The invention discloses an automatic fault detection and repair
integrated circuit design method based on a neural network. The method comprises the following steps: S1, obtaining and preprocessing operation data of an
integrated circuit; s2, analyzing the preprocessed data by using a trained neural
network model, and dynamically optimizing the model through an adaptive weight
pruning algorithm; s3, inputting circuit operation data in real time, automatically identifying fault types and positions, and storing fault information; s4, starting an automatic repair
mechanism based on the stored fault information, and generating a repair strategy through a multi-target collaborative optimization
algorithm; s5, logic reconstruction is executed according to the repair strategy, a redundant circuit and parameter adjustment are started, and a repair path is optimized through deep
reinforcement learning; s6, after repairing is completed, the neural
network model is used for detecting and verifying the repairing effect again; and S7, after the repair
verification is passed, updating the fault historical
database. According to the invention, the
automation level of fault detection and repair of the
integrated circuit is improved, and the reliability and efficiency of the
system are enhanced.