【摘要】 将遗传算法的全局搜索能力与小波神经网络的强拟合与容错能力相结合,构造了遗传小波神经网络。对模拟和极谱信号处理的结果表明:由于该网络使用遗传算法优化了神经网络的参数,从而避免了网络陷入局部最小和选择网络参数时的人工参与,能够有效地进行滤噪和数据压缩,使神经网络用于化学信号处理的智能化程度得以提高。更多还原

【Abstract】 Combined the global search ability of genetic algorithm with the great fitting capacity of neural network,a signal processing methods,genetic wavelet neural network,is proposed.Then the method is applied to the compression and denoising of the simulated and polargraphic signals.The experimental results show that the method is effective for the data compression and noise elimination.The improper selection of network parameters and local optimal solution which often occurs in the training process of WNN is avoided because the parameter of WNN is optimized by GAs.The intellectualized level of artificial neural network applied in chemical signal processing has been improved ulteriorly.更多还原