f(n) is upper Bounded by g(h). As n-> infinity F(n) will grow slower or as fast as g(n) but never faster. Option D.
This gives an asymptotic upper bound on the rate of increase in algorithm execution time. Let f(n) be the execution time of the algorithm and g(n) be the time complexity associated with the algorithm. Omega notation represents a lower bound on the running time of an algorithm.
It thus provides the optimal complexity of the algorithm. The above expression can be written as a function f(n) belonging to the set Ω. If a positive constant c exists and is above CG (n) for sufficiently large n. The number d is called tolerance. Arithmetic progressions differ by d and are obtained by subtracting any pair of terms an and On +1.
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