs for activated sludge process in the sewage treatment system. Activated sludge process(ASP) of sewage treatment system facilities is a process that handles biological treatment reaction and is a very complex system with non-linear characteristics. In this paper, we carry out modeling by using essential ASP factors such as water effluent quality, the manipulated value of various pumps, and water inflow quality, and so on. Intelligent algorithms used for constructing process simulator are developed by considering multi-output polynomial radial basis function Neural Networks(pRBFNNs) as well as Fuzzy C-Means clustering and Particle Swarm Optimization. Here, the apexes of the antecedent gaussian functions of fuzzy rules are decided by C-means clustering algorithm and the apexes of the consequent part of fuzzy rules are learned by using back-propagation based on gradient decent method. Also, the parameters related to the fuzzy model are optimized by means of particle swarm optimization. The coefficients of the consequent polynomial of fuzzy rules and performance index are considered by the Least Square Estimation and Mean Squared Error. The descriptions of developed process simulator architecture and ensuing operation method are handled.

• Journal of IKEEE
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• 제20권2호
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• pp.136-142
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• 2016

This paper presents a non-local means (NLM) denoising algorithm based on a new weighting function using a mixed norm. The fidelity of the difference between an anchor patch and the reference patch in the NLM denoising depends on noise level and local activity. This paper introduces a new weighting function based on a mixed norm type of which the order is determined by noise level and local activity of an anchor patch, so that the performance of the NLM denoising can be enhanced. Experimental results demonstrate the objective and subjective capability of the proposed algorithm. In addition, it was verified that the proposed algorithm can be used to improve the performance of the other $l_2$ norm based non-local means denoising algorithms

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권2호
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• pp.253-270
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• 2013

To achieve accurate localization information, complex algorithms that have high computational complexity are usually implemented. In addition, many of these algorithms have been developed to overcome several limitations, e.g., obstruction interference in multi-path and non-line-of-sight (NLOS) environments. However, localization systems those have complex design experience latency when operating multiple mobile nodes occupying various channels and try to compensate for inaccurate distance values. To operate multiple mobile nodes concurrently, we propose a localization system with both low complexity and high accuracy and that is based on a chirp spread spectrum (CSS) radio. The proposed localization system is composed of accurate ranging values that are analyzed by simple linear regression that utilizes a Big-$O(n^2)$ of only a few data points and an algorithm with a self-calibration feature. The performance of the proposed localization system is verified by means of actual experiments. The results show a mean error of about 1 m and multiple mobile node operation in a $100{\times}35m^2$ environment under NLOS condition.

• Journal of Korean Association for Spatial Structures
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• 제14권3호
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• pp.75-84
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• 2014

When adjacent tall buildings experience earthquake excitation, structural pounding may happen. In order to mitigate seismic pounding damage to adjacent structures, many studies have been done to date. Tuned mass dampers (TMD) are widely used for reduction of dynamic responses of building structures subjected to earthquake excitations. If a TMD is shared between adjacent buildings and it shows good control performance, it will be effective and economic means to reduce seismic responses of adjacent structures. In this study, control performance of a shared tuned mass damper (STMD) for seismic response reduction of adjacent buildings has been evaluated. For this purpose, two 8-story example buildings were used and multi-objective genetic algorithms has been employed for optimal design of the stiffness and damping parameters of the STMD. Based on numerical analyses, it has been shown that a STMD can effectively control dynamic responses and reduce the effect of pounding between adjacent buildings subjected to earthquake excitations in comparison with a traditional TMD.

• The Journal of Asian Finance, Economics and Business
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• 제2권2호
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• pp.13-18
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• 2015

In this paper the DRC model is presented for solving multi objective problem. The proposed model is a combination of data envelopment analysis, Cuckoo algorithm and the response surface method. Due to reasons like costs, time and irreversible damages, it is not possible to analyze each and every one of the proposed models in practice, so the simulation is used. Since the number of experiments for simulation process is high then the optimization has gone to practice and directs the simulation process. The response surface method is used as one of the approaches of simulation optimization. Furthermore, data envelopment analysis is used to consider several response surfaces as efficiency response surface. Then this efficiency response surface is solved by Cuckoo algorithms. The main advantage of DRC model is to make one efficiency response surface function instate of multi surface function for every output and also using the advantages of Cuckoo algorithms. In order to demonstrate the effectiveness of the proposed approach, the branches of Refah bank in Mashhad is analyzed and the results are presented.

• Journal of the Institute of Convergence Signal Processing
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• 제7권4호
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• pp.178-183
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• 2006

As a lot of researches on the speech signal processing are performed due to the recent rapid development of the information-communication technology. the pitch period is used as an important element to various speech signal application fields such as the speech recognition. speaker identification. speech analysis. or speech synthesis. A variety of algorithms for the time and the frequency domains related with such pitch period detection have been suggested. One of the pitch detection algorithms for the time domain. AMDF (average magnitude difference function) uses distance between two valley points as the calculated pitch period. However, it has a problem that the algorithm becomes complex in selecting the valley points for the pitch period detection. Therefore, in this paper we proposed the modified AMDF(M-AMDF) algorithm which recognizes the entire minimum valley points as the pitch period of the speech signal by using the rotation transform of AMDF. In addition, a threshold is set to the beginning portion of speech so that it can be used as the selection criteria for the pitch period. Moreover the proposed algorithm is compared with the conventional ones by means of the simulation, and presents better properties than others.