• Title/Summary/Keyword: Time Spectral method

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Artificial Bandwidth Extension Based on Harmonic Structure Extension and NMF (하모닉 구조 확장과 NMF 기반의 인공 대역 확장 기술)

  • Kim, Kijun;Park, Hochong
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.12
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    • pp.197-204
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    • 2013
  • In this paper, we propose a new method for artificial bandwidth extension of narrow-band signal in frequency domain. In the proposed method, a narrow-band signal is decomposed into excitation signal and spectral envelope, which are extended independently in frequency domain. The excitation signal is extended such that low-band harmonic structure is maintained in high band, and the spectral envelope is extended based on sub-band energy using NMF. Finally, the spectral phase is determined based on signal correlation between frames in time domain, resulting in the final wide-band signal. The subjective evaluation verified that the wide-band signal generated by the proposed method has a higher quality than the original narrow-band signal.

Low Noise Time-Frequency Analysis Algorithm for Real-Time Spectral Estimation (실시간 뇌파 특성 분석을 위한 저잡음 스펙트럼 추정 알고리즘)

  • Kim, Yeon-Su;Park, Beom-Su;Kim, Seong-Eun
    • Journal of IKEEE
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    • v.23 no.3
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    • pp.805-810
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    • 2019
  • We present a time-frequency analysis algorithm based on the multitaper method and the state-space frameworks. In general, time-frequency representations have a trade-off between the time duration and the spectral bandwidth by the uncertainty principle. To optimize the trade-off problems, the short-time Fourier transform and wavelet based algorithms have been developed. Alternatively, the authors proposed the state-space frameworks based on the multitaper method in the previous work. In this paper, we develop a real-time algorithm to estimate variances and spectrum using the state-space framework. We test our algorithm in spectral analysis of simulated data.

Enhanced Spatial Covariance Matrix Estimation for Asynchronous Inter-Cell Interference Mitigation in MIMO-OFDMA System (3GPP LTE MIMO-OFDMA 시스템의 인접 셀 간섭 완화를 위한 개선된 Spatial Covariance Matrix 추정 기법)

  • Moon, Jong-Gun;Jang, Jun-Hee;Han, Jung-Su;Kim, Sung-Soo;Kim, Yong-Serk;Choi, Hyung-Jin
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.5C
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    • pp.527-539
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    • 2009
  • In this paper, we propose an asynchonous ICI (Inter-Cell Interference) mitigation techniques for 3GPP LTE MIMO-OFDMA down-link receiver. An increasing in symbol timing misalignments may occur relative to sychronous network as the result of BS (Base Station) timing differences. Such symbol synchronization errors that exceed the guard interval or the cyclic prefix duration may result in MAI (Multiple Access Interference) for other carriers. In particular, at the cell boundary, this MAI becomes a critical factor, leading to degraded channel throughput and severe asynchronous ICI. Hence, many researchers have investigated the interference mitigation method in the presence of asynchronous ICI and it appears that the knowledge of the SCM (Spatial Covariance Matrix) of the asynchronous ICI plus background noise is an important issue. Generally, it is assumed that the SCM estimated by using training symbols. However, it is difficult to measure the interference statistics for a long time and training symbol is also not appropriate for MIMO-OFDMA system such as LTE. Therefore, a noise reduction method is required to improve the estimation accuracy. Although the conventional time-domain low-pass type weighting method can be effective for noise reduction, it causes significant estimation error due to the spectral leakage in practical OFDM system. Therefore, we propose a time-domain sinc type weighing method which can not only reduce the noise effectively minimizing estimation error caused by the spectral leakage but also implement frequency-domain moving average filter easily. By using computer simulation, we show that the proposed method can provide up to 3dB SIR gain compared with the conventional method.

A Study on Analysis of Heart Rate Variability Using Fractal Dimension (FRACTAL 차원을 이용한 심박변화 분석에 관한 연구)

  • Lee, Byung-Chae;Lee, Myoung-Ho
    • Proceedings of the KOSOMBE Conference
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    • v.1994 no.12
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    • pp.169-171
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    • 1994
  • This paper is to find out more reliable analyzing method of heart rate variability. Heart rate variability analysis is to evaluate cardiovascular stability and also have used as an indicator of autonomic nervous system activity. In this study, time domain analysis, spectral analysis and state space analysis method are applied to analyze heart rate variability. Because of nonlinear characteristics of heart rate, we need not only spectral analysis, but also state space analysis. Fractal dimension of spectral estimation is useful indicator of autonomic nervous activity.

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A Closed-Form Solution of Linear Spectral Transformation for Robust Speech Recognition

  • Kim, Dong-Hyun;Yook, Dong-Suk
    • ETRI Journal
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    • v.31 no.4
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    • pp.454-456
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    • 2009
  • The maximum likelihood linear spectral transformation (ML-LST) using a numerical iteration method has been previously proposed for robust speech recognition. The numerical iteration method is not appropriate for real-time applications due to its computational complexity. In order to reduce the computational cost, the objective function of the ML-LST is approximated and a closed-form solution is proposed in this paper. It is shown experimentally that the proposed closed-form solution for the ML-LST can provide rapid speaker and environment adaptation for robust speech recognition.

