Description: C Generate a pseudorandom, gaussian distributed number with mean 0 and standard deviation 1.
C The random number is generated with ran1.
C param idum An integer argument passed to ran1 Platform: |
Size: 510 |
Author:candice_yan@msn.com |
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Description: Generate Possion Dis.
step1:Generate a random number between [0,1]
step2:Let u=F(x)=1-[(1/e)x]
step3:Slove x=1/F(u)
step4:Repeat Step1~Step3 by using different u,you can get x1,x2,x3,...,xn
step5:If the first packet was generated at time [0], than the
second packet will be generated at time [0+x1],The third packet will be generated at time [0+x1+x2],
and so on ….
Random-number generation
1.static method random from class Math
-Returns doubles in the range 0.0 <= x < 1.0
2.class Random from package java.util
-Can produce pseudorandom boolean, byte, float, double, int, long and Gaussian values
-Is seeded with the current time of day to generate different sequences of numbers each time the program executes-Generate Possion Dis.
step1:Generate a random number between [0,1]
step2:Let u=F(x)=1-[(1/e)x]
step3:Slove x=1/F(u)
step4:Repeat Step1~Step3 by using different u,you can get x1,x2,x3,...,xn
step5:If the first packet was generated at time [0], than the
second packet will be generated at time [0+x1],The third packet will be generated at time [0+x1+x2],
and so on ….
Random-number generation
1.static method random from class Math
-Returns doubles in the range 0.0 <= x < 1.0
2.class Random from package java.util
-Can produce pseudorandom boolean, byte, float, double, int, long and Gaussian values
-Is seeded with the current time of day to generate different sequences of numbers each time the program executes Platform: |
Size: 155648 |
Author:黃文岩 |
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Description: This is noise generator with given statistical and spectral characteristics based on pseudorandom number generator which realises Merssenne Twister algorithm Platform: |
Size: 746496 |
Author:Roman Burzakovskiy |
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Description: Hamming codes are a class of binary linear codes. They can detect up to two simultaneous bit errors, and correct single-bit errors. In particular, a single-error-correcting and double error detecting variant commonly referred to SECDED.-a) Develop a Verilog module that will generate a 7-bit encoded data from a 4-bit data. Simulate your design for two inputs. Use even or odd parity according to the least significant figure of your ID number.
b) Develop a Veriog module for generating pseudorandom 4-bit data using Linear Feedback Shift Register( LFSR) method.
c) Develop a Verilog module to emulate one bit error in the data transmission. This can be done by changing only one of the encoded bits at each clock cycle. You may use a ring-counter and XOr gates for doing this. This arrangement will insert error in consecutive bits at each clock cycle.
d) Design a Hamming error detection and correction circuit to restore the original data.
e) Compare the original data with the restored data to verify the error correction capability of your design. If the two data sets are equal an OK signal will be set. Platform: |
Size: 1133568 |
Author:wei chenghao |
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Description: 将自定义的整数随机数生成器编写为一个类，该类使用一个公式从上一个随机数的到下一个伪随机数。随机数程序以某个“启动源（seed）”值开始。其后，通过对当前随机数执行某个运算得到下一个随机数，运算使当前随机数变成另一个（明显随机的）数。适用于整数的公式为：nextR=((oldR*25173)+13849) 65536；
它产生0~65536之间的数。为了得到看起来随机的好结果，该公式中几个特定的数已经给出。-The custom integer random number generators are written as a class, the class using a formula from the previous random number to the next pseudorandom number. Random number procedure to a "start source (seed)" value. Subsequently, by performing an operation on current number of random is the next random number, computing the current random number into another (clearly random) number. Applied to integers is: nextR= ((oldR*25173) +13849) 65536 It creates between the 0~65536 number. In order to get good results of seemingly random, some specific number has been given in the formula. Platform: |
Size: 63488 |
Author:慕容丹丹 |
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Description: 此程式是利用DES 來進行加密與解密的動作，Mode 採用ECB，Padding 方
法則採用PKCS5Padding。Key 是由程式自行產生，採用Pseudorandom number
generator 來產生Key。利用Framework 為Java Cryptography Extension (JCE) 。-This program is the use of DES to encrypt and decrypt action, Mode ECB Padding method using PKCS5Padding. Key is generated by the program on their own Pseudorandom number generator to generate the Key. The use of Framework for the Java Cryptography Extension (JCE). Platform: |
Size: 229376 |
Author:eason |
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Description: the LFSR is coded in VHDL, using a structural description, which is instantiated as a
separate component in the top-level design. Then we can get a random number by a pseudorandom number generator based on a linear feedback
shift register (LFSR) Platform: |
Size: 2048 |
Author:宋臣 |
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Description: A pseudorandom number generator (PRNG), also known as a deterministic random bit generator (DRBG),[1] is an algorithm for generating a sequence of numbers whose properties approximate the properties of sequences of random numbers. The PRNG-generated sequence is not truly random, because it is completely determined by a relatively small set of initial values, called the PRNG s seed (which may include truly random values). Although sequences that are closer to truly random can be generated using hardware random number generators, pseudorandom number generators are important in practice for their speed in number generation and their reproducibility.[2]
