• Title/Summary/Keyword: signal adaptation

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A Study on Phoneme Recognition using Neural Networks and Fuzzy logic (신경망과 퍼지논리를 이용한 음소인식에 관한 연구)

  • Han, Jung-Hyun;Choi, Doo-Il
    • Proceedings of the KIEE Conference
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    • 1998.07g
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    • pp.2265-2267
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    • 1998
  • This paper deals with study of Fast Speaker Adaptation Type Speech Recognition, and to analyze speech signal efficiently in time domain and time-frequency domain, utilizes SCONN[1] with Speech Signal Process suffices for Fast Speaker Adaptation Type Speech Recognition, and examined Speech Recognition to investigate adaptation of system, which has speech data input after speaker dependent recognition test.

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Soft Decision Approaches for Blind Decision Feedback Equalizer Adaptation (소프트 판정을 이용한 자력복구 적응 판정궤환 채널등화 기법)

  • Chung Won-Zoo
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.43 no.8 s.350
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    • pp.69-76
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    • 2006
  • In this paper, we propose blind adaptation strategies for decision feedback equalizer (DFE) optimizing the operation mode between acquisitionand tracking modes based on adjustable soft decision devices. The proposed schemes select an optimal soft decision device to generate feedback samples for the DFE at a given noise to signal ratio, and apply corresponding adaptation rules which combine a blind infinite impulse response (IIR) filtering adaptation and the decision-directed least mean squared (DD-LMS) DFE adaptation. These adaptation approaches attempt to achieve not only smooth transition between acquisition and tracking of DFE but also mitigation of error propagation.

Machine-Learning-Based Link Adaptation for Energy-Efficient MIMO-OFDM Systems (MIMO-OFDM 시스템에서 에너지 효율성을 위한 기계 학습 기반 적응형 전송 기술 및 Feature Space 연구)

  • Oh, Myeung Suk;Kim, Gibum;Park, Hyuncheol
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.27 no.5
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    • pp.407-415
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    • 2016
  • Recent wireless communication trends have emphasized the importance of energy-efficient transmission. In this paper, link adaptation with machine learning mechanism for maximum energy efficiency in multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM) wireless system is considered. For reflecting frequency-selective MIMO-OFDM channels, two-dimensional capacity(2D-CAP) feature space is proposed. In addition, machine-learning-based bit and power adaptation(ML-BPA) algorithm that performs classification-based link adaptation is presented. Simulation results show that 2D-CAP feature space can represent channel conditions accurately and bring noticeable improvement in link adaptation performance. Compared with other feature spaces, including ordered postprocessing signal-to-noise ratio(ordSNR) feature space, 2D-CAP has distinguished advantages in either efficiency performance or computational complexity.

THE EFFECTS OF ZINC DURING VISUAL ADAPTATION OF VERTEBRATE EYE

  • Kim, Hyun-Jung
    • Journal of Photoscience
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    • v.2 no.2
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    • pp.63-67
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    • 1995
  • Zinc plays a key role in genetic expression, cell division, and growth and is essential for the function of more than 200 enzymes; effects of zinc deficiency induce many syndromes, including abnormal visual adaptation. The pigment epithelium (EP) contains high concentrations of zinc in humans and in animals and it participates in threshold elevation, visual sensitivity increment, and acceleration of rhodopsin regeration during visual adaptation. The origin of c-wave of electroretinogram(ERG) is not only pigment epithelium as shown in present research, but also other cell layers, perhaps the photoreceptors. We propose zinc as a candidate for an internal messenger which participates in signal amplification.

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Adaptive echo canceller combined with speech coder for mobile communication systems (이동통신 시스템을 위한 음성 부호화기와 결합된 적응 반향제거기에 관한 연구)

  • 이인성;박영남
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.23 no.7
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    • pp.1650-1658
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    • 1998
  • This paper describes how to remove echoes effectively using speech parameter information provided form speech coder. More specially, the proposed adaptive echo canceller utilizes the excitation signal or linearly predicted error signal instead of output speech signal of vocoder as the input signal for adaptation algorithm. The normalized least mean ssquare(NLMS) algorithm is used for the adaptive echo canceller. The proposed algorithm showed a fast convergece charactersitcis in the sinulatio compared to the conventional method. Specially, the proposed echo canceller utilizing the excitation signal of speech coder showed about four times fast convergence speed over the echo canceller utilizing the output speech signal of the speech coder for the adaptation input.

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A comparative study on the improvement of the robustness in adaptive control systems (적응제어의 강인성개선에 관한 비교연구)

  • 김국헌;김영철;양흥석
    • 제어로봇시스템학회:학술대회논문집
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    • 1986.10a
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    • pp.352-355
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    • 1986
  • In this paper, some candidates suggested for the improvement of the robustness in adaptive control systems are shortly surveyed. Using dead zone concept of error in adaptation process, gain retardation methods such as .sigma.-modification and parameter restriction method are those considered. Feedforward compensation and normalized adaptation technique are also considered. New modeling technique suggested by Donati et al is used for the indirect control of plants containing unmodeled dynamics. The frequency band of input signal, which is used as a test signal and control signal simultaneously, is directly related to the control of plants containing high frequency parastics. Computer simulation results of the some selected algorithms are shown.

