The mathematical sciences, and particularly probabilistic and statistical methods, are key to understanding the dependencies of the systems. The purpose of this paper is to encourage a wider recognition by engineers of a new generalized principle which in its mathematical form is a powerful instrument for the solution of practical problems. Generalized probability density function was introduced to permit analysis without pre‐knowledge of the source of the data. The fundamental principles are extended to apply the most related engineering applications without the need to know the type of source generating the data. The generalized model presented eliminates preliminary work in engineering problems. The proposed model introduces an exponential density function to produce a direct solution to randomly varying data. The exponential density function is fully compatible with applications containing randomly distributed data. The success of the generalized model presented is due to the calculated parameters in the exponential density function. The method is applied to various problems chosen from the field of engineering with great success.

中文翻译：

---

广义概率密度函数及其在电路和系统实验数据中的应用

数学科学，尤其是概率和统计方法，对于理解系统的依赖性至关重要。本文的目的是鼓励工程师广泛认可一种新的广义原理，该原理以其数学形式是解决实际问题的有力工具。引入了通用概率密度函数，以允许在不事先知道数据源的情况下进行分析。基本原理已扩展为可应用最相关的工程应用程序，而无需了解生成数据的源类型。提出的通用模型消除了工程问题的前期工作。所提出的模型引入了指数密度函数，以产生对随机变化数据的直接解。指数密度函数与包含随机分布数据的应用程序完全兼容。所提出的广义模型的成功归因于指数密度函数中的计算参数。该方法成功应用于工程领域中的各种问题。