Chuo-Yean Chang

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This paper presents an indoor positioning technique based on neural networks (NN). The received signal strengths (RSS) sensed by Zigbee wireless sensor network were used to estimate the position of object. From the simulation results shown, the NN technique proposed still has the high accuracy even the signal strengths sensed are unstable. Besides, from the(More)
In this paper, the transmittance estimation of touch panel decoration film by using quantum neural network (QNN) is proposed. This model is able to catch the complex relationship between the film’s transmittance and its possible influencing factors. An artificial intelligent (AI) mechanism for the decision of control parameters of film evaporation(More)
This paper presents the identifications of ammonia concentration by using several different neural network (NN) models. The shear horizontal surface acoustic wave (SH-SAW) device coated with polyaniline (PANI) film was applied as ammonia sensor. The data sensed by SH-SAW sensor was implemented by these NN models. A reliable and superior intelligent(More)
In this paper, a comparison study for the non-stationary power signal prediction by using several neural models is presented. A reliable and accurate neural forecasting model is trying to be found and concluded. This study is expected to provide some suggestions and could be treated as a reference for the researchers in this area. All simulations are(More)
This paper presents the chromatic aberration estimations of touch panel (TP) film by using quasi-Newton neural networks. The data of TP film with one layer coating was studied and simulated. Through the training of neural network, the complex relationship between the chromatic aberration, i.e., L.A.B. values, and the relative parameters of TP decoration(More)
In this paper, the signal processing by using polynomial neural network (NN) and its equivalent polynomial function is studied and simulated. To demonstrate the superiority of the equivalent polynomial function proposed, the signal recognition in a two-dimension (NC2) non-convex system and system identification were simulated and discussed. All simulations(More)
In this paper, an AI estimator of electric contract capacity for community antenna television system (CATV) based on quantum neural network (QNN) is proposed. This intelligent estimator not only can make CATV company have a good planning on the development of TV network system and power demand, but also can greatly reduce the company's running cost. In this(More)
In this paper, a hybrid supervised learning algorithm for neural network was proposed. The problem of local minimum learning usually occurred in the real application of neural network is tried to be solved or reduced. In order to improve the efficiency and stability of conventional error back-propagation learning algorithm, a hybrid learning method(More)
The paper presents an intelligent control mechanism for the ITO bar's resistance of touch panel (TP). The artificial neural network is used to catch the complex relationship between bar's resistance and its relevant manufacturing parameters during the printing and etching processes. An effective and accurate manufacturing mechanism of ITO bar is expected to(More)