• Title/Summary/Keyword: minimum mean square error

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BER Performance Analysis of VBLAST Detection over an Underwater Acoustic MIMO Channel (수중음향 MIMO 채널에서 VBLAST 검파방식의 성능분석)

  • Kang, Heehoon
    • Journal of the Institute of Electronics and Information Engineers
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    • v.53 no.8
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    • pp.145-149
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    • 2016
  • For obtaining high speed data rate, underwater acoustic communication has several problems by the different environmental problem. To achieve high speed data rate, a method of multiple antennas have been researched. V-BLAST Algorithm is a detection method applied to terrestrial wireless communications. In this paper, BER performance of VBLAST detection for MIMO system is analyzed in the paper.

Speech Enhancement Using Microphone Array with MMSE-STSA Estimator Based Post-Processing (MMSE-STSA 추정치에 기반한 후처리를 갖는 마이크로폰 배열을 이용한 음성 개선)

  • Kwon Hong Seok;Son Jong Mok;Bae Keun Sung
    • Proceedings of the KSPS conference
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    • 2002.11a
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    • pp.187-190
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    • 2002
  • In this paper, a speech enhancement system using microphone array with MMSE-STSA (Minimum Mean Square Error-Short Time Spectral Amplitude) estimator based post-processing is proposed. Speech enhancement is first carried out by conventional delay-and-sum beamforming (DSB). A new MMSE-STSA estimator is then obtained by refining MMSE-STSA estimators from each microphone, which is applied to the output of conventional DSB to obtain additional speech enhancement. Computer simulation for white and pink noises show that the proposed system is superior to other approaches.

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On the algorithm of constructing the model-based optimal sample (모형에 기초한 표본추출방법의 알고리듬)

  • 강명욱;김영일
    • The Korean Journal of Applied Statistics
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    • v.10 no.2
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    • pp.253-260
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    • 1997
  • Various algorithms are investigated with respect to finding the best model-based samples according to criteria such as D-optimality and minimum mean square error. These two criteria are slightly different, but related to each other. Therefore, it is not surprising that these two are producing the almost identical samples. Some simple examples follow and critiques are provided along with directions for further research.

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Problems of Special Causes in Feedback Adjustment

  • Lee, Jae-June;Cho, Sin-Sup
    • Journal of Korean Society for Quality Management
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    • v.32 no.2
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    • pp.201-211
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    • 2004
  • Process adjustment is a complimentary tool to process monitoring in process control. Process adjustment directs on maintaining a process output close to a target value by manipulating another controllable variable, by which significant process improvement can be achieved. Therefore, this approach can be applied to the 'Improve' stage of Six Sigma strategy. Though the optimal control rule minimizes process variability in general, it may not properly function when special causes occur in underlying process, resulting in off-target bias and increased variability in the adjusted output process, possibly for long periods. In this paper, we consider a responsive feedback control system and the minimum mean square error control rule. The bias in the adjusted output process is investigated in a general framework, especially focussing on stationary underlying process and the special cause of level shift type. Illustrative examples are employed to illustrate the issues discussed.

Adaptive Noise Smoothing Algorithm Based on Nonstationary Correlation Assumption (영상의 비정적 상관관계 가정에 근거한 적응적 잡음제거 알고리즘)

  • 박성철;강문기
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2001.11b
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    • pp.129-133
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    • 2001
  • 영상에 포함된 잡음은 화질 및 영상의 압축효율을 저하시킨다. 최근 들어, 영상의 에지 성분을 효율적으로 고려하면서 잡음을 제거하기 위하여 다양한 비정적(nonstationary) 영상 모델에 근거한 잡음제거 알고리즘이 제안되어 왔다. 하지만, 기존의 비정적 영상모델에서는 연산량의 부담을 덜기 위하여 각 화소들 사이에 상관관계(correlation)가 없다는 가정을 하고 있어 영상의 미세한 정보들이 필터링에 의하여 훼손된다. 본 논문에서는 영상의 비정적 상관관계를 고려한 적응적 잡음제거 알고리즘을 제시한다. 영상신호는 비정적 평균을 가진다고 가정되며, 또한 각기 다른 정적(stationary) 상관관계를 가지는 부분 영상으로 분리된다고 가정된다. 제안된 영상 모델에서의 공분산(co-variance) 행렬의 특수한 구조를 이용하여 계산적으로 효율적인 FFT에 기반한 선형 minimum mean square error 필터를 유도한다. 제안된 영상 모델의 정당성 및 알고리즘의 효율성을 제시한다.

