PROBE： NOISE-AND-ROTATION RESISTANCE OF HOPFIELD NEURAL NETWORK IN IMAGED TRAFFIC SIGN RECALL

• 作 者: Chen Ken Yang Shoujian Celal B
• 机 构: CollegeofInformationScienceandEngineering,CollegeofEngineering
• 出 处: 电子科学学刊：英文版
• 发表日期: 2013年2期
• 基金项目: Supported by the Natural Science Foundation of Zhejiang Province （No. 2010A610105）.

This paper examines the noise and rotation resistance capacity of Hopfield Neural Network (HNN) given four corrupted traffic sign images. In the study, Signal-to-Noise Ratio (SNR), recall rate and pattern complexity are defined and employed to evaluate th