• Journal of the Korean Institute of Intelligent Systems
• /
• v.16 no.1
• /
• pp.113-118
• /
• 2006

This paper presents a new linear-matrix-inequality-based intelligent digital redesign (LMI-based IDR) technique to match the states of the analog and the digital T-S fuzzy control systems at the intersampling instants as well as the sampling ones. The main features of the proposed technique are: 1) the affine control scheme is employed to increase the degree of freedom; 2) the fuzzy-model-based periodic control is employed, and the control input is changed n times during one sampling period; 3) The proposed IDR technique is based on the approximately discretized version of the T-S fuzzy system, but its discretization error vanishes as n approaches the infinity. 4) some sufficient conditions involved in the state matching and the stability of the closed-loop discrete-time system can be formulated in the LMIs format.

• Proceedings of the Acoustical Society of Korea Conference
• /
• 1991.06a
• /
• pp.3-6
• /
• 1991

본 연구에서는 음성의 패턴작성법을 개선하고 음성인식율을 향상시키기 위하여 퍼지패턴매칭을 개선한 뉴럴퍼지패턴매칭에(a neural-fuzzy pattern matching)의해 특정화자 고립단어인식을 수행하였다. 이 방법에서는 신경회로망의 연상기억에 의한 사상에 의해 패턴을 작성하여 주파수변동을 흡수하고 표준패턴고 선형매칭에 의해 유사도를 측정하여 인식하므로써 시간변동의 문제를 보완하였다. 또한, 이 방법에서 사용하는 특징피라미터는 2진화 스펙트럽이며, 유사도는 논리연산에 의해 측정되기 때문에 종래의 왜곡척도를 이용한 DTW 방법에 비해 기억용량과 계산량이 매우 작다. 이 방법의 인식성능을 평가하기 위하여 남녀가 발성한 28개의 도시명을 대상으로 인식실험을 수행한 결과, 신경회로망을 이용하지 않은 퍼지패턴매칭보다 오인식을 감소시켰으며, 뉴럴-퍼지 패턴매칭에 의한 특정화자 고립단어인식의 우수성을 확인하였다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2001.05a
• /
• pp.117-120
• /
• 2001

This paper presents a new global state-matching intelligent digital redesign method for nonlinear systems by using genetic algorithms (GAs). The proposed method results in global matching of the states of the analogously controlled system with those of the digitally controlled system while the conventional intelligent digital redesign method does not. The proposed method provides a new approach for the digital redesign of a class of fuzzy-model-based controllers.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.38 no.2
• /
• pp.63-71
• /
• 2015

This study is about implementing an job matching web service system based on the Job seeker's company assessment model proposed by the researchers. Basically, the Job seekers' company assessment model is based on the concept that each job seeker can evaluate the recruitment company candidates using job seekers's own major consideration factors. Using the implemented information system, each job seeker's main considerations in job searching process are evaluated and stored and compared to those of other job seekers' or groups' characterized by sex, job experience residential area and etc. by finding out and listing up the companies in the order of the preference of job seeker own or belonging groups, job seekers can be helped to find suitable companies which fit well to themselves.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2000.11a
• /
• pp.176-179
• /
• 2000

This paper addresses a fuzzy controller for nonlinear systems control using a pole placement in a specified disk and fuzzy controller is redesign for Intelligent digital redesign method. for nonlinear system, we obtain continuous time state feedback gain that guarantee stability of globally TS fuzzy system. The feedback gain is satified pole placement in a specified disk region so that the closed loop system is stable, For digital control redesgin of continuous time TS fuzzy model, we does state matching and obtain feedback gain of digital controller. Finally, it is shown that the proposed method is feasible through a computer simulation.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.1244-1248
• /
• 2005

In this paper, we propose fuzzy c-means (FCM) to solve recognition errors in invariant range image, multi-pose face recognition. Scale, center and pose error problems were solved using geometric transformation. Range image face data was digitized into range image data by using the laser range finder that does not depend on the ambient light source. Then, the digitized range image face data is used as a model to generate multi-pose data. Each pose data size was reduced by linear reduction into the database. The reduced range image face data was transformed to the gradient face model for facial feature image extraction and also for matching using the fuzzy membership adjusted by fuzzy c-means. The proposed method was tested using facial range images from 40 people with normal facial expressions. The output of the detection and recognition system has to be accurate to about 93 percent. Simultaneously, the system must be robust enough to overcome typical image-acquisition problems such as noise, vertical rotated face and range resolution.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1997.10a
• /
• pp.247-251
• /
• 1997

FCM(Fuzzy Cognitive Map) is a fuzzy signed directed graph for representing causal reasoning which has fuzziness between causal concepts. Authors have already proposed FCM-based fault diagnostic scheme and verified its usefulness. However, the previously proposed scheme has the problem of lower diagnostic resolution as in the case of other qualitative approaches. In order to improve the diagnostic resolution, a concept of fuzzy number is introduced into the basic FCM-based fault diagnostic algorithm. By incorporation the fuzzy number into fault FCM models, quantitative information such as the transfer gain between the state variables can be effectively utilized for better diagnostic resolution. Furthermore, an enhanced TAM(Temporal Associative Memory) recall procedure and modified and modified pattern matching scheme are also proposed.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.15 no.6
• /
• pp.765-770
• /
• 2005

This paper presents a new intelligent digital redesign (IDR) method via the compensated bilinear transformation to design the digital controller such that the digital fuzzy system is equivalent to the analog fuzzy system in the sense of the state-matching. This paper especially consider a multirate control scheme with a predictive feature, where the digital control input is held constant N times between the sampling points. More precisely, the multirate control scheme is proposed that utilizes a numerical integration scheme to approximately predict the current state from the state measured at the sampling points, the delayed measurements. For this system, the IDR conditions incorporated with stabilizability in the format of the linear matrix inequalities (LMIs) are derived. The superiority of the proposed technique is convincingly visualized through a numerical example.

• Proceedings of the KIPE Conference
• /
• 2003.11a
• /
• pp.69-72
• /
• 2003

The paper presents implementation of a PV fuzzy logic power tracking controller. Using maximum power point tracker with the intermediate converter can increase the system efficiency by matching the PV system to the load. A new fuzzy MPPT is proposed, where fuzzy inputs parameters are dp/dI and the last incremental of duty of duty ratio $L{\delta}D$, and the output is the new incremental value $(new{\delta}D)$ according to the maximum power point under various illumination levels.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2005.04a
• /
• pp.378-381
• /
• 2005

This paper presents a new linear-matrix-inequality-based intelligent digital redesign (LMI-based IDR) technique to match the states of the analog and the digital T-S fuzzy control systems at the intersampling instants as well as the sampling ones. The main features of the proposed technique are: 1) the fuzzy-model-based periodic control is employed, and the control input is changed n times during one sampling period; 2) The proposed IDR technique is based on the approximately discretized version of the T-S fuzzy system, but its discretization error vanishes as n approaches the infinity. 3) some sufficient conditions involved in the state matching and the stability of the closed-loop discrete-time system can be formulated in the LMIs format.