The invention relates to the technical field of computer-aided communication, in particular to a
wireless mouse strong interference source avoiding method based on a
wireless frequency hopping model, which comprises the following steps: acquiring multi-band
signal characteristics by monitoring
electromagnetic spectrum data of an environment where a
wireless mouse is located in real time; constructing an interference source analysis model by using an improved weighted
fuzzy clustering algorithm, and accurately identifying the type and intensity distribution of an interference source; according to an analysis result, dynamically generating a frequency hopping strategy by using a channel
state prediction model based on
reinforcement learning, and determining priority sequences of a
main channel and a standby channel; when the interference on the
main channel exceeds a preset threshold value, performing real-time evaluation by means of a composite quality index and switching to an optimal standby channel; meanwhile, through a closed-loop feedback mechanism, according to the difference between actual channel quality and expected channel quality, a
stochastic gradient descent method is adopted to optimize frequency hopping strategy parameters, and dynamic self-adaptive adjustment of interference avoidance is achieved. Complex
electromagnetic environment interference can be effectively dealt with, and the communication stability of the wireless mouse and the use experience of a user are remarkably improved.