When you perform parallel processing, do not useRNG（“洗牌”）to set the random number stream on different workers to ensure independent streams since it seeds the random number generator based on the current time. This is especially true when the command is sent to multiple workers simultaneously, such as inside aparforjob. For independent streams on the workers, use the default behavior or consider using a unique substream on each worker usingRandStream。

When you perform parallel processing, the default random number generators on the MATLAB client and MATLAB workers are different. If you need to generate the same random stream of numbers on the client and workers, you can useRNGwith the same generator type and seed (or consider usingRandStream具有相同的发电机类型，种子和正常转化算法）。有关更多信息，请参阅Control Random Number Streams on Workers(Parallel Computing Toolbox)。

To useRNGinstead of therand或者randnfunctions with the'种子','状态', or'twister'inputs, see替换Rand和Randn的灰心语法。