Correlational Sensitivity among Strictly Bounded Conditional Entropy and Channel Capacity of GIG Function

Rohit Kumar Verma, Som Kumari
Abstract

This paper explores the Gaussian Information Gain Function  as an alternative to traditional logarithmic information measures. We define a corresponding entropy function and examine its mathematical properties, including concavity and bounds. Furthermore, we derive a formulation for channel capacity based on Gaussian information, providing a non-logarithmic perspective on information transmission. This approach is particularly relevant in fuzzy systems, uncertain environments, and non-additive information frameworks.

PDF download