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Performance of Adaptive Equalizer with Switching Methods for SC-FDMA in Uplink of 3GPP-LTE System (3GPP-LTE 시스템의 상향링크 기술인 SC-FDMA을 위한 적응형 스위칭 등화기법)

  • Koo, Sung-Wan;Bae, Jung-Nam;Kim, Jun-Young
    • Proceedings of the KAIS Fall Conference
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    • 2009.12a
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    • pp.985-988
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    • 2009
  • 본 논문에서는 3GPP-LTE 상향링크 기술인 SC-FDMA에서 적응형 등화기 성능에 대해 알아보았다. SC-FDMA의 등화기에서 계산량을 줄여 효율성을 높이는 방법으로 ZF(Zero Forcing)과 MMSE(Minimum Mean Square Error)를 이용한 스위칭 기법을 제안하고, 제안한 시스템에서의 성능을 비교 분석하고자 한다. 제안한 스위칭 기법을 사용함으로써 SNR이 낮을 때는 MMSE를 이용하여 잡음에 대한 영향을 최소화 시켜주고, SNR이 높을 때는 ZF을 써서 상대적으로 복잡도가 적은 등화 기법을 통해 전체적인 시스템 복잡도를 줄여 효율성을 높이고자 한다.

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Relay Selection Based on Rank-One Decomposition of MSE Matrix in Multi-Relay Networks

  • Bae, Young-Taek;Lee, Jung-Woo
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2010.07a
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    • pp.9-11
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    • 2010
  • Multiple-input multiple-output (MIMO) systems assisted by multi-relays with single antenna are considered. Signal transmission consists of two hops. In the first hop, the source node broadcasts the vector symbols to all relays, then all relays forward the received signals multiplied by each power gain to the destination simultaneously. Unlike the case of full cooperation between relays such as single relay with multiple antennas, in our case there is no closed form solution for optimal relay power gain with respect to minimum mean square error (MMSE). Thus we propose an alternative approach in which we use an approximation of the cost function based on rank-one matrix decomposition. As a cost function, we choose the trace of MSE matrix. We give several simulation results to validate that our proposed method obtains a negligible performance loss compared to optimal solution obtained by exhaustive search.

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Image Restoration in Dual Energy Digital Radiography using Wiener Filtering Method

  • Min, Byoung-Goo;Park, Kwang-Suk
    • Journal of Biomedical Engineering Research
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    • v.8 no.2
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    • pp.171-176
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    • 1987
  • Wiener filtering method was applied to the dual energy imaging procedure in digital radiography(D.R.). A linear scanning photodiode arrays with 1024 elements(0.6mm H 1.3mm pixel size) were used to obtain chest images in 0.7 sec. For high energy image acquisition, X-ray tube was set at 140KVp, 100mA with a rare-earth phosphor screen. Low energy image was obtained with X-ray tube setting at 70KVp, 150mA. These measured dual energy images are represented in the vector matrix notation as a linear discrete model including the additive random noise. Then, the object images are restored in the minimum mean square error sense using Wiener filtering method in the transformed domain. These restored high and low energy images are used for computation of the basis image decomposition. Then the basis images are linearly combined to produce bone or tissue selective images. Using this process, we could improve the signal to noise ratio characteristics in the material selective images.

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Modified MMSE Estimator based on Non-Linearly Spaced Pilots for OFDM Systems

  • Khan, Latif Ullah
    • IEIE Transactions on Smart Processing and Computing
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    • v.3 no.1
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    • pp.35-39
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    • 2014
  • This paper proposes a Modified Minimum Mean Square Error (M-MMSE) estimator for an Orthogonal Frequency Division Multiplexing (OFDM) System over fast fading Rayleigh channel. The proposed M-MMSE estimator considered the effects of the efficient placement of pilots based on the channel energy distribution. The pilot symbols were placed in a non-linear manner according to the density of the channel energy. Comparative analysis of the MMSE estimator for a comb-type pilot arrangement and M-MMSE estimator for the proposed pilot insertion scheme revealed significant performance improvement of the M-MMSE estimator over the MMSE estimator.

Speech Processing System Using a Noise Reduction Neural Network Based on FFT Spectrums

  • Choi, Jae-Seung
    • Journal of information and communication convergence engineering
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    • v.10 no.2
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    • pp.162-167
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    • 2012
  • This paper proposes a speech processing system based on a model of the human auditory system and a noise reduction neural network with fast Fourier transform (FFT) amplitude and phase spectrums for noise reduction under background noise environments. The proposed system reduces noise signals by using the proposed neural network based on FFT amplitude spectrums and phase spectrums, then implements auditory processing frame by frame after detecting voiced and transitional sections for each frame. The results of the proposed system are compared with the results of a conventional spectral subtraction method and minimum mean-square error log-spectral amplitude estimator at different noise levels. The effectiveness of the proposed system is experimentally confirmed based on measuring the signal-to-noise ratio (SNR). In this experiment, the maximal improvement in the output SNR values with the proposed method is approximately 11.5 dB better for car noise, and 11.0 dB better for street noise, when compared with a conventional spectral subtraction method.