Computer-generated random number seeds need is to what extent the general range
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Users questions: Computer-generated random number seeds need is to what extent the general range, certainly in the 0 ~ 65 535 What? But I feel I do not know matlab random numbers generated by this range ah? Up to those who ask what I mean is 0 ~ 65535 or 65 536 seeds can generate random numbers of effective bits . I see I'm using scilab generated random number function of effective number of bits is 7, thank you for help.
Experts answer: in the computer and not a true random number generator, but it can be done to make the number generated by very low repetition rate, this looks like a real random numbers, to achieve this A function of the program is called pseudo-random number generator. The theory of how to generate random numbers, many, if you want to discuss in detail the need thick pages of a book. No matter what method of random number generator, we must give it a "seed" the initial value. And the best value is random, Or at least the value of a pseudo random. "Seed" value is usually quick count registers or shift registers to generate the. Talk about the C language in the following provided by the use of random number generator. The C compiler now provides an ANSI standard based on pseudo-random number generator function, for students Into a random number. They are the rand () and srand () function. These two functions work as follows: 1) First to srand () provides a seed, it is a unsignedint type, its values range from 0 to 65535; 2) then call rand (), Which provides for the basis of srand () returns a seed value of random number (0 to 32767) 3) The need to repeatedly call the rand (), to continuously obtain new random number; 4) whether When, can give srand () provides a new seed, Further "randomized" rand () output. This may seem simple, the problem is, if every time you call srand () seeds when they provide the same value, then you will get the same sequence of random numbers, then that phenomenon is not random numbers, each a few are The same as the. For example, the seed value of 17 to call srand () after the first call to rand (), you get 94 random numbers. In the second and third call rand () will be 26,602 and 30,017 respectively, these numbers appear to be very random (although this is only A small set of data points), however, you again for the seed value of 17 calls srand () after the rand () call in the first three, from the return value is still in the 94,26602,30017, and then get the return value is still in the rand ( ) The first call received by the rest of the return value. Therefore, only again to srand () provides a random seed value, can once again get a random number. The following examples use a simple and effective way to generate a fairly random "seed" value **** time of day values:
Experts answer: in the computer and not a true random number generator, but it can be done to make the number generated by very low repetition rate, this looks like a real random numbers, to achieve this A function of the program is called pseudo-random number generator. The theory of how to generate random numbers, many, if you want to discuss in detail the need thick pages of a book. No matter what method of random number generator, we must give it a "seed" the initial value. And the best value is random, Or at least the value of a pseudo random. "Seed" value is usually quick count registers or shift registers to generate the. Talk about the C language in the following provided by the use of random number generator. The C compiler now provides an ANSI standard based on pseudo-random number generator function, for students Into a random number. They are the rand () and srand () function. These two functions work as follows: 1) First to srand () provides a seed, it is a unsignedint type, its values range from 0 to 65535; 2) then call rand (), Which provides for the basis of srand () returns a seed value of random number (0 to 32767) 3) The need to repeatedly call the rand (), to continuously obtain new random number; 4) whether When, can give srand () provides a new seed, Further "randomized" rand () output. This may seem simple, the problem is, if every time you call srand () seeds when they provide the same value, then you will get the same sequence of random numbers, then that phenomenon is not random numbers, each a few are The same as the. For example, the seed value of 17 to call srand () after the first call to rand (), you get 94 random numbers. In the second and third call rand () will be 26,602 and 30,017 respectively, these numbers appear to be very random (although this is only A small set of data points), however, you again for the seed value of 17 calls srand () after the rand () call in the first three, from the return value is still in the 94,26602,30017, and then get the return value is still in the rand ( ) The first call received by the rest of the return value. Therefore, only again to srand () provides a random seed value, can once again get a random number. The following examples use a simple and effective way to generate a fairly random "seed" value **** time of day values:
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