• Title/Summary/Keyword: Adaptive weight

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Design and Performance Analysis of Adaptive First-Order Decimator Using Local Intelligibility (국부 가해성을 이용한 적응형 선형 축소기의 설계 및 성능 분석)

  • Kwak, No-Yoon
    • Journal of Digital Contents Society
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    • v.9 no.1
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    • pp.17-26
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    • 2008
  • This paper has for its object to propose AFOD(Adaptive First-Order Decimator) which sets a value of decimated element as an average of a value of neighbor intelligible component and a output value of FOD(First-Order Decimator) for the target pixel, and to analyze its performance in terms of subjective image quality and hardware complexity. In the proposed AFOD, a target pixel located at the center of sliding window is selected first, then the gradient amplitudes of its right neighbor pixel and its lower neighbor pixel are calculated using first order derivative operator respectively. Secondly, each gradient amplitude is divided by the summation result of two gradient amplitudes to generate each local intelligible weight. Next, a value of neighbor intelligible component is defined by adding a value of the right neighbor pixel times its local intelligible weight to a value of the lower neighbor pixel times its intelligible weight. Since the proposed method adaptively reflects neighbor intelligible informations of neighbor pixels on the decimated element according to each local intelligible weight, it can effectively suppress the blurring effect being the demerit of FOD. It also possesses the advantages that it can keep the merits of FOD with the good results on average but also lower computational cost.

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FLIR and CCD Image Fusion Algorithm Based on Adaptive Weight for Target Extraction (표적 추출을 위한 적응적 가중치 기반 FLIR 및 CCD 센서 영상 융합 알고리즘)

  • Gu, Eun-Hye;Lee, Eun-Young;Kim, Se-Yun;Cho, Woon-Ho;Kim, Hee-Soo;Park, Kil-Houm
    • Journal of Korea Multimedia Society
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    • v.15 no.3
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    • pp.291-298
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    • 2012
  • In automatic target recognition(ATR) systems, target extraction techniques are very important because ATR performance depends on segmentation result. So, this paper proposes a multi-sensor image fusion method based on adaptive weights. To incorporate the FLIR image and CCD image, we used information such as the bi-modality, distance and texture. A weight of the FLIR image is derived from the bi-modality and distance measure. For the weight of CCD image, the information that the target's texture is more uniform than the background region is used. The proposed algorithm is applied to many images and its performance is compared with the segmentation result using the single image. Experimental results show that the proposed method has the accurate extraction performance.

Medical Image Enhancement Using an Adaptive Weight and Threshold Values (적응적 가중치와 문턱치를 이용한 의료영상의 화질 향상)

  • Kim, Seung-Jong
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.12 no.5
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    • pp.205-211
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    • 2012
  • By using an adaptive threshold and weight based on the wavelet transform and Haar transform, a novel image enhancement algorithm is proposed. First, a medical image was decomposed with wavelet transform and all high-frequency sub-images were decomposed with Haar transform. Secondly, noise in the frequency domain was reduced by the proposed soft-threshold method. Thirdly, high-frequency coefficients were enhanced by the proposed weight values in different sub-images. Then, the enhanced image was obtained through the inverse Haar transform and wavelet transform. But the pixel range of the enhanced image is narrower than a normal image. Lastly, the image's histogram was stretched by nonlinear histogram equalization. Experiments showed that the proposed method can be not only enhance an image's details but can also preserve its edge features effectively.

Analysis of DOA Estimation and Adaptive Beam-forming of MIMO between Linear-circular Array Antennas (선형-원형배열 안테나에 따른 MIMO의 DOA 추정과 적응 빔성형 분석)

  • Yang, Doo-Yeong;Lee, Min-Soo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.6
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    • pp.2777-2784
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    • 2011
  • In this paper, DOA(direction of arrival) of multiple incident signals received from linear array antenna and circular array antenna, which is based on nonparametric estimation algorithm, and adaptive beam-forming algorithm are studied and analyzed. In nonparametric estimation algorithm, we minimize a regularized objective function for finding a estimate of the signal energy as a function of angle, using nonquadratic norm which leads to supper resolution and noise suppression. And then, DOA is estimated by the signal and noise spatial steering vector, and adaptive beam-forming pattern is improved by weight vectors obtained from the spatial vector. Especially, the discrimination ability of DOA and the adaptive beam-forming ability according to antenna array methods and the number of array elements are compared and considered.

An Adaptive Decision Feedback Equalizer for Underwater Acoustic Communications (수중음향통신을 위한 적응 결정궤환 등화기)

  • Choi, Young-Chol;Park, Jong-Won;Lim, Yong-Kon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.4
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    • pp.645-651
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    • 2009
  • In this paper, we present bit error rate(BER) performance of an adaptive decision feedback equalizer(DFE) using experimental data. The experiment was performed at the shore of Geoje in November 2007. The BER of the adaptive DFE whose tap weight is updated by RLS is described with change of feedforward filter length, feedback filter length, training sequence length, and delay, which shows that the uncoded average BER is $4{\times}10^2\;and\;1.5{\times}10^{-2}$ with transmission range of 9.7km and 4km, respectively. The BER of the adaptive DFE can be lower than 10-3 by a forward error correction code and therefore the adaptive DFE may be a good candidate for a high speed AUV communications since the volume and weight of the underwater acoustic modem should be small because of the restricted space and power in the battery-operated AUV.

