Step 1: Understanding Dynamic Programming for Sequence Alignment
The time complexity of dynamic programming for sequence alignment between multiple sequences is \(O(n^3)\), where \(n\) is the length of each sequence, and there are three sequences being aligned.
Step 2: Evaluating the Options
- \(5n^3\): Incorrect time complexity for three sequences.
- \(6n^3\): Incorrect, does not match the expected time complexity.
- \(7n^3\) Correct, the time complexity is typically \(O(n^3)\) for three sequences.
- \(8n^3\): Incorrect, does not match the expected time complexity.
Step 3: Conclusion
The time complexity for dynamic programming for aligning three sequences is \(O(n^3)\), which corresponds to the option \(7n^3\).
List I: Fermentation Products | List II: Strain used | ||
A | Mast cells | I | Clostridium tetani |
B | Lymphocytes | II | Brevibacterium sp. |
C | T-cells | III | Leuconostac mesenteroids |
D | Monocytes- Macrophages | IV | Bacillus subtillis |
V | Streptomyces olivaceus |
A closed-loop system has the characteristic equation given by: $ s^3 + k s^2 + (k+2) s + 3 = 0 $.
For the system to be stable, the value of $ k $ is:
A digital filter with impulse response $ h[n] = 2^n u[n] $ will have a transfer function with a region of convergence.