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The difference between random and pseudo-random

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Release: 2023-10-10 09:27:59
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The difference between random and pseudo-random lies in predictability, reproducibility, uniformity and security. Detailed introduction: 1. Predictability. Random numbers cannot be predicted. Even if the past results are known, future results cannot be accurately predicted. Pseudo-random numbers can be predicted because they are generated by algorithms. As long as you know the algorithm and seed, you can regenerate the same sequence or sequence; 2. Reproducibility, random numbers are not reproducible, and the results generated each time are independent, while pseudo-random numbers are reproducible. Yes, just use the same algorithm and seeds etc.

The difference between random and pseudo-random

Randomness and pseudo-randomness are two commonly used concepts that are often discussed in computer science and statistics. Although they both involve randomness, there are some important differences between them.

First, let’s define random and pseudo-random.

Randomness refers to the nature of an event or value that cannot be predicted or determined. Mathematically, randomness can be described by probability, that is, the likelihood of a certain event occurring.

Pseudo-random refers to a sequence or sequence generated through a certain algorithm and seed. It looks random, but in fact it can be predicted and reproduced. This generated number sequence or sequence is called a pseudo-random number sequence or pseudo-random sequence.

Let’s discuss the difference between random and pseudo-random in detail.

1. Predictability: Random numbers cannot be predicted. Even if the past results are known, the future results cannot be accurately predicted. Pseudo-random numbers can be predicted because they are generated through algorithms. As long as the algorithm and seed are known, the same sequence or sequence can be generated repeatedly.

2. Reproducibility: Random numbers are not reproducible, and the results generated each time are independent. Pseudo-random numbers are reproducible. As long as the same algorithm and seed are used, the same sequence or sequence can be generated.

3. Uniformity: Ideally, random numbers should be evenly distributed, that is, each value has an equal probability of occurrence. Pseudo-random numbers may be biased in some cases, that is, certain values ​​have a higher or lower probability of occurring.

4. Security: Random numbers play an important role in the field of cryptography and security because they provide an encryption method that cannot be cracked. Pseudo-random numbers are insecure in the field of cryptography and security because they can be predicted and reproduced.

To sum up, random numbers are truly random and cannot be predicted and reproduced, while pseudo-random numbers are generated through algorithms and have a certain degree of predictability and reproducibility. In practical applications, we choose to use random numbers or pseudo-random numbers based on specific needs. In some scenarios that require true randomness, such as cryptography and security, we must use true random numbers. In some scenarios that need to look random, such as simulation experiments and game development, we can use pseudo-random numbers to simplify calculations and improve efficiency.

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