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Low memory requirements and modest computational complexity facilitates calculations on high-resolution three-dimensional models.
The proposed Sparse RML (SpRML) approximate sampling approach can be used to assess the uncertainty in the calibrated model with a relatively modest computational complexity.
In order to guarantee numerical reliability and modest computational complexity compared with other identification techniques, in this paper, we propose a synergistic identification technique based on the principal components analysis (PCA) and subspace identification method (SIM) under white noise assumptions.
This results in a modest computational complexity for the algorithm as a whole.
Similar(56)
Our scheduler has low computational complexity.
In addition, it has also a low computational complexity.
Our approach is approximate, but it allows analysis of high-dimensional small sampled data, and its computational complexity is very modest.
Overall, the computational complexity is very low.
Computational Complexity theory is covered in computability and complexity.
The result is a low complexity controller, suitable for implementation in embedded control systems with modest computational power and available memory.
Recent fast summation techniques such as the Fast Multipole (FM) Method accelerate the solution of large fracture problems, demanding linear complexity O(N) in memory and execution time with very modest computational resources.
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