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收集所有交通大學研究人員與學生個人或團體所發表之各項學術著作，涵蓋期刊論文、教師專書、學位論文等項。;;Collections of Publications of NCTU Researchers and Students Like Journal Papers and Thesis.

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🏛️國立陽明交通大學機構典藏

Author: search.filters.author.Wu, RC

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Now showing 1 - 10 of 18
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    Frequency estimation of phase-modulated carriers
    (1998-12-01)
    Su, YT
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    Wu, RC
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    電信工程研究所
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    Institute of Communications Engineering
    Conventional approach for frequency estimation usually assume a single tone without data modulation. In many applications such an assumption, realized by using either a separate pilot beacon or synchronization preamble is not feasible. This paper deals with frequency estimation of phase-modulated carriers in the absence of timing information and known data pattern. We introduce new frequency estimators that are based on the generalized maximum likelihood principle. The communication channels under consideration include both additive white Gaussian noise (AWGN) channels and correlated Rician fading channels. For the latter class, we distinguish between the case when the fading (amplitude) process is tracked and that when it is not tracked.
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    Noncoherent detectors for PN code acquisition in the presence of data modulation
    (2000-11-01)
    Wu, RC
    ;
    Su, YT
    ;
    Lin, WC
    ;
    電信工程研究所
    ;
    Institute of Communications Engineering
    Noncoherent detectors for use in acquiring data-modulated direct-sequence spread-spectrum (DS/SS) signals are considered in this paper. Taking data modulation and timing uncertainty into account and using the generalized maximum likelihood (GML) or maximum likelihood (ML) detection approaches, we derive optimal detectors in the sense of Bayes or Neyman-Pearson and propose various suboptimal detectors. A simple systematic means for their realization is suggested and the numerical performance of these detectors is presented. We also compare their performance with that of the noncoherent combining (NC1) detector that had been proposed to serve the same need. Numerical results show that even the proposed suboptimal detectors can outperform the NC1 detector in most cases of interest.
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    Frequency acquisition and tracking in high dynamic environments
    (2000-11-01)
    Su, YT
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    Wu, RC
    ;
    電信工程研究所
    ;
    友訊交大聯合研發中心
    ;
    Institute of Communications Engineering
    This paper presents mean squared error (MSE) analysis of two classes of frequency acquisition and tracking algorithms. Additive white Gaussian noise as well as Rician fading channels are considered, The class of batch-processing algorithms is an extension of earlier least squares proposals used in more benign (lower dynamic) environments. These algorithms try to fit the phase trajectory of the down-converted samples of a received signal. Such a trajectory will depend on the histories of both the signal and the local frequency variations when the local frequency is updated recursively. We propose a method to solve this difficulty and present both first-order and second-order recursive algorithms. Numerical results demonstrate that the MSE performance predicted by our analysis is consistent with that estimated by computer simulation and that the proposed algorithms not only provide rapid acquisition times but also give small tracking jitters.
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    Noisy speech segmentation/enhancement with multiband analysis and neural fuzzy networks
    (2002-11-01)
    Lin, CT
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    Wu, RC
    ;
    Wu, GD
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    電控工程研究所
    ;
    Institute of Electrical and Control Engineering
    This paper addresses the problem of speech segmentation and enhancement in the presence of noise. We first propose a new word boundary detection algorithm by using a neural fuzzy network (called ATF-based SONFIN algorithm) for identifying islands of word signals in fixed noise-level environment. We further propose a new RTF-based RSONFIN algorithm where the background noise level varies during the procedure of recording. The adaptive time-frequency (ATF) and refined time-frequency (RTF) parameters extend the TF parameter from single band to multiband spectrum analysis, and help to make the distinction of speech and noise signals clear. The ATF and RTF parameters can extract useful frequency information by adaptively choosing proper bands of the mel-scale frequency bank. Due to the self-learning ability of SONFIN and RSONFIN, the proposed algorithms avoid the need of empirically determining thresholds and ambiguous rules. The RTF-based RSONFIN algorithm can also find the variation of the background noise level and detect correct word boundaries in the condition of variable background noise level by processing the temporal relations. Our experimental results show that both in the fixed and variable noise-level environment, the algorithms that we proposed achieved higher recognition rate than several commonly used word boundary detection algorithms and reduced the recognition error rate due to endpoint detection.
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    Design an intelligent CIM system based on data mining technology for new manufacturing processes
    (2004)
    Wu, RC
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    Chen, RS
    ;
    Fan, CR
    ;
    資訊管理與財務金融系 註：原資管所+財金所
    ;
    Department of Information Management and Finance
    The purpose of this paper is to explain a specific intelligent CIM (computer integrated manufacturing) system by integrating the following five major subject areas: computer integrated manufacturing, data warehouse, online analytical processing (OLAP), data mining and artificial intelligence. The data mining system makes use of the decision tree algorithm and classification model in exploring the meaningful information, which is useful in the process of decision making. Subsequently, the rules discovered by the data mining system are expressed through the rule based knowledge presentation method of the expert system. The intelligent CIM system is applied to semiconductor packing factories and also point at the great fluctuation of DRAM (dynamic random access memory) prices. The results of this paper are the product yield, the manufacturing cycle time and the frequency of holding lot, which have been improved. The contribution can increase business competitiveness, reduce production cost, and promote the rate of available promise for order.
