On Efficiencey of Linear Estimators Under Heavy-Tailedness

2005 ◽  
Author(s):  
Rustam Ibragimov
Keyword(s):  
Linear Estimators

scholarly journals Blind Deblurring Based on Sigmoid Function

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3484
Author(s):  
Shuhan Sun ◽  
Lizhen Duan ◽  
Zhiyong Xu ◽  
Jianlin Zhang
Keyword(s):  
Performance Optimization ◽  
Degradation Process ◽  
Image Deconvolution ◽  
Sigmoid Function ◽  
Blind Image Deblurring ◽  
Linear Estimators ◽  
Blind Deblurring ◽  
Degraded Image ◽  
Excellent Property ◽  
Blind Image

Blind image deblurring, also known as blind image deconvolution, is a long-standing challenge in the field of image processing and low-level vision. To restore a clear version of a severely degraded image, this paper proposes a blind deblurring algorithm based on the sigmoid function, which constructs novel blind deblurring estimators for both the original image and the degradation process by exploring the excellent property of sigmoid function and considering image derivative constraints. Owing to these symmetric and non-linear estimators of low computation complexity, high-quality images can be obtained by the algorithm. The algorithm is also extended to image sequences. The sigmoid function enables the proposed algorithm to achieve state-of-the-art performance in various scenarios, including natural, text, face, and low-illumination images. Furthermore, the method can be extended naturally to non-uniform deblurring. Quantitative and qualitative experimental evaluations indicate that the algorithm can remove the blur effect and improve the image quality of actual and simulated images. Finally, the use of sigmoid function provides a new approach to algorithm performance optimization in the field of image restoration.

scholarly journals Optimal Linear Estimators for Time-Delay Systems with Fading Measurements and Correlated Noises

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Yazhou Li ◽  
Jiayi Li ◽  
Xin Wang
Keyword(s):  
Time Delay ◽  
Minimum Variance ◽  
Delay Systems ◽  
Multiplicative Noises ◽  
Linear Estimators ◽  
Discrete Linear Systems ◽  
Estimation Problems ◽  
Optimal Linear ◽  
State Augmentation ◽  
Correlated Noises

The optimal linear estimation problems are investigated in this paper for a class of discrete linear systems with fading measurements and correlated noises. Firstly, the fading measurements occur in a random way where the fading probabilities are regulated by probability mass functions in a given interval. Furthermore, time-delay exists in the system state and observation simultaneously. Additionally, the multiplicative noises are considered to describe the uncertainty of the state. Based on the projection theory, the linear minimum variance optimal linear estimators, including filter, predictor, and smoother are presented in the paper. Compared with conventional state augmentation, the new algorithm is finite-dimensionally computable and does not increase computational and storage load when the delay is large. A numerical example is provided to illustrate the effectiveness of the proposed algorithms.

Reduced Order Modeling and Direct Parameter Identification for a Complex Parallel Robot

2008 ◽  
Author(s):  
Jens Kroneis ◽  
Peter Mu¨ller ◽  
Steven Liu
Keyword(s):  
Parameter Identification ◽  
Parallel Robot ◽  
Parallel Robots ◽  
Minimal Form ◽  
Linear Estimators ◽  
New Strategy ◽  
Reduction Methods ◽  
Verification Process ◽  
Dynamical Description ◽  
Solid Edge

In this paper a new strategy for dynamic modeling and parameter identification of complex parallel robots including parallel crank mechanisms is presented. Based on a model reduction strategy motivated by the structure of the parallel robot SpiderMill, kinematics and dynamics are derived in a compact form by applying the modified Denavit-Hartenberg method and the Newton-Euler approach. The obtained parameter-linear dynamical description is reduced to a parameter-minimal form using analytical and numerical reduction methods. Rigid body parameters of the model are identified using optimized trajectories and linear estimators. Through the whole modeling and verification process MSC.ADAMS and Solid Edge models of the demonstrator SpiderMill are used.

A note on the inefficiency of non-linear estimators

1985 ◽  
Vol 17 (4) ◽  
pp. 347-350 ◽  
Author(s):  
Keith Hylton
Keyword(s):  
Linear Estimators ◽  
Non Linear
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