Temporal Discretization Errors Produce Minimal Effects on Vestibular Prosthesis Performance1

2016 ◽  
Vol 10 (3) ◽  
Author(s):  
Peter J. Boutros ◽  
Nicolas Valentin ◽  
Kristin N. Hageman ◽  
Dale Roberts ◽  
Chenkai Dai ◽  
...  
Keyword(s):  
Vestibular Prosthesis ◽  
Temporal Discretization ◽  
Discretization Errors

scholarly journals Scaling behavior of discretization errors in renormalization and improvement constants

2006 ◽  
Vol 73 (11) ◽  
Author(s):  
Tanmoy Bhattacharya ◽  
Rajan Gupta ◽  
Weonjong Lee ◽  
Stephen R. Sharpe
Keyword(s):  
Scaling Behavior ◽  
Discretization Errors

scholarly journals Development of a Multichannel Vestibular Prosthesis Prototype by Modification of a Commercially Available Cochlear Implant

2013 ◽  
Vol 21 (5) ◽  
pp. 830-839 ◽  
Author(s):  
Nicolas S. Valentin ◽  
Kristin N. Hageman ◽  
Chenkai Dai ◽  
Charles C. Della Santina ◽  
Gene Y. Fridman
Keyword(s):  
Cochlear Implant ◽  
Vestibular Prosthesis

Robustness of Natural Controls of Distributed-Parameter Systems

1996 ◽  
Vol 118 (1) ◽  
pp. 56-63 ◽  
Author(s):  
Jai Hyuk Hwang ◽  
Doo Man Kim ◽  
Kyoung Ho Lim
Keyword(s):  
Closed Loop ◽  
Distributed Parameter Systems ◽  
Distributed Parameter ◽  
Control Force ◽  
Spatial Discretization ◽  
Actual System ◽  
Discretization Errors

In this paper, the effect of parameter and spatial discretization errors on the closed-loop behavior of distributed-parameter systems is analyzed for natural controls. If the control force designed on the basis of the postulated system with the parameter and discretization errors is applied to control the actual system, the closed-loop performance of the actual system will be degraded depending on the degree of the errors. The extent of deviation of the closed-loop performance from the expected one is derived and evaluated using operator techniques. It has been found that the extent of the deviation is proportional to the magnitude of the parameter and discretization errors, and that the proportional coeffecient depends on the structures of the natural controls.

Recent Refinements in the Multi-Point Approximation Method in Conjunction With Adaptive Mesh Refinement

1996 ◽  
Author(s):  
Fred van Keulen ◽  
Vassili Toropov ◽  
Valery Markine
Keyword(s):  
Approximation Method ◽  
Adaptive Mesh Refinement ◽  
Weighted Least Squares ◽  
Mesh Refinement ◽  
Structural Response ◽  
Adaptive Mesh ◽  
The Finite Element Method ◽  
Point Approximation ◽  
Discretization Errors ◽  
Weight Coefficients

Abstract Application of the Multi-point Approximation Method (MAM) to structural optimization is considered. Structural analyses are performed by means of the finite element method with Adaptive Mesh Refinement (AMR). The required discretization errors are changed during the optimization process to achieve a higher computational efficiency. A straightforward combination of the MAM and AMR may yield complications, which are discussed in detail. Therefore, several modifications in the MAM are necessary. An alternative strategy for determining the explicit approximation functions using a weighted least-squares fitting is proposed. The applied weight coefficients reflect the levels of the discretization errors. The approximation functions are fitted with a sub-set of the available structural response analyses. An alternative move limit strategy is given. On the basis of several numerical examples it is shown that the proposed modifications improve the convergence characteristics of the MAM when combined with AMR. Moreover it is demonstrated that the proposed refinements are also beneficial for optimization of systems with noisy objective and constraint functions.

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