• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.49-54
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• 2007

Structural integrity assessment technique for pavement system is studied considering the uncertainties among the material properties. The artificial neural networks technique is applied for the inverse analysis to estimate the elastic modulus based on the measured deflections from the FWD test. A computer code based on the spectral element method was developed for the accurate and fast analysis of the multi-layered soil structures, and the developed program was used for generating the training and testing patterns for the neural network. Neural networks was applied to estimate the elastic modulus of pavement system using the maximum deflections with and without the uncertainties in the material properties. It was found that the estimation results by the conventiona1 neural networks were very poor when there exist the uncertainties and the estimation results could be significantly improved by adopting the proposed method for generating training patterns considering the uncertainties among material properties.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.1
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• pp.1-5
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• 2004

A new method for the estimation of pitch-frequency contour of voiced speech is presented. The method is based on the double application of Kaiser's energy operator［1］, which has the capabilities of extracting amplitude and frequency of a sinusoidal waveform. According to the modulation model, a vowel can be represented by a combination of damped sinusoids representing formants, modulated by pitch pulses. Therefore, the amplitude envelope of each of the components will give a pitch-like waveform and the pitch can be obtained by averaging the frequencies of this waveform. The first part is the same as Gopalan's approach［9］, but by substituting the LPC based spectral analysis with the second application of energy operator, the algorithm becomes very simple and can be processed on-line. Although the estimation is rather coarse, the suggested algorithm can be useful for getting a general sketch of pitch contour on-line.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.3
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• pp.142-152
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• 2014

Vehicular Ad-hoc Networks (VANETs) are comprised of wireless mobile nodes characterized by a randomly changing topology, high mobility, availability of geographic position, and fewer power constraints. Orthogonal Frequency Division Multiplexing (OFDM) is a promising candidate for the physical layer of VANET because of the inherent characteristics of the spectral efficiency and robustness to channel impairments. The susceptibility of OFDM to Inter-Carrier Interference (ICI) is a challenging issue. The high mobility of nodes in VANET causes higher Doppler shifts, which results in ICI in the OFDM system. In this paper, a frequency domain com-btype channel estimation was used to cancel out ICI. The channel frequency response at the pilot tones was estimated using a Least Square (LS) estimator. An efficient interpolation technique is required to estimate the channel at the data tones with low interpolation error. This paper proposes a robust interpolation technique to estimate the channel frequency response at the data subcarriers. The channel induced noise tended to degrade the Bit Error Rate (BER) performance of the system. Parallel concatenated Convolutional codes were used for error correction. At the decoding end, different decoding algorithms were considered for the component decoders of the iterative Turbo decoder. A performance and complexity comparison among the various decoding algorithms was also carried out.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.6 s.360
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• pp.18-23
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• 2007

In this Paper, we consider multiple input multiple output Feher-patented quadrature phase shift keying (MIMO-FQPSK) system supporting high spectral efficiency and throughput. Based on the fact that the complex baseband signal sampled at every bit duration has only eight phase values and its signal can be considered as 8-phase-shift keying signal, FQPSK demodulation with maximum likelihood sequence estimation(MLSE) is considered and it is extended to MIMO system. The performance of MIMO-FQPSK receiver is analyzed by computer simulation and by considering the union upper bounds for zrero forcing detection and minimum mean square error detection.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.12
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• pp.1756-1760
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• 2015

This paper focuses on a priori signal to noise ratio (SNR) estimation method for the speech enhancement. There are many researches for speech enhancement with several ambient noise cancellation methods. The method based on spectral subtraction (SS) which is widely used in noise reduction has a trade-off between the performance and the distortion of the signals. So the need of adaptive method like an estimated a priori SNR being able to making a high performance and low distortion is increasing. The decision directed (DD) approach is used to determine a priori SNR in noisy speech signals. A priori SNR is estimated by using only the magnitude components and consequently follows a posteriori SNR with one frame delay. We propose a modified a priori SNR estimator and the weighted rational transfer function for speech enhancement with wind noises. The experimental result shows the performance of our proposed estimator is better Perceptual Evaluation of Speech Quality scores (PESQ, ITU-T P.862) compare to the conventional DD approach-based systems and different noise reduction methods.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.11
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• pp.1206-1212
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• 2008

This paper presents a the method for estimating the noise source contribution on the road noise of the vehicle in a multiple input system where the input sources may be coherent with each other. By coherence function method, it is found that the biggest part of the noise source in the road noise is generated by structural vibration on the mechanical-acoustic transfer functions of vehicles. This analysis is modeled as four input/single output system because the noise is generated with four wheels that mechanism of the road noise is very complicated. The coherence function method is proved to be useful tool for identifying of noise source. The overall levels of the interior noise be coherence function method are compared with those measured and calculated by the frequency response function approach using mechanical excitation test. The experimental results have shown a good agreement with the results calculated by the coherence function method when the input sources are coherent strongly each other. The estimation of the road noise indicates that significant coherent can be achieved in the vehicle interior noise.

