A Novel Dynamic Evolutionary Model Integrating Discrete Hopfield Neural Networks With Satisfiability Problems And Its Applications In Image Encryption And Decryption - Feng, Caicai (2025)
This thesis proposes a series of innovative DHNN-SAT variants and their applications. To address the inefficiency of traditional DHNN-SAT networks in solving SAT problems with dynamic constraints, a Dynamically Evolving Discrete Hopfield-SAT Neural Network with a flexible and scalable architecture is specifically designed. To tackle challenges posed by varying network scales and logical complexities, an optimized network based on a Crow Search Algorithm-guided Fuzzy Clustering Hybrid Method is proposed.