【摘要】 文中提出了一种基于模糊神经网络方法的味觉信号识别模型，利用小波变换实现了对传感器所采集的味觉信号进行数据压缩及特征抽取，以模糊神经网络作为味觉信号的识别工具，并利用遗传算法训练网络权值、优化隶属度函数．文中实现了对酸、甜复合味觉信号的数据处理和模糊识别．实验结果表明了将模糊神经网络引入到味觉信号模糊识别的可行性和有效性更多还原

【Abstract】 An identification model of taste signals is developed based on fuzzy neural networks.The data compression and feature extraction of the sampled taste signals obtained using taste sensors are implemented employing wavelet transformation.Fuzzy neural networks are used to identify the taste signals.The training of network weights and the optimization of membership functions are conducted employing genetic algorithms.The data processing and fuzzy identification of mixed acid and sweet taste signals are realized.Simulated experimental results show that it is feasible and effective to introduce fuzzy neural networks into the fuzzy identification of taste signals.更多还原