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394 results on '"Bien Z"'

1. Learning Systems with FUZZY

Author

Lee, Sang Wan, Zenn Bien, Z., Kacprzyk, Janusz, Series editor, Tamir, Dan E., editor, Rishe, Naphtali D., editor, and Kandel, Abraham, editor

Published
2015
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2. Estimation of Instantaneous Bandwidth and Reconstruction of Noisy ECG Signal Measured by a 24- Hour Continuous Healthcare System for the Elderly and People with Disabilities

Author

Lee, Heyoung, Bien, Z. Zenn, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Lee, Yeunsook, editor, Bien, Z. Zenn, editor, Mokhtari, Mounir, editor, Kim, Jeong Tai, editor, Park, Mignon, editor, Kim, Jongbae, editor, Lee, Heyoung, editor, and Khalil, Ismail, editor

Published
2010
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16. Decentralized iterative learning control to large-scale industrial processes for nonrepetitive trajectory tracking

Author

Ruan, Xiaoe, Bien, Z. Zenn, and Park, Kwang-Hyun

Subjects
Algorithm, Algorithms -- Analysis, Mathematical optimization -- Evaluation
Abstract

In the procedure of steady-state hierarchical optimization with feedback for a large-scale industrial process, it is usual that a sequence of step set-point changes is carried out and used by the decision-making units while searching the eventual optimum. In this case, the real process experiences a form of disturbances around its operating set-point. In order to improve the dynamic performance of transient responses for such a large-scale system driven by the set-point changes, an open-loop proportional integral derivative-type iterative learning control (ILC) strategy is explored in this paper by considering the different magnitudes of the controller's step set-point change sequence. Utilizing the Hausdorff-Young inequality of convolution integral, the convergence of the algorithm is derived in the sense of Lebesgue-P norm. Furthermore, the extended higher order ILC rule is developed, and the convergence is analyzed. Simulation results illustrate that the proposed ILC strategies can remarkably improve the dynamic performance such as decreasing the overshoot, accelerating the transient response, shortening the settling time, etc. Index Terms--Convergence, effectiveness, higher order, iterative learning control (ILC), large-scale systems, Lebesgue-P norm, steady-state optimization.

Published
2008

19. Intention reading is essential in human-friendly interfaces for the elderly and the handicapped

Author

Bien, Z. Zenn, Park, Kwang-Hyun, Jung, Jin-Woo, and Do, Jun-Hyeong

Subjects
Aged -- Education, Intelligent devices -- Usage, Computer interfaces -- Research, IEEE-488 interface, Business, Computers, Electronics, Electronics and electrical industries
Abstract

Some major issues of human-friendly man-machine interaction/interfaces in an intelligent residential system are dealt with to cope with increasing needs of the elderly and the handicapped for a higher level of living conditions. Specifically, the existing systems in this area are first examined and the inadequacy of some current remote-control interfaces for the elderly/handicapped is pointed out. Then, some intention-reading techniques are introduced for the elderly and/or the physically handicapped, for easier and more convenient use of machines and engineering systems. Index Terms--Human-friendly interface, intelligent residential system, intention reading.

Published
2005

24. Fuzzy Inductive Learning System for Learning Preference of the User's Behavior Pattern

Author

Lee Hyong-Euk, Cho Joonmyun, Kim MinGyoung, Bien Z. Zenn, Kim Yong-Su, June Jin-Woo, Kim Yong-Hwi, and Park Kwang-Hyun

Subjects
Preference learning, Knowledge extraction, Computer science, Home automation, business.industry, Behavioral pattern, Construct (python library), Artificial intelligence, business, Fuzzy logic, Preference, Cognitive load
Abstract

Smart home is one of the ubiquitous environment platforms with various complex sensor-and-control network. In this paper, a now learning methodology for learning user`s behavior preference pattern is proposed in the sense of reductive user`s cognitive load to access complex interfaces and providing personalized services. We propose a fuzzy inductive learning methodology based on life-long learning paradigm for knowledge discovery, which tries to construct efficient fuzzy partition for each input space and to extract fuzzy association rules from the numerical data pattern.

Published
2005

35. An action-based behavior model for persuasive telehealth

Author

Lee, Yeunsook, Bien, Z. Zenn, Mokhtari, Mounir, Kim, Jeong Tai, Park, Mignon, Kim, Jongbae, Lee, Heyoung, Khalil, Ismail, Lee, D., Helal, Sumi, Johnson, B.D., Lee, Yeunsook, Bien, Z. Zenn, Mokhtari, Mounir, Kim, Jeong Tai, Park, Mignon, Kim, Jongbae, Lee, Heyoung, Khalil, Ismail, Lee, D., Helal, Sumi, and Johnson, B.D.

Abstract

Technological advances in telehealth systems are primarily focused on sensing, monitoring and analysis. Intervention, behavior alternation and in general affecting change could use additional research and technology development. Many people, especially the elderly, are resistant to change. Such resistance diminishes the impact factor of telehealth systems. Persuasion technology and mechanisms are urgently needed to counter this resistance to change and promote healthy lifestyle. In this paper, we propose an action- based behavior model to enable persuasion. We also review existing technologies we believe are most suitable for enabling persuasive telehealth. We present our ongoing work in the domain of behavior alteration for obese and diabetic individuals. © 2010 Springer-Verlag.

Published
2010

40. A multivariable generalized predictive control approach based on T-S fuzzy model

Author

Zhang, HG, Cai, LL, Bien, Z., Zhang, HG, Cai, LL, and Bien, Z.

Abstract

In this paper, the Takagi-Sugeno (T-S) fuzzy model is used to express dynamic systems, and an on-line identification algorithm for its parameters and structures is presented. A new multivariable fuzzy generalized predictive control approach is put forward based on the identified fuzzy model by means of Clark's principle of single-variable generalized predictive control, some of whose performances are analysed in detail. A simulation study of the multivariable load system of electric generating unit shows that the approach is superior to conventional load control systems.

Published
2000

41. A fuzzy basis function vector-based multivariable adaptive controller for nonlinear systems

Author

Zhang, HG, Cai, Lilong, Bien, Z., Zhang, HG, Cai, Lilong, and Bien, Z.

Abstract

In this paper, a new fuzzy basis function vector (FBFV) approach for the adaptive control of multivariable nonlinear systems is presented. With this method, the nonlinear plant is first linearized. The linearized bias and uncertainties as well as disturbances are assumed to be included in the model structure and their upper bound will be adaptively learned by the FBFV method. The output of the FBFV is used as the parameters of the robust controller in the sense that both the robustness and the asymptotic error convergence can be obtained for the multivariable nonlinear system. The effectiveness of the proposed analysis and design method is illustrated with a simulated example.

Published
2000

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