• Title/Summary/Keyword: Robust filtering

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H Filtering for a Class of Nonlinear Systems with Interval Time-varying Delay (구간시변 지연을 가지는 비선형시스템의 H 필터링)

  • Lee, Sangmoon;Liu, Yajuan
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.63 no.4
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    • pp.502-508
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    • 2014
  • In this paper, a delay-dependent $H_{\infty}$ filtering problem is investigated for discrete-time delayed nonlinear systems which include a more general sector nonlinear function instead of employing the commonly used Lipschitz-type function. By using the Lyapunov-Krasovskii functional approach, a less conservative sufficient condition is established for the existence of the desired filter, and then, the corresponding solvability condition guarantee the stability of the filter with a prescribed $H_{\infty}$ performance level. Finally, two simulation examples are given to show the effectiveness of the proposed filtering scheme.

Speech Recognition in Noisy Environments using Wiener Filtering (Wiener Filtering을 이용한 잡음환경에서의 음성인식)

  • Kim, Jin-Young;Eom, Ki-Wan;Choi, Hong-Sub
    • Speech Sciences
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    • v.1
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    • pp.277-283
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    • 1997
  • In this paper, we present a robust recognition algorithm based on the Wiener filtering method as a research tool to develop the Korean Speech recognition system. We especially used Wiener filtering method in cepstrum-domain, because the method in frequency-domain is computationally expensive and complex. Evaluation of the effectiveness of this method has been conducted in speaker-independent isolated Korean digit recognition tasks using discrete HMM speech recognition systems. In these tasks, we used 12th order weighted cepstral as a feature vector and added computer simulated white gaussian noise of different levels to clean speech signals for recognition experiments under noisy conditions. Experimental results show that the presented algorithm can provide an improvement in recognition of as much as from $5\%\;to\;\20\%$ in comparison to spectral subtraction method.

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Selective pole filtering based feature normalization for performance improvement of short utterance recognition in noisy environments (잡음 환경에서 짧은 발화 인식 성능 향상을 위한 선택적 극점 필터링 기반의 특징 정규화)

  • Choi, Bo Kyeong;Ban, Sung Min;Kim, Hyung Soon
    • Phonetics and Speech Sciences
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    • v.9 no.2
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    • pp.103-110
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    • 2017
  • The pole filtering concept has been successfully applied to cepstral feature normalization techniques for noise-robust speech recognition. In this paper, it is proposed to apply the pole filtering selectively only to the speech intervals, in order to further improve the recognition performance for short utterances in noisy environments. Experimental results on AURORA 2 task with clean-condition training show that the proposed selectively pole-filtered cepstral mean normalization (SPFCMN) and selectively pole-filtered cepstral mean and variance normalization (SPFCMVN) yield error rate reduction of 38.6% and 45.8%, respectively, compared to the baseline system.

A Krein Space Approach for Robust Extended Kalman Filtering on Mobile Robots in the Presence of Uncertainties

  • Jin, Seung-Hee;Park, Jin-Bae
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1771-1776
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    • 2003
  • In mobile robot navigation, one of the key problems is the pose estimation of the mobile robot. Although the odometry can be used to describe the motions of the mobile robots quite simple and accurately, the validities of the models are limited by a number of error sources contaminating the encoder outputs so that applying the conventional extended Kalman filter to these nominal model does not yield the satisfactory performance. As a remedy for this problem, we consider the uncertain nonlinear kinematic model of the mobile robot that contains the norm bounded uncertainties and also propose a new robust extended Kalman filter based on the Krein space approach. The proposed robust filter has the same recursive structure as the conventional extended Kalman filter and can hence be readily designed to effectively account for the uncertainties. The computer simulations will be given to verify the robustness against the parameter variation as well as the reliable performance of the proposed robust filter.

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Robust Kalman Filter Design in Indefinite inner product space (부정내적공간에서의 강인칼만필터 설계)

  • Lee, Tae-Hoon;Yoon, Tae-Sung;Park, Jin-Bae
    • Proceedings of the KIEE Conference
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    • 2002.11c
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    • pp.104-109
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    • 2002
  • A new robust Kalman filter is designed for the linear discrete-time system with norm-bounded parametric uncertainties. Sum quadratic constraint, which describes the uncertainties of the system, is converted into an indefinite quadratic form to be minimized in indefinite inner product space. This minimization problem is solved by the new robust Kalman filter. Since the new filter is obtained by simply modifying the conventional Kalman filter, robust filtering scheme can be more readily designed using the proposed method in comparison with the existing robust Kalman filters. A numerical example demonstrates the robustness and the improvement of the proposed filter compared with the existing filters.

