The Single-vector and Multi-vector Mixed Compressed Storage of Tangent Matrix
Wenjiao Da, Xiuli Wang, Jing Wen, Han Zhang
Available Online May 2016.
- https://doi.org/10.2991/iceat-16.2017.1How to use a DOI?
- The compressed storage, single-vector, multi-vector, the tangent matrix
- Matrix is a mathematical object, commonly used in scientific computing and engineering calculation. We are not interested in data itself in the data structure, but interested in how to store the elements in the matrix, and make the various operations can run effectively. The main purpose of the compressed storage is to make more of the same nonzero elements share the same storage unit according to the distribution of matrix element, while the zero elements don't allocate storage space. In this paper, we studied the single-vector and multi-vector compressed storage problems of tangent matrix, and obtained the row and column priority compressed storage address mapping function. These two kinds of compressed storage have a high compression ratio. These conclusions hope to provide the basis theory of data compression storage for the scientific research workers.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Wenjiao Da AU - Xiuli Wang AU - Jing Wen AU - Han Zhang PY - 2016/05 DA - 2016/05 TI - The Single-vector and Multi-vector Mixed Compressed Storage of Tangent Matrix BT - Proceedings of the 2016 International Conference on Engineering and Advanced Technology PB - Atlantis Press SP - 1 EP - 4 SN - 2352-5401 UR - https://doi.org/10.2991/iceat-16.2017.1 DO - https://doi.org/10.2991/iceat-16.2017.1 ID - Da2016/05 ER -