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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.

The Single-vector and Multi-vector Mixed Compressed Storage of Tangent Matrix