• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.559-562
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• 2011

In this research, We derived Recursive Least Squares(RLS) algorithm with adaptive maximum-likelihood channel estimate for digital pulse amplitude modulated sequence in the presence of intersymbol interference and additive white Gaussian noise. RLS algorithms have better convergence characteristics than conventional algorithms, LMS (Least Mean Squares) algorithms.

• Journal of Broadcast Engineering
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• v.21 no.6
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• pp.920-928
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• 2016

Recently high dynamic range imaging technique is hot issue in computer graphic area. We present a progressive tone mapping algorithm, which is based on weighted least squares optimization framework. Our approach combines weighted least squares filtering with iCAM06 model. To show more perceptual high dynamic range images in conventional display, we decompose high dynamic range image into base layers and detail layers. The base layers are obtained by using weighted least squares filter. Then, we adopt chromatic adaption function and non-linear compression function to deal with base layers. Only the base layers reduce contrast, and preserving detail. The image quality assessment shows that our tone mapped image is more similar to original high dynamic range image. Moreover, the subjective result shows our algorithm produces more reliable and pleasing image.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.240-240
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• 2000

This paper presents two algorithms based on the concept of the frequency domain adaptive filter(FDAF). First the frequency domain recursive least squares(FRLS) algorithm with the overlap-save filtering technique is introduced. This minimizes the sum of exponentially weighted square errors in the frequency domain. To eliminate discrepancies between the linear convolution and the circular convolution, the overlap-save method is utilized. Second, the sliding method of data blocks is studied Co overcome processing delays and complexity roads of the FRLS algorithm. The size of the extended data block is twice as long as the filter tap length. It is possible to slide the data block variously by the adjustable hopping index. By selecting the hopping index appropriately, we can take a trade-off between the convergence rate and the computational complexity. When the input signal is highly correlated and the length of the target FIR filter is huge, the FRLS algorithm based on the block processing technique has good performances in the convergence rate and the computational complexity.