Furthermore, Akutsu et al. [ 9] developed algorithms with guaranteed worst case time complexity for the singleton attractor detection for BNs with limited Boolean functions.
This results in the worst case time duration for an immediate neighbor of a node to communicate with it.
We combine the solutions to obtain nH0+o(nlogσ) bits of space and O logn(1+logσloglogn)) worst-case time for all the operations.
The results also show that the hardware cost for an FPGA implementation of our architecture is considerably smaller than other network-on-chips with similar reconfiguration functionalities, and that the worst-case time for a reconfiguration is smaller than that seen in functionally equivalent architectures.
One solution, by Mäkinen and Navarro, achieves compressed space (i.e., nH0+o(nlogσ) bits) and O lognlogσ) worst-case time for all the operations, where n is the sequence length, σ is the alphabet size, and H0 is the zero-order entropy of the sequence.
The worst-case time for this algorithm is O (m ⋅ (n + m + ∑ r ∈ P | X (r ) | + | Y (r ) | ) ).
Finally, the longitudinal controller for ATV, based on a nonlinear control technique so-called Dynamic Surface Control (DSC), is designed and validated via simulation whether it can compensate for the worst case time delay and packet loss resulting from CAN communications.
Let us now check the worst case time complexity of selecting the next hop forwarders for node v i.
For a specific neighborhood size κ, we can then determine the worst case time complexity of each neighborhood operator.
Moreover, the FPTAS improves the worst-case time bound for obtaining approximate solutions to BKP as compared to using FPTASs designed for BKP or the 0-1 KnaProblemroblem.
In our case, the weighted unranking algorithm requires a precomputation step in worst-case time O (n 2 ) for computing all weighted class sizes up to input size n.