Blind Adaptive Receiver based on Constant Modulus for Downlink MC-CDMA Systems (하향링크 MC-CDMA 시스템을 위한 CM 기반의 블라인드 적응 수신기)

  • Seo, Bangwon
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.5
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    • pp.47-54
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    • 2019
  • In this paper, we consider a constant modulus (CM) based blind adaptive receiver design for downlink multi-carrier code-division multiple access (MC-CDMA) systems employing simple space-time block coding (STBC). In the paper, filter weight vectors used for the detection of the transmitted symbols are partitioned into its subvectors and then, special relations among the optimal subvectors minimizing the CM metric are derived. Using the special relations, we present a modified CM metric and propose a new blind adaptive stochastic-gradient CM algorithm (SG-CMA) by minimizing the modified CM metric. The proposed blind adaptive SG-CMA has faster convergence rate than the conventional SG-CMA because the filter weight vectors of the proposed scheme are updated in the region of satisfying the derived special relations. Computer simulation results are given to verify the superiority of the proposed SG-CMA.

A Study on Adaptive Pattern Null Synthesis for Active Phased Array Antenna (능동위상배열안테나의 적응형 패턴 널 형성에 관한 연구)

  • Jung, Jin-Woo;Park, Sung-Il
    • The Journal of the Korea institute of electronic communication sciences
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    • v.16 no.3
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    • pp.407-416
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    • 2021
  • An active phased array antennas can not only electrically steer the beam by controlling the weighting of the excitation signal, but can also form a pattern null in the direction of the interference source. The weight of the excitation signal to steer the main beam can be easily calculated based on the position of the radiating element. In addition, the weight of the excited signal for pattern null formation can also be calculated by setting the required radiation pattern and using WLSM(Weighted Least Squares Method). However, in a general wireless communication network environment, the location of the interference source is unknown. Therefore, an adaptive pattern null synthesis is needed. In this paper, it was confirmed that pattern null synthesis according to the required radiation characteristic was possible. And based on this, adaptive pattern null synthesis into the direction of an interference source was studied using a binary search algorithm based on observation area. As a result of conducting a simulation based on the presented technique, it was confirmed that adaptive pattern null forming into the direction of an interference is possible in efficient way.

Blind adaptive receiver for uplink multiuser massive MIMO systems

  • Shin, Joonwoo;Seo, Bangwon
    • ETRI Journal
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    • v.42 no.1
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    • pp.26-35
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    • 2020
  • Herein, we consider uplink multiuser massive multiple-input multiple-output systems when multiple users transmit information symbols to a base station (BS) by applying simple space-time block coding (STBC). At the BS receiver, two detection filters for each user are used to detect the STBC information symbols. One of these filters is for odd-indexed symbols and the other for even-indexed symbols. Using constrained output variance metric minimization, we first derive a special relation between the closed-form optimal solutions for the two detection filters. Then, using the derived special relation, we propose a new blind adaptive algorithm for implementing the minimum output variance-based optimal filters. In the proposed adaptive algorithm, filter weight vectors are updated only in the region satisfying the special relation. Through a theoretical analysis of the convergence speed and a computer simulation, we demonstrate that the proposed scheme exhibits faster convergence speed and lower steady-state bit error rate than the conventional scheme.

Spatially Adaptive Image Fusion Based on Local Spectral Correlation (지역적 스펙트럼 상호유사성에 기반한 공간 적응적 영상 융합)

  • 김성환;박종현;강문기
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.2343-2346
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    • 2003
  • The spatial resolution of multispectral images can be improved by merging them with higher resolution image data. A fundamental problem frequently occurred in existing fusion processes, is the distortion of spectral information. This paper presents a spatially adaptive image fusion algorithm which produces visually natural images and retains the quality of local spectral information as well. High frequency information of the high resolution image to be inserted to the resampled multispectral images is controlled by adaptive gains to incorporate the difference of local spectral characteristics between the high and the low resolution images into the fusion. Each gain is estimated to minimize the l$_2$-norm of the error between the original and the estimated pixel values defined in a spatially adaptive window of which the weight are proportional to the spectral correlation measurements of the corresponding regions. This method is applied to a set of co-registered Landsat7 ETM+ panchromatic and multispectral image data.

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Adaptive High-Order Neural Network Control of Induction Servomotor System (유도기 서보모터 시스템의 적응 고차 신경망 제어)

  • Kim, Do-Woo;Chung, Ki-Chull;Lee, Seng-Hak
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.54 no.11
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    • pp.650-653
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    • 2005
  • In this paper, adaptive high-order neural network controller(AHONNC) is adopted to control an induction servomotor. A algorithm is developed by combining compensation control and high-order neural networks. Moreover, an adaptive bound estimation algorithm was proposed to estimate the bound of approximation error. The weight of the high-order neural network can be online tuned in the sense of the Lyapunov stability theorem; thus, the stability of the closed-loop system can be guaranteed. Simulation results for induction servomotor drive system are shown to confirm the validity of the proposed controller.