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The Study on the Speaker Adaptation Using Speaker Characteristics of Phoneme (음소에 따른 화자특성을 이용한 화자적응방법에 관한 연구)

  • 채나영;황영수
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2003.06a
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    • pp.6-9
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    • 2003
  • In this paper, we studied on the difference of speaker adaptation according to the phoneme classification for Korean Speech recognition. In order to study of speech adaptation according to the weight of difference of phoneme as recognition unit, we used SCHMM as recognition system. And Speaker adaptation method used in this paper was MAPE(Maximum A Posteriori Probability Estimation), Linear Spectral Estimation. In order to evaluate the performance of these methods, we used 10 Korean isolated numbers as the experimental data. It is possible for the first and the second methods to be carried out unsupervised learning and used in on-line system. And the first method was shown performance improvement over the second method, and hybrid adaptation showed the better recognition results than those which performed each method. And the result of Speaker adaptation using the variable weight according to the phoneme had better than the result using fixed weight.

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A Study on the Beam Steering Error Modification method to Adaptive Array System (적응배열 시스템에서 빔 지향 오차 수정기법에 대한 연구)

  • Lee, Myung-Ho
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.4
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    • pp.39-44
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    • 2008
  • Wireless channel exists interference by multipath a component. Adaptation array antenna that remove this interference a component forms null point about interference signal and maximizes gains about target signal. If target signal and correlative coherent interference signal are received, there is problem that is removed from arrangement output to target signal. And, adaptation array antenna is shortcoming that is sensitive in directivity error. Therefore, in this paper, introduce each existing algorithm to solve directivity error about coherent interference, and proposed beam forming technique that minimize degree of freedom loss and damage because analyzes the problem and reduces coherent interference and directivity error.

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Nonlinear Echo Cancellation using a Correlation LMS Adaptation Scheme (상관(Correlation) LMS 적응 기법을 이용한 비선형 반향신호 제거에 관한 연구)

  • Park, Hong-Won;An, Gyu-Yeong;Song, Jin-Yeong;Nam, Sang-Won
    • Proceedings of the KIEE Conference
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    • 2003.11c
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    • pp.882-885
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    • 2003
  • In this paper, nonlinear echo cancellation using a correlation LMS (CLMS) algorithm is proposed to cancel the undesired nonlinear echo signals generated in the hybrid system of the telephone network. In the telephone network, the echo signals may result the degradation of the network performance. Furthermore, digital to analog converter (DAC) and analog to digital converter (ADC) may be the source of the nonlinear distortion in the hybrid system. The adaptive filtering technique based on the nonlinear Volterra filter has been the general technique to cancel such a nonlinear echo signals in the telephone network. But in the presence of the double-talk situation, the error signal for tap adaptations will be greatly larger, and the near-end signal can cause any fluctuation of tap coefficients, and they may diverge greatly. To solve a such problem, the correlation LMS (CLMS) algorithm can be applied as the nonlinear adaptive echo cancellation algorithm. The CLMS algorithm utilizes the fact that the far-end signal is not correlated with a near-end signal. Accordingly, the residual error for the tap adaptation is relatively small, when compared to that of the conventional normalized LMS algorithm. To demonstrate the performance of the proposed algorithm, the DAC of hybrid system of the telephone network is considered. The simulation results show that the proposed algorithm can cancel the nonlinear echo signals effectively and show robustness under the double-talk situations.

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Fast Speaker Adaptation Based on Eigenspace-based MLLR Using Artificially Distorted Speech in Car Noise Environment (차량 잡음 환경에서 인위적 왜곡 음성을 이용한 Eigenspace-based MLLR에 기반한 고속 화자 적응)

  • Song, Hwa-Jeon;Jeon, Hyung-Bae;Kim, Hyung-Soon
    • Phonetics and Speech Sciences
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    • v.1 no.4
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    • pp.119-125
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    • 2009
  • This paper proposes fast speaker adaptation method using artificially distorted speech in telematics terminal under the car noise environment based on eigenspace-based maximum likelihood linear regression (ES-MLLR). The artificially distorted speech is built from adding the various car noise signals collected from a driving car to the speech signal collected from an idling car. Then, in every environment, the transformation matrix is estimated by ES-MLLR using the artificially distorted speech corresponding to the specific noise environment. In test mode, an online model is built by weighted sum of the environment transformation matrices depending on the driving condition. In 3k-word recognition task in the telematics terminal, we achieve a performance superior to ES-MLLR even using the adaptation data collected from the driving condition.

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