• Wind and Structures
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• v.21 no.4
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• pp.443-460
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• 2015

In this paper, an integrator based method to estimate the effective wind speed in wind turbine systems is proposed. First, the aerodynamic torque was accurately estimated through a proportional gain based observer where the generator speed is the measured output of the system. The torque signal contains not only useful frequencies of the wind, but also high frequencies and the ones due to structural vibration. The useful information of the wind signal is low frequency. A spectral analysis permitted the determination of the useful frequencies. The high frequencies were then filtered before introducing the torque signal in the wind speed observer. The desired effective wind speed was extracted through an integrator based observer using the previously estimated aerodynamic torque. The strength of the method is to avoid numerical solutions used in literature of the wind speed estimation. The effectiveness of the proposed wind speed estimator and its use to control the generator speed has been tested under turbulent situations using the FAST software (Fatigue, Aerodynamics, Structures, and Turbulence), for large scale Megawatt turbine.

• Structural Engineering and Mechanics
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• v.50 no.5
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• pp.653-664
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• 2014

Wind fragility analysis provides a quantitative instrument for delineating the safety performance of civil structures under hazardous wind loading conditions such as cyclones and tornados. It has attracted and would be expected to continue to attract intensive research spotlight particularly in the nowadays worldwide context of adapting to the changing climate. One of the challenges encumbering efficacious assessment of the safety performance of existing civil structures is the possible incompleteness of the structural appraisal data. Addressing the issue of the data missingness, the study presented in this paper forms a first attempt to investigate the feasibility of using the expectation-maximization (EM) algorithm and Bayesian techniques to predict the wind fragilities of existing civil structures. Numerical examples of typical linear or hysteretic shear frames are introduced with the wind loads derived from a widely used power spectral density function. Specifically, the application of the maximum a posteriori estimates of the distribution parameters for the story stiffness is examined, and a surrogate model is developed and applied to facilitate the nonlinear response computation when studying the fragilities of the hysteretic shear frame involved.

• Current Optics and Photonics
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• v.4 no.4
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• pp.317-325
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• 2020

Accurate estimation of spatial frequencies and phases for illumination patterns are essential to reconstructing super-resolution images in structured illumination microscopy (SIM). In this manuscript, we propose the improved component cross-correlation (ICC) algorithm, which is based on optimization of the cross-correlation values of the overlapping information between various spectral components. Compared to other algorithms for spatial-frequency and phase determination, the results calculated by the ICC algorithm are more accurate when the modulation depths of the illumination patterns are low. Moreover, the ICC algorithm is able to calculate the spatial frequencies and phases simultaneously. Simulation results indicate that even if the modulation depth is lower than 0.1, the ICC algorithm still estimates the parameters precisely; the images reconstructed by the ICC algorithm are much clearer than those reconstructed by other algorithms. In experiments, our home-built SIM system was used to image bovine pulmonary artery endothelial (BPAE) cells. Drawing support from the ICC algorithm, super-resolution images were reconstructed without artifacts.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.161-167
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• 2021

This paper proposes a new personalized HRTF estimation method which is based on a deep neural network (DNN) model and improved elevation reproduction using a notch filter. In the previous study, a DNN model was proposed that estimates the magnitude of HRTF by using anthropometric measurements [1]. However, since this method uses zero-phase without estimating the phase, it causes the internalization (i.e., the inside-the-head localization) of sound when listening the spatial sound. We devise a method to estimate both the magnitude and phase of HRTF based on the DNN model. Personalized HRIR was estimated using the anthropometric measurements including detailed data of the head, torso, shoulders and ears as inputs for the DNN model. After that, the estimated HRIR was filtered with an appropriate notch filter to improve elevation reproduction. In order to evaluate the performance, both of the objective and subjective evaluations are conducted. For the objective evaluation, the root mean square error (RMSE) and the log spectral distance (LSD) between the reference HRTF and the estimated HRTF are measured. For subjective evaluation, the MUSHRA test and preference test are conducted. As a result, the proposed method can make listeners experience more immersive audio than the previous methods.