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NONPARAMETRIC IDENTIFICATION OF MISO HAMMERSTEIN SYSTEM FROM STRUCTURED DATA

Journal of Systems Science and Systems Engineering 2015年第1期24卷 68-80页

作者： pawel wachel Przemyslaw liwiński Zygmunt Hasiewicz Department of Control Systems and Mechatronics Wroclaw University of Technology

The problem of nonparametric identification of a multivariate nonlinearity in a D-input Hammer- stein system is examined. It is demonstrated that if the input measurements are structured, in the sense that there exists some hidden relation between them, i.e. if they are distributed on some （unknown） d-dimensional space M in IRD, d 〈 D, then the system nonlinearity can be recovered at points on M with the convergence rate O（n-1/（2＋d）） dependent on d. This rate is thus faster than the generic rate O（n-1/（2＋D）） achieved by typical nonparametric algorithms and controlled solely by the number of inputs D.

关键词： MISO Hammerstein system nonparametric system identification structured data conver-gence rate

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A Simple Model for On-Sensor Phase-Detection Autofocusing Algorithm

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Journal of Computer and Communications 2013年第6期1卷 11-17页

作者： Przemyslaw Sliwinski pawel wachel Institute of Computer Engineering Control and RoboticsWroclaw University of TechnologyWroclawPoland

A simple model of the phase-detection autofocus device based on the partially masked sensor pixels is described. The cross-correlation function of the half-images registered by the masked pixels is proposed as a focus function. It is shown that—in such setting—focusing is equivalent to searching of the cross-correlation function maximum. Application of stochastic approximation algorithms to unimodal and non-unimodal focus functions is shortly discussed.

关键词： Phase Detection Autofocus On-Sensor Circuit Formal Model Cross-Correlation Stochastic Approximation

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Efficiency Analysis of the Autofocusing Algorithm Based on Orthogonal Transforms

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Journal of Computer and Communications 2013年第6期1卷 41-45页

作者： Przemyslaw Sliwinski Krzysztof Berezowski Piotr Patronik pawel wachel Institute of Computer Engineering Control and RoboticsWroclaw University of TechnologyWroclawPoland

Efficiency of the autofocusing algorithm implementations based on various orthogonal transforms is examined. The algorithm uses the variance of an image acquired by a sensor as a focus function. To compute the estimate of the variance we exploit the equivalence between that estimate and the image orthogonal expansion. Energy consumption of three implementations exploiting either of the following fast orthogonal transforms: the discrete cosine, the Walsh-Hadamard, and the Haar wavelet one, is evaluated and compared. Furthermore, it is conjectured that the computation precision can considerably be reduced if the image is heavily corrupted by the noise, and a simple problem of optimal word bit-length selection with respect to the signal variance is analyzed.

关键词： Auto-Focusing Image Variance Discrete Orthogonal Transforms Word-Length Selection Architectural Performance Evaluation

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