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The Kernel Logistic Regression (KLR) method [18] performed slightly better than BMRF, but this method involves an expensive matrix exponentiation operation, that is needed to compute the diffusion kernel.
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One difficulty with this approach is its reliance on the matrix exponential e m Δ. Identifying general numerical approaches to matrix exponentiation is known to be problematic (Moler and Van Loan, 2003).
Most common models are defined using rate matrices, which are 4×4 matrices whose off-diagonal elements are non-negative substitution rates, and whose rows sum to 0. A stochastic transition matrix P is obtained from a rate matrix R through matrix exponentiation: P= e R. A common assumption made on the substitution process is that it is homogeneous throughout time.
Texp: The time of executing a modular exponentiation operation.
As reported in[14], the modular inverse computation and modular exponentiation operation are the most time-consuming operations.
Estimation is done by matrix exponentiation of the transition rate matrix for a continuous time finite state Markov chain approximation.
In addition, one signature generation and verification operation in conventional cryptosystem such as RSA are equivalent to one modular exponentiation operation.
Compared with CP-ABE, we add an exponentiation operation in this algorithm, and the added operation has no obvious influence on computation cost as shown in Fig. 4a.
The probability element is constructed at the 1600 return points on matrix exponentiation for one-, five-, and ten-day returns.
In this paper, we investigate two different ways to implement modular exponentiation based on the evolved addition chain: the first approach consists of implementing all the exponentiation operation on hardware and the second approach combines software and hardware.
Estimation is conducted by employing a continuous-time finite-state Markov chain approximation that yields probability elements on matrix exponentiation of the transition rate matrix.
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