提出了复杂系统中自聚集的概念, 这是广泛存在于复杂系统中的一种自组织的形式, 然后考虑系统的功能, 尝试对熟知的$1+1>2$(总体大于部分之和),
即关于系统功能的定性表达, 寻求一种进一步定量定性的更一般的关系.  给出了一个描述复杂系统的简单的网络模型, 它有相当广泛的代表性,
并用它分析系统的生长、演化及涌现过程以及在过程中功能的变化, 得到一个定量定性的关系式$f(n)=\frac{1}{2}n(n-1)$, 表达功能变化规律.
此式能揭示系统功能的一些性质并解释一些重要现象, 诸如: $1+1>2$ 是此式当$n=2$时的特例, 此式还给出具体的非线性；
它还说明系统生长初期, 组分的增减对系统的功能影响显著;当系统规模达到一定大时, 将导致稳态涌现；
以及系统功能从起始的脆弱性到稳态涌现的鲁棒性. $f(n)$还蕴涵着正反馈的激励放大机制, 并给出一个表达式.
据此说明此式可作为``报酬递增''的机制以及导致无标度网结构形成的``优先连接''的机制. 最后是几句关于复杂与简单的话.

In this paper the concept of ``self-clustering" is presented. It is one kind of the self-organizing and widely existing in complex systems. For the function of complex systems, there is a well-known inequality $1+1>2$ , showing that the whole is more than the sum of its parts. Could it seek one more quantitative expression for the function of complex systems? For this purpose a simple but widely representative network model is given. With this model, the process of growing, evolving and emergence of the system can be analyzed and a quantitative/qualitative expression $f(n)=\frac{1}{2}n(n-1)$ for system function can be derived. This expression indicates properties of the system function and gives explanations of some important phenomena.  Such as: $1+1>2$ is a special case of $f(n)$ as $n=2$. Moreover, $f(n)$ shows the nonlinearity obviously.  It also shows that at the initial stage of the process, adding or losing a few components will give rise to notable effect to the system function.  There will be a steady emergence as $n$ increased to a considerable amount.
  Thus, it reveals the change that from the fragility at the initial stage to the robustness accompanying the steady emergence.  In addition, $f(n)$ implies positive feedback.  An expression is given to show this mechanism, which turns out to be the mechanism of "increasing returns" and the mechanism of ``preferential attachment",  leading to the scale-free network structure. Finally, a brief conclusion regarding complexity and simplicity is given.