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Moreover, the implementation is simple: approximately 50 lines of code for the shared-memory version.
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Since both steps in the algorithm use linear models, implementation is simple and straightforward.
This strategy is used because its implementation is simple, the algorithm can be extended to support more parameter combinations and its number of generated combinations is similar to other strategies [19, 27].
Compared to the solution reconstruction in Godunov-type methods, its implementation is simple and easy, and the computational complexity is relatively low.
The effectiveness of the proposed method is demonstrated, and its implementation is simple, robust and flexible.
We choose the K-means algorithm since it is known to be a very efficient data mining tool that is widely used in practice as its implementation is simple and the algorithm converges quickly [5].
Our proposed method is intuitive and its implementation is simple compared with optimization methods using the level set method or phase field model.
Hence, its implementation is simple; it just needs a small modification to the software of the helicopter position controller.
Its numerical implementation is simple, making it easy for users to make changes as they see fit.
The scheme is based on temporal skewing between data words on even and odd lines of an interconnection link, and its hardware implementation is simple and area-efficient.
Compared with other multiscale feature point detectors, our implementation is simple and fast.
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