Strong Linear Dependence and Unbiased Distribution of Non-propagative Vectors
This paper proves (i) in any (n − 1)-dimensional linear sub-space, the non-propagative vectors of a function with n variables are linearly dependent, (ii) for this function, there exists a non-propagative vector in any (n − 2)-dimensional linear subspace and there exist three non-propagative vectors...
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| creator | Zheng, Yuliang Zhang, Xian-Mo |
| description | This paper proves (i) in any (n − 1)-dimensional linear sub-space, the non-propagative vectors of a function with n variables are linearly dependent, (ii) for this function, there exists a non-propagative vector in any (n − 2)-dimensional linear subspace and there exist three non-propagative vectors in any (n − 1)-dimensional linear subspace, except for those functions whose nonlinearity takes special values. |
| doi_str_mv | 10.1007/3-540-46513-8_7 |
| format | Book Chapter |
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| fulltext | fulltext |
| identifier | ISSN: 0302-9743 |
| ispartof | Lecture notes in computer science, 2000, Vol.1758, p.92-105 |
| issn | 0302-9743 1611-3349 |
| language | eng |
| recordid | cdi_pascalfrancis_primary_1177321 |
| source | Springer Books |
| subjects | Applied sciences Boolean Function Cryptography Exact sciences and technology Information, signal and communications theory Nonlinearity Propagation Signal and communications theory Telecommunications and information theory |
| title | Strong Linear Dependence and Unbiased Distribution of Non-propagative Vectors |
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