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A method is presented to obtain a full (non-proportional) viscous damping matrix from complex modes and complex natural frequencies.
The method uses experimentally identified complex modes and complex natural frequencies, together with the knowledge of the mass matrix for the system.
As the model is specifically aimed at the effects of absorption on the lower acoustic modes, and complex geometries may be represented, the method should find applications in vehicle interior noise prediction.
Once the complex modes and complex modal forces are known, the modal equation can be formed and a time history integration can be carried out to determine the buffeting responses.
Theoretical derivation of distributive mass effect of steel spring on vibration is presented, and multiple eigenfrequencies are obtained, which manifest that distributive mass results in extra modes and complex impedance properties.
The procedure is based on a constrained error minimization approach and uses only experimentally identified complex modes and complex natural frequencies together with, for the non-viscous model, the mass matrix of the system.
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Step 3: derive the prediction mode of the co-located texture video treeblocks; if texture treeblock has no motion, perform early merge/skip mode decision and go to Step 7, else go to Step 4. Step 4: compute C based on Equation 3 and T 1 and T 2 based on Equation 4; classify the current depth map treeblock into the simple mode region, normal mode region, and complex mode region.
The accuracies here are defined as the ratio of the number of the simple mode, normal mode, and complex mode, which select the same best modes using the 3D-HEVC encoder as well as the proposed algorithm.
The normal complex modes and generalized complex modes are defined.
Thus, if we disable inter-view prediction in the normal mode region and complex mode region, the coding efficiency loss is not negligible.
Although the test sequences such as 'Poznan_Hall2' and 'Newspaper' contain a large area of the homogeneous textures and low-activity motion, which are more likely to be encoded with temporal prediction, the probability of inter-view prediction for a treeblock with a normal mode region and complex mode region is still highest.
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