Touch Sensitive Device
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Benefits of technology
Problems solved by technology
Method used
Image
Examples
example 1
m=3, n=2
[0195]Output 1 transfer admittances: P1—1=0.472+0.00344j
[0196]Output 2 transfer admittances: P1—2=−0.206−0.195j
[0197]Output 1 transfer admittances: P2—1=0.479−0.129j
[0198]Output 2 transfer admittances: P2—2=0.262+0.000274j
[0199]Output 1 transfer admittance: P3—1=−0.067−0.180j
[0200]Output 2 transfer admittance: P3—2=0.264+0.0014j
[0201]All at Once
M1+M2=(0.3030.171-0.012j-0.087-0.034j0.171+0.012j0.3150.061-0.095j-0.087+0.034j0.061+0.095j0.107);
|M1+M2|=0
[0202]M1+M2: eigenvalues are 0, 0.218 and 0.506:
[0203]Eigenvector after scaling: (0.434−0.011j, −0.418+0.199j, 0.764+0.115j)
[0204]One at a Time
[0205]Solve output 1, and then output 2. As 3>2 we should get the same answer.
M1=(0.2230.226-0.063j-0.032-0.085j0.226+0.063j0.246-0.009-0.095j-0.032+0.085j-0.009+0.095j0.037);
|M1|=0
[0206]M1: eigenvalues are 0, 0 and 0.506:
[0207]Eigenvector V1: (0.748, −0.596−0.165j, 0.085−0.224j)
[0208]Eigenvector V2: (−0.062+0.026j, 0.096+0.350j, 0.929)
[0209]New problem; select a and b such that a·V1+b·V2...
example 2
m=3, n>=3
[0221]Here we have 1 acoustic pressure output and a number of velocity outputs.
[0222]Acoustic scaled error matrix is M1, summed velocity scaled error matrix is M2.
M1=(3.928-2.667+2.473j-2.674+2.506j-2.667-2.473j3.3673.393-0.018j-2.674-2.506j3.393+0.018j3.418);
|M1|=0
[0223]M2=(1.0230.602+0.112j-0.528+0.409j0.602+0.112j0.977-1.144+0.205j-0.528-0.409j-1.144-0.205j5.473);
|M2|=2.510
[0224]All at Once
[0225]All n output error matrices are summed and the eigenvector corresponding to the lowest eigenvalue is found.
[0226]Eigenvalues (M1+M2)=1.146, 3.869, 13.173
[0227]Solution=(0.739−0.235j, 0.483+0.306j, 0.246+0.104j)
[0228]One at a Time
[0229]Actually, we solve just the acoustics problem, then do the rest all at once. That way, the acoustics problem is solved exactly.
[0230]Eigenvalues (M1)=0, 0, 10.714
[0231]V1=(0.770−0.199j, 0.376+0.202j, 0.377+0.206j)
[0232]V2=(0.097−0.071j, 0.765+0.010j, −0.632+0.0016j)
[0233]As V1 and V2 both correspond to a zero eigenvalue, a·V1+b·V2 is also an eigenve...
PUM

Abstract
Description
Claims
Application Information

- R&D
- Intellectual Property
- Life Sciences
- Materials
- Tech Scout
- Unparalleled Data Quality
- Higher Quality Content
- 60% Fewer Hallucinations
Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.
© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com