# Algorithm design of a combinatorial mathematical model for computer random signals

## TL;DR

This paper introduces a new mathematical model for computer random signals using an intelligent algorithm to improve signal processing.

## Contribution

A novel combinatorial mathematical model and optimized kernel function for enhanced signal processing in noisy environments.

## Key findings

- The ambiguity function of conventional FHS was analyzed mathematically and graphically.
- A new kernel function improved parameter estimation of FHS in various noise environments.
- Simulation experiments confirmed the model's effectiveness in enhancing signal combination.

## Abstract

To improve the processing effect of computer random signals, the manuscript employs the intelligent signal recognition algorithm to design a combinatorial mathematical model for computer random signals, and studies the parameter estimation of conventional frequency hopping signal (FHS) based on optimizing kernel function (KF). First, the mathematical form and graphical representation of the ambiguity function of the conventional FHS are explored. Furthermore, a new KF is presented according to its fuzzy function (FF) and the parameters of conventional FHSs are estimated according to the time-frequency distribution corresponding to the KF. Then, simulation experiments are carried out in different types of interference noise environments. The proposed combinatorial mathematical model for computer random signals shows a practical impact, and can effectively improve the effect of random signal combination.