The rapid advancement of large-scale language models and artificial intelligence technologies has highlighted the importance of data processing efficiency. This study outlines a measurement optimization method for high-speed pulse equipment to accurately analyze the operating dynamics of ReRAM, a core hardware component for simulating neural networks. An optimized evaluation methodology combining connection compensation and a dual-channel configuration was established to minimize measurement errors caused by parasitic resistance and capacitance during pulse measurements using the Keithley 4200A-SCS and 4225-PMU modules, and to address HRS/LRS measurement errors caused by mismatches between the measurement range and source limits. The proposed precision measurement guidelines can be applied to the evaluation of semiconductor devices that require pulse measurements, such as transistors and DRAM.