PRNGs are central in applications such as simulations (e.g. for the Monte Carlo method), electronic games (e.g. for procedural generation), and cryptography. Cryptographic applications require the output not to be predictable earlier outputs, and more elaborate algorithms, which do not inherit the linearity of simpler PRNGs, are needed.-A pseudorandom number generator (PRNG), also known as a deterministic random bit generator (DRBG),[1] is an algorithm for generating a sequence of numbers whose properties approximate the properties of sequences of random numbers. The PRNG-generated sequence is not truly random, because it is completely determined by a relatively small set of initial values, called the PRNG s seed (which may include truly random values). Although sequences that are closer to truly random can be generated using hardware random number generators, pseudorandom number generators are important in practice for their speed in number generation and their reproducibility.[2]
PRNGs are central in applications such as simulations (e.g. for the Monte Carlo method), electronic games (e.g. for procedural generation), and cryptography. Cryptographic applications require the output not to be predictable earlier outputs, and more elaborate algorithms, which do not inherit the linearity of simpler PRNGs, are needed. Platform: |
Size: 9216 |
Author:rajendra |
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Description: In recent years, a large number of discrete chaotic cryptographic algorithms have been proposed. The chaotic based cryptograms are suitable for large-scale data encryption such as images, videos or audio data. This paper propose a novel higher dimensional chaotic system for audio encryption, in which variables are treated as encryption keys in order to achieve secure transmission of audio signals. Since the highly sensitive to the initial condition of a system and to the variation of a parameter, and chaotic trajectory is so unpredictable. As a result we obtain much higher security. The higher dimensional of the algorithm is used to enhance the key space and security of the algorithm. The security analysis of the algorithm is given. The experiments show that the algorithm has the characteristic of sensitive to initial condition, high key space pixel distribution uniformity and the algorithm will not break in chosen/known-plaintext attacks-In recent years, a large number of discrete chaotic cryptographic algorithms have been proposed. The chaotic based cryptograms are suitable for large-scale data encryption such as images, videos or audio data. This paper propose a novel higher dimensional chaotic system for audio encryption, in which variables are treated as encryption keys in order to achieve secure transmission of audio signals. Since the highly sensitive to the initial condition of a system and to the variation of a parameter, and chaotic trajectory is so unpredictable. As a result we obtain much higher security. The higher dimensional of the algorithm is used to enhance the key space and security of the algorithm. The security analysis of the algorithm is given. The experiments show that the algorithm has the characteristic of sensitive to initial condition, high key space pixel distribution uniformity and the algorithm will not break in chosen/known-plaintext attacks Platform: |
Size: 23552 |
Author:medo |
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Description: 根据学习过的离散事件系统仿真的基本概念，进一步了解离散事件系统中伪随机数生成的基本方法-According to the study of the basic concept of discrete event system simulation, a deeper understanding of the basic methods of discrete event systems generate pseudorandom number
Platform: |
Size: 239616 |
Author:Ansen.J |
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Description: 在实际应用中往往使用伪随机数就足够了。这些数列是“似乎”随机的数，实际上它们是通过一个固定的、可以重复的计算方法产生的。计算机或计算器产生的随机数有很长的周期性。它们不真正地随机，因为它们实际上是可以计算出来的，但是它们具有类似于随机数的统计特征。这样的发生器叫做伪随机数发生器。
在真正关键性的应用中，比如在密码学中，人们一般使用真正的随机数。-In actual applications tend to use a pseudorandom number is sufficient. The number of columns is " as if" a random number, in fact they are through a fixed, repeatable calculation produced. A random number generated by a computer or a calculator has a long periodicity. They are not really random, because they can actually be calculated, but they have similar statistical characteristics of random numbers. Such a pseudo random number generator is called the generator. In the real critical applications, such as in cryptography, people generally use a truly random number. Platform: |
Size: 1024 |
Author:张羽翔 |
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Description: NIST标准的随机数检测工具；支持单比特频数检测、块内频数检测、扑克检测、重叠子序列检测、游程总数检测、游程分布检测等(A Statistical Test Suite for Random and Pseudorandom Number Generators for Cryptographic Applications) Platform: |
Size: 6544384 |
Author:ddbing
|
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Description: 说明： NIST标准的随机数检测工具；支持单比特频数检测、块内频数检测、扑克检测、重叠子序列检测、游程总数检测、游程分布检测等源代码(A Statistical Test Suite for Random and Pseudorandom Number Generators for Cryptographic Applications source code) Platform: |
Size: 46080 |
Author:ddbing
|
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Description: MATLAB，随机数伪随机数生成概念，蒲丰投针实验原理(The concept of generation of random number pseudorandom number) Platform: |
Size: 724992 |
Author:111qqq222 |
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Description: 用VC++6实现的一个伪随机数生成演示程序源码,包含了正态分布随机数生成和平均分布随机数两种生成方式,(Using VC 6 to realize a pseudorandom number generation demonstration program source code, including normal distribution random number generation and average distribution random number generation methods.) Platform: |
Size: 17408 |
Author:eopsip |
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Search - pseudorandom number