DIN EN ISO 16610-62:2021-11, Geometrische Produktspezifikation_(GPS)_- Filterung_- Teil_62: Lineare Flächenfilter: Spline-Filter (ISO/DIS_16610-62:2021); Deutsche und Englische Fassung prEN_ISO_16610-62:2021

2021 ◽  
Keyword(s):  
Spline Filter

Pipelined nonlinear spline filter for speech prediction

2021 ◽  
Vol 179 ◽  
pp. 108057
Author(s):  
Zhao Zhang ◽  
Sheng Zhang ◽  
Jiashu Zhang
Keyword(s):  
Spline Filter

scholarly journals A Synthetic Algorithm for Tracking a Moving Object in a Multiple-Dynamic Obstacles Environment Based on Kinematically Planar Redundant Manipulators

2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Hongzhe Jin ◽  
Hui Zhang ◽  
Zhangxing Liu ◽  
Decai Yang ◽  
Dongyang Bie ◽  
...  
Keyword(s):  
Real Time ◽  
Null Space ◽  
Inverse Kinematic ◽  
Moving Object ◽  
Redundant Manipulators ◽  
Joint Angles ◽  
The Real ◽  
Time Path ◽  
Planar Manipulators ◽  
Spline Filter

This paper presents a synthetic algorithm for tracking a moving object in a multiple-dynamic obstacles environment based on kinematically planar manipulators. By observing the motions of the object and obstacles, Spline filter associated with polynomial fitting is utilized to predict their moving paths for a period of time in the future. Several feasible paths for the manipulator in Cartesian space can be planned according to the predicted moving paths and the defined feasibility criterion. The shortest one among these feasible paths is selected as the optimized path. Then the real-time path along the optimized path is planned for the manipulator to track the moving object in real-time. To improve the convergence rate of tracking, a virtual controller based on PD controller is designed to adaptively adjust the real-time path. In the process of tracking, the null space of inverse kinematic and the local rotation coordinate method (LRCM) are utilized for the arms and the end-effector to avoid obstacles, respectively. Finally, the moving object in a multiple-dynamic obstacles environment is thus tracked via real-time updating the joint angles of manipulator according to the iterative method. Simulation results show that the proposed algorithm is feasible to track a moving object in a multiple-dynamic obstacles environment.

Comparison of Endpoint Data Treatment Methods for the Estimation of Kinematics and Kinetics Near Impact During the Tennis Serve

2012 ◽  
Vol 28 (1) ◽  
pp. 93-98 ◽  
Author(s):  
M. M. Reid ◽  
Amity C. Campbell ◽  
B. C. Elliott
Keyword(s):  
Upper Limb ◽  
Treatment Method ◽  
Biomechanical Analysis ◽  
Quintic Spline ◽  
Tennis Serve ◽  
Analysis System ◽  
Endpoint Data ◽  
Spline Filter ◽  
The Impact ◽  
Kinematics And Kinetics

Tennis stroke mechanics have attracted considerable biomechanical analysis, yet current filtering practice may lead to erroneous reporting of data near the impact of racket and ball. This research had three aims: (1) to identify the best method of estimating the displacement and velocity of the racket at impact during the tennis serve, (2) to demonstrate the effect of different methods on upper limb kinematics and kinetics and (3) to report the effect of increased noise on the most appropriate treatment method. The tennis serves of one tennis player, fit with upper limb and racket retro-reflective markers, were captured with a Vicon motion analysis system recording at 500 Hz. The raw racket tip marker displacement and velocity were used as criterion data to compare three different endpoint treatments and two different filters. The 2nd-order polynomial proved to be the least erroneous extrapolation technique and the quintic spline filter was the most appropriate filter. The previously performed “smoothing through impact” method, using a quintic spline filter, underestimated the racket velocity (9.1%) at the time of impact. The polynomial extrapolation method remained effective when noise was added to the marker trajectories.

The spline filter: A regularization approach for the Gaussian filter

2012 ◽  
Vol 36 (4) ◽  
pp. 586-592 ◽  
Author(s):  
Hao Zhang ◽  
Yibao Yuan ◽  
Weiying Piao
Keyword(s):  
Gaussian Filter ◽  
Spline Filter

scholarly journals Study the influence of selected new filtration methods on roughness of standard surfaces

Mechanik ◽  
2017 ◽  
Vol 90 (3) ◽  
pp. 224-228 ◽  
Author(s):  
Aneta Łętocha
Keyword(s):  
Contact Method ◽  
Gaussian Filter ◽  
Morphological Filters ◽  
Surface Parameters ◽  
Roughness Profile ◽  
Spline Filter ◽  
The Impact

Paper presents the results of research in order to determine the impact of selected new filtration methods on roughness results of standard surfaces – sinusoidal (C type) and random (D type). Three filtering methods were chosen: robust Gaussian filter, spline filter, morphological filters. Studies with use contact method and confocal profiling method (optical) were made. Results of selected height roughness profile and surface parameters were analysed.

Restoration of noisy blurred images by a smoothing spline filter

1977 ◽  
Vol 16 (12) ◽  
pp. 3147 ◽  
Author(s):  
M. J. Peyrovian ◽  
A. A. Sawchuk
Keyword(s):  
Smoothing Spline ◽  
Spline Filter ◽  
Blurred Images
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