NTA-NET (UGC-NET) Computer Science & Applications (87) Analysis and Design of Algorithms-Asymptotic Notations-Big Ohm, Omega and Theta Study Material (Page 2 of 4)

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Asymptotic Notations – Big Ohm, Omega and Theta: Constant Time

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Constant Time

  • This represents the Constant Time. An operation՚s complexity is constant regardless of the number of inputs. Accessing the first element in an array will always be (1) . It is the same for an array with elements as it is for an array with 10. In fact, accessing any element in the array by its index should be a constant complexity operation regardless of whether it is the first item or the th. The execution time of these algorithm is independent of the size of the input.

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Asymptotic Notations: Factorial Notation

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Factorial Notation

  • This 2 to the power “n” is by far the most complex of all the operations involved. Knowing the power of 2 from the number systems like binary etc. we know that even the smaller values of n like 10 or would mean a highly complex algorithm. Example we know that 220 itself is a million while 230 is in billions. As far as the examples are concerned, the classical recursive Fibonacci number calculation can be deemed as
  • This factorial notation is even bigger than the previous power of 2 notati…

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