Optimal linear filter for self-tuning application

1985 ◽  
Author(s):  
M. Grimble
Keyword(s):  
Linear Filter ◽  
Optimal Linear ◽  
Self Tuning

RF tomography based optimal linear filter

2017 ◽  
Author(s):  
Muftah Akroush ◽  
Michael C. Wicks ◽  
Hamdi Abdelbagi ◽  
Turki Alanazi ◽  
Abdunaser Abdusamad ◽  
...  
Keyword(s):  
Linear Filter ◽  
Optimal Linear

Optimal Linear Filter for Multi-rate Singular System

2014 ◽  
Author(s):  
Hao Jin ◽  
Jing Ma ◽  
Yun Li ◽  
Ming Zhao
Keyword(s):  
Singular System ◽  
Linear Filter ◽  
Optimal Linear

Optimal Linear Filter for Multi-rate System

2014 ◽  
Author(s):  
Jing Ma ◽  
Hao Jin ◽  
Tian Tian ◽  
Wei Zhang
Keyword(s):  
Linear Filter ◽  
Rate System ◽  
Optimal Linear

scholarly journals Dynamics of Smooth Pursuit Maintenance

2009 ◽  
Vol 102 (1) ◽  
pp. 110-118 ◽  
Author(s):  
Abtine Tavassoli ◽  
Dario L. Ringach
Keyword(s):  
Visual Tracking ◽  
Smooth Pursuit ◽  
Moving Objects ◽  
Good Accuracy ◽  
Visual Target ◽  
Target Velocity ◽  
Linear Filter ◽  
Optimal Linear ◽  
Eye Velocity ◽  
Effective Integration

Smooth pursuit eye movements allow the approximate stabilization of a moving visual target on the retina. To study the dynamics of smooth pursuit, we measured eye velocity during the visual tracking of a Gabor target moving at a constant velocity plus a noisy perturbation term. The optimal linear filter linking fluctuations in target velocity to evoked fluctuations in eye velocity was computed. These filters predicted eye velocity to novel stimuli in the 0- to 15-Hz band with good accuracy, showing that pursuit maintenance is approximately linear under these conditions. The shape of the filters were indicative of fast dynamics, with pure delays of merely ∼67 ms, times-to-peak of ∼115 ms, and effective integration times of ∼45 ms. The gain of the system, reflected in the amplitude of the filters, was inversely proportional to the size of the velocity fluctuations and independent of the target mean speed. A modest slow-down of the dynamics was observed as the contrast of the target decreased. Finally, the temporal filters recovered during fixation and pursuit were similar in shape, supporting the notion that they might share a common underlying circuitry. These findings show that the visual tracking of moving objects by the human eye includes a reflexive-like pathway with high contrast sensitivity and fast dynamics.

Estimation of Time-Varying Reactivity by theH∞, Optimal Linear Filter

1995 ◽  
Vol 119 (2) ◽  
pp. 128-138 ◽  
Author(s):  
Katsuo Suzuki ◽  
Junya Shimazaki ◽  
Koiti Watanabe
Keyword(s):  
Linear Filter ◽  
Time Varying ◽  
Optimal Linear ◽  
Estimation Of Time
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