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Since low encoding complexity is the prime motivation for DVC, an evaluation of the complexity characteristics of the proposed feedback-channel-free architecture is unavoidable.
Section Complexity evaluation and normalization presents an evaluation of the receiver complexity in terms of number and type of arithmetic operations and memory access.
We conduct an evaluation of the computational complexity using TIC and TOC instruction in MATLAB.
High-accuracy subpixel motion estimation is discussed in Section 4. Section 5 presents an evaluation of the computational complexity of our algorithm.
Even though the focus of a DVC codec is the reduction in encoding complexity, an evaluation of the decoding time is important to understand the complexity of the entire system.
Open image in new window Fig. 14 Evaluation of complexity of the experimental modal shapes: on the first row, representation of the modal shapes with the interpolating line; on the second, MCF2 method.
We provide an evaluation of the worst-case time and message complexity and some performance data from a prototype implementation.
In order to appreciate the complexity of the two iterative modes, an accurate evaluation of the complexity in terms of number and type of operations and memory accesses is required.
In order to appreciate this study, an accurate evaluation of the complexity in terms of number and type of operations and memory access has been done in Section Number of iterations analysis for identical complexity.
We perform a detailed evaluation of the complexity of the problem for various classes of graphs.
An evaluation on the complexity of the algorithm [12] can be found in [17].
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