• Title/Summary/Keyword: Discrete Signal

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Control For Minimizing Settling Time in High-Density Disk Drives (고밀도 디스크 드라이브의 안착시간 최소화 제어)

  • 강창익;김창환;임충혁
    • Journal of Institute of Control, Robotics and Systems
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    • v.9 no.1
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    • pp.10-21
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    • 2003
  • During seek operation in disk drives, the recording head is moved toward desired track by seek servo controller and then is settled onto the center of the desired track by settling servo controller. If the head speed at the start of settling servo control is not slow, it may produce overshoot relative to the center of track and thus extend the settling time. The degradation in settling performance will be more severe as the track width becomes smaller for higher density of data storage. We design a new settling servo controller for minimizing settling time based on the pole-zero cancellation. In order to cancel slow poles in settling response, we apply discrete pulse signals to the system in addition to the state feedback control. For exact pole-zero cancellation, we consider the dynamics of power amplifier used for actuator current regulation and the effects of delay in control action. In addition, we present system parameter identification algerian for the robustness of our controller to system parameter variation. In order to demonstrate the practical use of our controller, we present experimental results obtained by using a commercially available disk drive.

Speaker-Dependent Emotion Recognition For Audio Document Indexing

  • Hung LE Xuan;QUENOT Georges;CASTELLI Eric
    • Proceedings of the IEEK Conference
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    • summer
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    • pp.92-96
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    • 2004
  • The researches of the emotions are currently great interest in speech processing as well as in human-machine interaction domain. In the recent years, more and more of researches relating to emotion synthesis or emotion recognition are developed for the different purposes. Each approach uses its methods and its various parameters measured on the speech signal. In this paper, we proposed using a short-time parameter: MFCC coefficients (Mel­Frequency Cepstrum Coefficients) and a simple but efficient classifying method: Vector Quantification (VQ) for speaker-dependent emotion recognition. Many other features: energy, pitch, zero crossing, phonetic rate, LPC... and their derivatives are also tested and combined with MFCC coefficients in order to find the best combination. The other models: GMM and HMM (Discrete and Continuous Hidden Markov Model) are studied as well in the hope that the usage of continuous distribution and the temporal behaviour of this set of features will improve the quality of emotion recognition. The maximum accuracy recognizing five different emotions exceeds $88\%$ by using only MFCC coefficients with VQ model. This is a simple but efficient approach, the result is even much better than those obtained with the same database in human evaluation by listening and judging without returning permission nor comparison between sentences [8]; And this result is positively comparable with the other approaches.

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Fault diagnostic system for rotating machine based on Wavelet packet transform and Elman neural network

  • Youk, Yui-su;Zhang, Cong-Yi;Kim, Sung-Ho
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.9 no.3
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    • pp.178-184
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    • 2009
  • An efficient fault diagnosis system is needed for industry because it can optimize the resources management and improve the performance of the system. In this study, a fault diagnostic system is proposed for rotating machine using wavelet packet transform (WPT) and elman neural network (ENN) techniques. In most fault diagnosis for mechanical systems, WPT is a well-known signal processing technique for fault detection and identification. In previous work, WPT can improve the continuous wavelet transform (CWT) used over a longer computing time and huge operand. It can also solve the frequency-band disagreement by discrete wavelet transform (DWT) only breaking up the approximation version. In the experimental work, the extracted features from the WPT are used as inputs in an Elman neural network. The results show that the scheme can reliably diagnose four different conditions and can be considered as an improvement of previous works in this field.

Fano Decoding with Timeout: Queuing Analysis

  • Pan, W. David;Yoo, Seong-Moo
    • ETRI Journal
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    • v.28 no.3
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    • pp.301-310
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    • 2006
  • In mobile communications, a class of variable-complexity algorithms for convolutional decoding known as sequential decoding algorithms is of interest since they have a computational time that could vary with changing channel conditions. The Fano algorithm is one well-known version of a sequential decoding algorithm. Since the decoding time of a Fano decoder follows the Pareto distribution, which is a heavy-tailed distribution parameterized by the channel signal-to-noise ratio (SNR), buffers are required to absorb the variable decoding delays of Fano decoders. Furthermore, since the decoding time drawn by a certain Pareto distribution can become unbounded, a maximum limit is often employed by a practical decoder to limit the worst-case decoding time. In this paper, we investigate the relations between buffer occupancy, decoding time, and channel conditions in a system where the Fano decoder is not allowed to run with unbounded decoding time. A timeout limit is thus imposed so that the decoding will be terminated if the decoding time reaches the limit. We use discrete-time semi-Markov models to describe such a Fano decoding system with timeout limits. Our queuing analysis provides expressions characterizing the average buffer occupancy as a function of channel conditions and timeout limits. Both numerical and simulation results are provided to validate the analytical results.

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Performance analysis of multi-carrier CDMA system using an orthogonal pair of quadrature filter banks (직교 쌍 필터 뱅크 기반 다중 반송파 CDMA 시스템의 성능분석)

  • 이재철
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.9B
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    • pp.1570-1578
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    • 2000
  • A quadrature pair of filter banks that are composed of a pair of cosine and sine modulated filter banks is applied to MC-CDMA data transmultiplexing in the view point of mitigating inter-channel interferences. Exploiting superior capabilities of wavelet properties in composing the filter banks the proposed scheme is capable of compromising inter-channel interference problems better than the conventional DFT-based MC-CDMA due to superior subchannelization effects. To verify the behavior of our proposed MC-CDMA system based on the quadrature filter banks the reverse-link bit error rates with respect to signal-to-noise ratio under Rayleigth fading and additive white Gaussian noise channel environments are computed. The results show an improved system performance over the conventional MC-CDMA in the view point of minimizing interference effects.

