Answer:
O(N!), O(2N), O(N2), O(N), O(logN)
Explanation:
N! grows faster than any exponential functions, leave alone polynomials and logarithm. so O( N! ) would be slowest.
2^N would be bigger than N². Any exponential functions are slower than polynomial. So O( 2^N ) is next slowest.
Rest of them should be easier.
N² is slower than N and N is slower than logN as you can check in a graphing calculator.
NOTE: It is just nitpick but big-Oh is not necessary about speed / running time ( many programmers treat it like that anyway ) but rather how the time taken for an algorithm increase as the size of the input increases. Subtle difference.
Answer:
i do not know
Explanation:
but it helps to communication
A big question or problem in the tech field that i would like to solve is Data security.
<h3>What is Data security ?</h3>
Data security can be regarded as process of protecting data from unauthorized user as well as protection from data corruption .
I will like to solve this problem because as advances in technology, the data of individual or organization is not been total secured and this is posing so much loss to individuals.
Data security are;
- data encryption
- hashing
- tokenization
Learn more about Data security at;
brainly.com/question/17493537
Cache memory is a high-speed memory that stores the instructions and data that have been frequently accessed. It decreases the time it takes to decode the instructions stored in the instruction pipeline.
A. It decreases the time it takes to decode instructions stored in the instruction pipeline.
<u>Explanation:</u>
Whenever an instruction is invoked or some data is accessed, the CPU looks for it in the cache memory before accessing the main memory.
If the content is found in the cache memory, it accessed from there and then and hence the access time and decode time is reduced as there were no main memory lockups.