IMPLEMENTATION OF REAL TIME RELP VOCODER ON THE TMS320C25 DSP CHIP

  • Kwon, Kee-Hyeon;Chong, Jong-Wha
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1994.06a
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    • pp.957-962
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    • 1994
  • Real-time RELP vocoder is implemented on the TMS320C25 DSP chip. The implemented system is IBM-PC add-on board and composed of analog in/out unit, DSP unit, memoy unit, IBM-PC interface unit and its supporting assembly software. Speech analyzer and synthesizer is implimented by DSP assembly software. Speech parameters such as LPC coefficients, base-band residuals, and signal gains is extracted by autocorrelation method and inverse filter and synthesized by spectral folding method and direct form synthesis filter in this board. And then, real-time RELP vocoder with 9.6Kbps is simulated by down-loading method in the DSP program RAM.

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Practical methods for GPU-based whole-core Monte Carlo depletion calculation

  • Kyung Min Kim;Namjae Choi;Han Gyu Lee;Han Gyu Joo
    • Nuclear Engineering and Technology
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    • v.55 no.7
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    • pp.2516-2533
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    • 2023
  • Several practical methods for accelerating the depletion calculation in a GPU-based Monte Carlo (MC) code PRAGMA are presented including the multilevel spectral collapse method and the vectorized Chebyshev rational approximation method (CRAM). Since the generation of microscopic reaction rates for each nuclide needed for the construction of the depletion matrix of the Bateman equation requires either enormous memory access or tremendous physical memory, both of which are quite burdensome on GPUs, a new method called multilevel spectral collapse is proposed which combines two types of spectra to generate microscopic reaction rates: an ultrafine spectrum for an entire fuel pin and coarser spectra for each depletion region. Errors in reaction rates introduced by this method are mitigated by a hybrid usage of direct online reaction rate tallies for several important fissile nuclides. The linear system to appear in the solution process adopting the CRAM is solved by the Gauss-Seidel method which can be easily vectorized on GPUs. With the accelerated depletion methods, only about 10% of MC calculation time is consumed for depletion, so an accurate full core cycle depletion calculation for a commercial power reactor (BEAVRS) can be done in 16 h with 24 consumer-grade GPUs.

A Study on the Voice Conversion Algorithm with High Quality (고음질을 갖는 음색변경에 관한 연구)

  • 박형빈;배명진
    • Proceedings of the IEEK Conference
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    • 2000.09a
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    • pp.157-160
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    • 2000
  • In the generally a voice conversion has used VQ(Vector Quantization) for partitioning the spectral feature and has performed by adding an appropriate offset vector to the source speaker's spectral vector. But there is not represented the target speaker's various characteristics because of discrete characteristics of transformed parameter. In this paper, these problems are solved by using the LMR(Linear Multivariate Regression) instead of the mapping codebook which is determined to the relationship of source and target speaker vocal tract characteristics. Also we propose the method for solved the discontinuity which is caused by applying to time aligned parameters using Dynamic Time Warping the time or pitch-scale modified speech. In our proposed algorithm for overcoming the transitional discontinuities, first of all, we don't change time or pitch scale and by using the LMR change a speaker's vocal tract characteristics in speech with non-modified time or pitch. Compared to existed methods based on VQ and LMR, we have much better voice quality in the result of the proposed algorithm.

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Bootstrap methods for long-memory processes: a review

  • Kim, Young Min;Kim, Yongku
    • Communications for Statistical Applications and Methods
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    • v.24 no.1
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    • pp.1-13
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    • 2017
  • This manuscript summarized advances in bootstrap methods for long-range dependent time series data. The stationary linear long-memory process is briefly described, which is a target process for bootstrap methodologies on time-domain and frequency-domain in this review. We illustrate time-domain bootstrap under long-range dependence, moving or non-overlapping block bootstraps, and the autoregressive-sieve bootstrap. In particular, block bootstrap methodologies need an adjustment factor for the distribution estimation of the sample mean in contrast to applications to weak dependent time processes. However, the autoregressive-sieve bootstrap does not need any other modification for application to long-memory. The frequency domain bootstrap for Whittle estimation is provided using parametric spectral density estimates because there is no current nonparametric spectral density estimation method using a kernel function for the linear long-range dependent time process.

Time Domain Acoustic Propagation Analysis Using 2-D Pseudo-spectral Modeling for Ocean Environment (해양환경에서 2차원 유사 스펙트럴 모델링을 이용한 시간 영역 음 전달 해석)

  • Kim Keesan;Lee Keunhwa;Seong Woojae
    • The Journal of the Acoustical Society of Korea
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    • v.23 no.8
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    • pp.576-582
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    • 2004
  • A computer code that is based on the Pseudo-spectral finite difference algorithm using staggered grid is developed for the wave propagation modeling in the time domain. The advantage of a finite difference approximation is that any geometrically complicated media can be modeled. Staggered grids are advantageous as it provides much more accuracy than using a regular grid. Pseudo-spectral methods are those that evaluate spatial derivatives by multiplying a wavenumber by the Fourier transform of a pressure wave-field and performing the inverse Fourier transform. This method is very stable and reduces memory and the number of computations. The synthetic results by this algorithm agree with the analytic solution in the infinite and half space. The time domain modeling was implemented in various models. such as half-space. Pekeris waveguide, and range dependent environment. The snapshots showing the total wave-field reveals the Propagation characteristic or the acoustic waves through the complex ocean environment.