仿真研究表明，SVM具有优良的逆模型辨识能力，基于模糊控制补偿的支持向量机逆控制系统的动态性能好、跟踪精度高、鲁棒稳定性强。
Simulations demonstrate that SVM has good nonlinear approximation capability for inverse model, and the proposed control system has good dynamic and static performances as well as good robustness.
他有辨识好的歌声的能力。
仿真试验表明，利用P SO算法实现弹道辨识比BP算法辨识精度高，收敛性好。
Simulation results reveal that the proposed recognition technique based on PSO has higher precision of recognition and better convergence than those based on BP algorithm.
该方法对噪声鲁棒性好，能准确辨识各复合振荡模式，有助于电力系统强非线性模式分析，便于在线监测应用。
The proposed method can identify composite modes and strongly time-varying modes accurately with good noise robustness, catering for online analysis.
该方法对噪声鲁棒性好，能准确辨识各复合振荡模式，有助于电力系统强非线性模式分析，便于在线监测应用。
The proposed method can identify composite modes and strongly time-varying modes accurately with good noise robustness, catering for online analysis.
应用推荐