For most large underdetermined systems of linear equations the minimal 1-norm solution is also the sparsest solution We consider linear equations y = Φx where y is a given vector in ℝn and Φ is a given n × m matrix with n < m ≤τn, and we wish to solve ... David,L.,Don...
Lemma 1. Let M denote an arbitrary 16 by 16 matrix of elements in GF(q), representing a linear transformation on AES states5. Let x be an input state to this linear transformation M and let b be a non-zero output mask. Then b • (M × x) = (MT × b) • x. The ...
We demonstrate that if B k 脳 k n is a sequence of symmetric matrices that converges in probability to some fixed but unspecified nonsingular symmetric matrix B elementwise, then B = B 0 for a specified matrix B 0 if and only if both the trace and squared Euclidean norm of D n D T...
The setup is that the prover has a linear function f and ordered pairs such that (in (1), the function f is defined by the matrix ). He wishes to prove the knowledge of with small coefficients such that . The algorithm from [CDXY17] works in two stages. In the first stage, it ...
摘要: The definition of the concave-convex character and its judgment theorem are first described and then further examples are listed to illustrate the application of function concave-convex character in proving inequality. 关键词: concave convex character inequality 被引量: 1 年份: 2003 收藏...
. . , (yn, xn) such that f (xi) = yi (in (1), the function f is defined by the matrix A). He wishes to prove the knowledge of xi with small coefficients such that f (xi) = yi. The algorithm from [CDXY17] works in two stages. In the first stage, it runs the "...