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    A novel prosodic-information synthesizer based on recurrent fuzzy neural network for the Chinese TTS system
    (2004-02-01)
    Lin, CT
    ;
    Wu, RC
    ;
    Chang, JY
    ;
    Liang, SF
    ;
    電控工程研究所
    In this paper, a new technique for the Chinese text-to-speech (TTS) system is proposed. Our major effort focuses on the prosodic information generation. New methodologies for constructing fuzzy rules in a prosodic model simulating human's pronouncing rules are developed. The proposed Recurrent Fuzzy Neural Network (RFNN) is a multilayer recurrent neural network (RNN) which integrates a Self-constructing Neural Fuzzy Inference Network (SONFIN) into a recurrent connectionist structure. The RFNN can be functionally divided into two,parts. The first part adopts the SONFIN as a prosodic model to explore the relationship between high-level linguistic features and prosodic information based on fuzzy inference rules. As compared to conventional neural networks, the SONFIN can always construct itself with an economic network size in high learning speed. The second part employs a five-layer network to generate all prosodic parameters by directly using the prosodic fuzzy rules inferred from the first part as well as other important features of syllables. The TTS system combined with the proposed method can behave not only sandhi rules but also the other prosodic phenomena existing in the traditional TTS systems. Moreover, the proposed scheme can even find out some new rules about prosodic phrase structure. The performance of the proposed RFNN-based prosodic model is verified by imbedding it into a Chinese TTS system with a Chinese monosyllable database based on the time-domain pitch synchronous overlap add (TD-PSOLA) method. Our experimental results show that the proposed RFNN can generate proper prosodic parameters including pitch means, pitch shapes, maximum energy levels, syllable duration, and pause duration. Some synthetic sounds are on-line available for demonstration.
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    Estimating driving performance based on EEG spectrum analysis
    (2005)
    Lin, CT
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    Wu, RC
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    Jung, TP
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    Liang, SF
    ;
    Huang, TY
    The growing number of traffic accidents in recent years has become a serious concern to society. Accidents caused by driver's drowsiness behind the steering wheel have a high fatality rate because of the marked decline in the driver's abilities of perception, recognition, and vehicle control abilities while sleepy. Preventing such accidents caused by drowsiness is highly desirable but requires techniques for continuously detecting, estimating, and predicting the level of alertness of drivers and delivering effective feedbacks to maintain their maximum performance. This paper proposes an EEG-based drowsiness estimation system that combines electroencephalogram (EEG) log subband power spectrum, correlation analysis, principal component analysis, and linear regression models to indirectly estimate driver's drowsiness level in a virtual-reality-based driving simulator. Our results demonstrated that it is feasible to accurately estimate quantitatively driving performance, expressed as deviation between the center of the vehicle and the center of the cruising lane, in a realistic driving simulator.
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    Frequency acquisition and tracking for mobile LEO satellite communications
    (1997)
    Su, YT
    ;
    Wu, RC
    ;
    交大名義發表
    ;
    電信工程研究所
    ;
    National Chiao Tung University
    A class of recursive frequency acquisition and tracking algorithms for use in high dynamic mobile low earth orbit (LEO) satellite communication systems is proposed. The underlying principle of these algorithms is to apply the least-squares method to the reconstructed phase trajectories to estimate and predict the received frequency variations (Doppler frequency, Doppler rate, etc.). We consider both additive white Gaussian noise (AWGN) and Rician fading channels and analyze the corresponding mean squared errors (MSE). Numerical performance of the proposed algorithms demonstrates that the new frequency tracking algorithms not only has rapid acquisition times but also gives smaller tracking jitters.
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    Code acquisition in a class of time-varying channels
    (1998)
    Su, YT
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    Wu, RC
    ;
    電信工程研究所
    ;
    Institute of Communications Engineering
    This paper presents a model for the code acquisition in a time-varying channel and evaluates the associated acquisition time statistics. We first use a finite-state Markov chain to represent the time-varying channel. Each channel state can have either a frequency-selective or a frequency-nonselective fading characteristic. This model is an unconstrained model as it does not take into account two time-parameters. The first time-parameters the "time unit" for the Markov channel, which has to be determined by the channel Doppler spread or its fading rate. The second time-parameter has to do with the detection structure. Incorporating the constraints imposed by these two time-parameters we discuss modifications of the unconstrained model, derive related statistics (e.g., probability distribution function or characteristic function) of the acquisition time and then provide numerical examples of the acquisition time performance.
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    Optimal and suboptimal noncoherent detectors for PN code acquisition in the presence of data modulation
    (1998)
    Su, YT
    ;
    Lin, WC
    ;
    Wu, RC
    ;
    電信工程研究所
    ;
    Institute of Communications Engineering
    Noncoherent detectors for use in acquiring data-modulated direct-sequence spread-spectrum (DS/SS) signals are considered in this paper. Taking data modulation into account, we examine maximum likelihood (ML) and generalized maximum likelihood (GML) detection structures and then derive suboptimal detectors. We call one of the suboptimal detector as noncoherent partially matched filter (PMF) as it matches only part of the family of legitimate data patterns, We compare the detector operating characteristic (DOC) performance of the PM filter and that of the noncoherent combining (NC) detector that had been proposed to serve the same need. Although the PM filter requires a little more computing it does give better performance.