Recursive Regularization Filters: Design, Properties, and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches
Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches
Digital Image Processing: PIKS Scientific Inside
Digital Image Processing: PIKS Scientific Inside
Digital Image Processing Using MATLAB: AND " Mathworks, MATLAB Sim SV 07 "
Digital Image Processing Using MATLAB: AND " Mathworks, MATLAB Sim SV 07 "
Signal Processing and Performance Analysis for Imaging Systems
Signal Processing and Performance Analysis for Imaging Systems
Robust filter design for uncertain systems defined by both hard andsoft bounds
IEEE Transactions on Signal Processing
A frequency domain approach to the problems ofH∞-minimum error state estimation anddeconvolution
IEEE Transactions on Signal Processing
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In this paper, a new deconvolution estimator design method is proposed to solve the problems caused by unknown input for a discrete time-varying linear system (DTVLS). These problems arise in cases of image restoration or geological exploration. Our proposed method modifies the state estimate error x(k)-x@^(k) of traditional performance measures to the input estimate error u(k)-u@^(k) to develop a deconvolution estimator via game theory in an H"~ setting. In this paper, unknown input is estimated using noisy measurements, and statistical information about the process and measurement noises is not necessarily required in an H"~ setting. The new deconvolution estimator yields an estimated input that is close to the actual input and that leads to improvements in terms of MSE and PSNR for performance.