• IEIE Transactions on Smart Processing and Computing
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• 제1권1호
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• pp.50-64
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• 2012

Quality of Service (QoS) and fairness considerations are undoubtedly essential parameters that need to be considered in the design of next generation scheduling algorithms. This work presents a novel game theoretic cross-layer design that offers optimal allocation of wireless resources to heterogeneous services in Orthogonal Frequency Division Multiple Access (OFDMA) networks. The method is based on the Axioms of the Symmetric Nash Bargaining Solution (S-NBS) concept used in cooperative game theory that provides Pareto optimality and symmetrically fair resource distribution. The proposed strategies are determined via convex optimization based on a new solution methodology and by the transformation of the subcarrier indexes by means of time-sharing. Simulation comparisons to relevant schemes in the literature show that the proposed design can be successfully employed to typify ideal resource allocation for next-generation broadband wireless systems by providing enhanced performance in terms of queuing delay, fairness provisions, QoS support, and power consumption, as well as a comparable total throughput.

• 대한기계학회논문집
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• 제7권4호
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• pp.461-468
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• 1983

The series of experiments have been performed to study the transient heat transfer in air from a suddenly heated vertical thin wire. A platinum wire has been used as a resistance thermometer as well as a heating element to eliminate the disturbances in the measurements. The measured temperature as a function of time is compared with the calculated transient temperature with the aid of a pure conduction equation. The overshoot phenomena in terms of the Nusselt numbers have been detected and it is reasonable to define the delay time at which the onset of convection heat transfer occurs. The measured data are compared with the existing steady-state data and the agreements are reasonable within the comparable ranges.

• 한국음향학회:학술대회논문집
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• 한국음향학회 1992년도 학술논문발표회 논문집 제11권 1호
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• pp.61-65
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• 1992

This paper presents a study on Neural Networks for Phoneme Recognition and performs phoneme recognition using TDNN(Time Delay Neural Network). Also, this paper proposes new training algorithm for speech recognition using neural nets that proper to large scale TDNN. Because phoneme recognition is indispensable for continuous speech recognition, this paper uses TDNN to get accurate recognition result of phoneme. And this paper proposes new training algorithm that can converge TDNN to optimal state regardless of the number of phoneme to be recognized. The result of recognition on three phoneme classes shows recognition rate of 9.1%. And this paper proves that proposed algorithm is a efficient method for high performance and reducing convergence time.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2001년도 추계학술대회 논문집
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• pp.185-189
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• 2001

This paper presents a precision voltage control technique of a single phase PWM inverter for a constant voltage and constant frequency(CVCF) applications. The proposed control employes a PLL compensating loop which minimize the steady state error and phase delay. The computer simulation and experiment are carried out for the actual single phase PWM inverter and the results well demonstrate the effectiveness of the proposed control.

• 전기학회논문지P
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• 제65권4호
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• pp.292-297
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• 2016

The first-order plus dead time(FOPDT) and second-order plus dead time(SOPDT), which describes a linear monotonic process quite well in most chemical and industrial processes and is often sufficient for PID and IMC controller tuning. This paper presents an application of heuristic harmony search(HS) optimization algorithm to the identification of linear continuous time-delay systems from step response. This recently developed HS algorithm is conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search so that derivative information is unnecessary. The effectiveness of the proposed identification method has been demonstrated through a number of simulation examples.

• 한국정밀공학회지
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• 제24권11호
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• pp.91-100
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• 2007

Many manufacturing devices must execute motions as quickly as possible to achieve profitable high-volume production. Most of them have devices having flexibility and a time delay of one sampling is added to the plants when they are controlled by fast discrete controllers, which brings about non-minimum phase zeros. This paper develops a control strategy that combines feedforward and feedback control with command shaping for such devices. First, the feedback controller is designed to increase damping and eliminate steady-state error. Next, the feedforward controller is designed to speed up the transient response. Finally, an appropriate reference profile is generated using command-shaping techniques to ensure fast point-to-point motions with minimum residual vibration. The particular focus of the paper is to understand the interactions between these individual control components. The resulting control strategy is demonstrated on a model of a high-speed semiconductor manufacturing machine.

• 한국소음진동공학회논문집
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• 제17권7호
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• pp.662-667
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• 2007

A new neuro-control scheme for active control of structures is proposed. It utilizes lattice pattern of state vector as training data of probabilistic neural network(PNN). Therefore. it is the so-called lattice probabilistic neural network(LPNN). PNN makes control forces by using all the training patterns. Therefore, it takes much time to obtain a control force in application. This inevitably may delay the control action. However. control force of LPNN is calculated by using only the adjacent information of LPNN input. So, the response of LPNN is greatly faster than PNN. The proposed control algorithm is applied for three story building under California and El Centro earthquakes. Also, control results of the LPNN are compared with those of the conventional PNN. The structural responses have been suppressed effectively by the proposed algorithm.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 춘계학술대회논문집
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• pp.978-982
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• 2007

A new neuro-control scheme for active control of structures is proposed. It utilizes lattice pattern of state vector as training data of probabilistic neural network (PNN). Therefore, it is the so-called lattice probabilistic neural network (LPNN). PNN makes control forces by using all the training patterns. Therefore, it takes much time to obtain a control force in application. This inevitably may delay the control action. However, control force of LPNN is calculated by using only the adjacent information of LPNN input. So, the response of LPNN is greatly faster than PNN. The proposed control algorithm is applied for one story building under California and El Centro earthquakes. Also, control results of the LPNN are compared with those of the conventional PNN. The structural responses have been suppressed effectively by the proposed algorithm.

• 전기학회논문지
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• 제58권8호
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• pp.1624-1632
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• 2009

In this study, we introduce the design methodology of an optimized Interval Type-2 fuzzy controller. The fixed MF design of type-1 based FLC leads to the difficulty of rule-based control design for representing the linguistically uncertain expression. In the Type-2 FLC as the expanded type of Type-1 FLC, we can effectively improve the control characteristic by using the footprint of uncertainty(FOU) of membership function. Type-2 FLC has a robust characteristic in the unknown system with unspecific noise when compared with Type-1 FLC. Through computer simulation as well as practical experiment, we compare their performance by applying both the optimized Type-1 and Type-2 fuzzy cascade controllers to ball and beam system. To evaluate each controller performance, we consider controller characteristic parameters such as maximum overshoot, delay time, rise time, settling time and steady-state error.

• International Journal of Aeronautical and Space Sciences
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• 제18권4호
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• pp.757-766
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• 2017

For implementing the proportional navigation guidance law on passive homing missiles equipped with strapdown imaging infrared seekers, the line-of-sight angles and rates with respect to the inertial frame should be estimated by carefully handling the parasitic instability effect due to the seeker's latency. By introducing a new state vector representation along with the Pade approximation for compensating the time-delay of the seeker, this paper proposes a new guidance filter structure, stochastic dynamic models and measurement equations, in three-dimensional homing problem. Then, it derives the line-of-sight angle and rate estimator in general two-dimensional engagement by applying the extended Kalman filter to the proposed structure. The estimation performance and the characteristics of the proposed filter were evaluated via a series of numerical experiments.