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The Design of 50 MHz~3 GHz Wide-band Amplifier IC using SiGe HBT (SiGe HBT를 이용한 50 MHz~3 GHz 대역폭의 광대역 증폭기 IC 설계)

  • 이호성;김병성;박수균
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.13 no.1
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    • pp.68-73
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    • 2002
  • This paper presents the implementation of wide-band RFIC amplifier operating from near 50 MHz to 3 GHz using Tachyonics SiGe HBT foundry. Voltage shunt feedback is used for the flat gain and the broad band impedance matching. Initial design parameters are calculated through the low frequency small signal analysis. Since the HBT model was not available at the design time, discrete tuning board was made for fine adjustment in the low frequency range. Fabricated amplifier shows 12 dB gain with 1 dB fluctuation and P1 dB reaches 15 dBm at 850 MHz.

A Study on the Holter Data Compression Algorithm -Using Piecewise Self-Affine Fractal Model- (Holter Data 압축 알고리즘에 관한 연구 -Piecewise Self-Affine Fractal Model을 이용한-)

  • 전영일;정형만
    • Journal of Biomedical Engineering Research
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    • v.16 no.1
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    • pp.17-24
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    • 1995
  • This paper presents a new compression method (or ECG data using iterated contractive transformations. The method represents any range of ECG signal by piecewise self-afrine fractal Interpolation (PSAFI). The piecewise self-afrine rractal model is used where a discrete data set is viewed as being composed of contractive arfine transformation of pieces of itself. This algorithm was evaluated using MIT/BIH arrhythmia database. PSAFI is found to yield a relatively low reconstruction error for a given compression ratio than conventional direct compression methods. The compression ratio achieved was 883.9 bits per second (bps) - an average percent rms difference (AFRD) of 5.39 percent -with the original 12b ECG samples digitized at 400 Hz.

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A Watermarking System using Adaptive Thresholds (적응 임계값을 사용한 워터마킹 시스템)

  • Sang-Heun Oh;Sung-Wook Park;Bvyung-Jun Kim
    • Journal of KIISE:Information Networking
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    • v.30 no.1
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    • pp.30-37
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    • 2003
  • In this paper, a discrete wavelet transform (DWT)-based watermarking system is proposed. The main feature of proposed system is that the embedding system uses adaptive thresholds to control the trade-off between the qualify of the watermarked image and the capacity of the watermark, and the trade-off between the quality and robustness of the watermarked image. Also, the extracting system rebuilds threshold according to various attacks and decides a watermark bit from the least distorted coefficient after measuring the distortion of coefficient. Finally, a new measure to detect the uniqueness of watermark is proposed. The experimental result shows that the proposed watermarking system is robust against conventional signal processing and intentional attacks.

A Feature Vector Extraction Method For the Automatic Classification of Power Quality Disturbances (전력 외란 자동 식별을 위한 특징 벡터 추출 기법)

  • Lee, Chul-Ho;Lee, Jae-Sang;Cho, Kwan-Young;Chung, Ji-Hyun;Nam, Sang-Won
    • Proceedings of the KIEE Conference
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    • 1996.11a
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    • pp.404-406
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    • 1996
  • The objective of this paper is to present a new feature-vector extraction method for the automatic detection and classification of power quality(PQ) disturbances, where FFT, DWT(Discrete Wavelet Transform), and data compression are utilized to extract an appropriate feature vector. In particular, the proposed classifier consists of three parts: i.e., (i) automatic detection of PQ disturbances, where the wavelet transform and signal power estimation method are utilized to detect each disturbance, (ii) feature vector extraction from the detected disturbance, and (iii) automatic classification, where Multi-Layer Perceptron(MLP) is used to classify each disturbance from the corresponding extracted feature vector. To demonstrate the performance and applicability of the proposed classification algorithm, some test results obtained by analyzing 7-class power quality disturbances generated by the EMTP are also provided.

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Comparison of Fusion Methods for Generating 250m MODIS Image

  • Kim, Sun-Hwa;Kang, Sung-Jin;Lee, Kyu-Sung
    • Korean Journal of Remote Sensing
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    • v.26 no.3
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    • pp.305-316
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    • 2010
  • The MODerate Resolution Imaging Spectroradiometer (MODIS) sensor has 36 bands at 250m, 500m, 1km spatial resolution. However, 500m or 1km MODIS data exhibits a few limitations when low resolution data is applied at small areas that possess complex land cover types. In this study, we produce seven 250m spectral bands by fusing two MODIS 250m bands into five 500m bands. In order to recommend the best fusion method by which one acquires MODIS data, we compare seven fusion methods including the Brovey transform, principle components algorithm (PCA) fusion method, the Gram-Schmidt fusion method, the least mean and variance matching method, the least square fusion method, the discrete wavelet fusion method, and the wavelet-PCA fusion method. Results of the above fusion methods are compared using various evaluation indicators such as correlation, relative difference of mean, relative variation, deviation index, peak signal-to-noise ratio index and universal image quality index, as well as visual interpretation method. Among various fusion methods, the local mean and variance matching method provides the best fusion result for the visual interpretation and the evaluation indicators. The fusion algorithm of 250m MODIS data may be used to effectively improve the accuracy of various MODIS land products.