在所有这些全我在不同层面的分身之间有一个常定的潜意识在交换信息，这也是这个过程中最重要的一点。
There is a constant subconscious interchange of information between all these layers of the whole self, and this is an extremely important process.
对于发生变化的动态经济过程，应用定常参数模型进行预测时误差较大。
In forecasting dynamic economic processes by using the model with steady parameters, large errors are often discovered.
本文提出了利用定常卡尔曼滤波来实现任意一维平稳随机过程递推最佳滤波的方法。
This paper proposes a method for recursive optimal filtering of one-dimension stationary ran-dom processes by use of Kalman filtering of constant system.
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