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Design of Incoming Ballistic Missile Tracking Systems Using Extended Robust Kalman Filter (확장 강인 칼만 필터를 이용한 접근 탄도 미사일 추적 시스템 설계)

  • 이현석;나원상;진승희;윤태성;박진배
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.188-188
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    • 2000
  • The most important problem in target tracking can be said to be modeling the tracking system correctly. Although the simple linear dynamic equation for this model has used until now, the satisfactory performance could not be obtained owing to uncertainties of the real systems in the case of designing the filters baged on the dynamic equations. In this paper, we propose the extended robust Kalman filter (ERKF) which can be applied to the real target tracking system with the parameter uncertainties. A nonlinear dynamic equation with parameter uncertainties is used to express the uncertain system model mathematically, and a measurement equation is represented by a nonlinear equation to show data from the radar in a Cartesian coordinate frame. To solve the robust nonlinear filtering problem, we derive the extended robust Kalman filter equation using the Krein space approach and sum quadratic constraint. We show the proposed filter has better performance than the existing extended Kalman filter (EKF) via 3-dimensional target tracking example.

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A Synchronization Scheme Based on Moving Average for Robust Audio Watermarking

  • Zhang, Jinquan;Han, Bin
    • Journal of Information Processing Systems
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    • v.15 no.2
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    • pp.271-287
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    • 2019
  • The synchronization scheme based on moving average is robust and suitable for the same rule to be adopted in embedding watermark and synchronization code, but the imperceptibility and search efficiency is seldom reported. The study aims to improve the original scheme for robust audio watermarking. Firstly, the survival of the algorithm from desynchronization attacks is improved. Secondly, the scheme is improved in inaudibility. Objective difference grade (ODG) of the marked audio is significantly changed. Thirdly, the imperceptibility of the scheme is analyzed and the derived result is close to experimental result. Fourthly, the selection of parameters is optimized based on experimental data. Fifthly, the search efficiency of the scheme is compared with those of other synchronization code schemes. The experimental results show that the proposed watermarking scheme allows the high audio quality and is robust to common attacks such as additive white Gaussian noise, requantization, resampling, low-pass filtering, random cropping, MP3 compression, jitter attack, and time scale modification. Moreover, the algorithm has the high search efficiency and low false alarm rate.

Improved Collaborative Filtering Using Entropy Weighting

  • Kwon, Hyeong-Joon
    • International Journal of Advanced Culture Technology
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    • v.1 no.2
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    • pp.1-6
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    • 2013
  • In this paper, we evaluate performance of existing similarity measurement metric and propose a novel method using user's preferences information entropy to reduce MAE in memory-based collaborative recommender systems. The proposed method applies a similarity of individual inclination to traditional similarity measurement methods. We experiment on various similarity metrics under different conditions, which include an amount of data and significance weighting from n/10 to n/60, to verify the proposed method. As a result, we confirm the proposed method is robust and efficient from the viewpoint of a sparse data set, applying existing various similarity measurement methods and Significance Weighting.

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Nonlinear Echo Cancellation using an ECLMS Algorithm (ECLMS 알고리즘을 이용한 비선형 반향신호 제거)

  • Nam, Sang-Won;Kim, Byoung-Soo
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.54 no.10
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    • pp.639-642
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    • 2005
  • In this paper, a robust nonlinear echo cancellation is proposed, where a third-order adaptive Volterra filtering is employed along with an expanded correlation LMS (ECLMS) algorithm to compensate for nonlinear distortion in the echo path. (e.g., DAC of the hybrid network). Finally, the robustness in the echo cancellation of the proposed approach is demonstrated using computer simulations, where high attenuation of echo signals is achieved even in the double-talk situation (e.n., BdB improvement in ERLE).

A ROBUST WATERMARKING METHOD BASED ON HVS (HVS 기반 워터마킹에서 외부 공격에 강인한 방법에 관한 연구)

  • 심상흔;정용주;강호경;노용만
    • Proceedings of the IEEK Conference
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    • 2001.06d
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    • pp.73-76
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    • 2001
  • In this paper, we utilize a HVS(Human Visual System) watermarking method where watermarks are embedded in a DFT domain. The HVS watermarking method is robust for attacks like JPEC, filtering, noise, etc. But, when images are attacked by basic geometric attacks as cropping, scaling, rotation, a watermarks may not be detected. In this paper, we introduce the HVS watermarking method that inserts references In a domain of LSB(Least Significant Bit) of image. Experimental results show that the proposed method based on HVS watermarking method gives more robustness to the basic geometric attacks compared with original HVS watermarking methods.

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