The role of neuron transfer function in artificial neural networks
神经元传输函数对人工神经网络动力学特性的影响

By analysis of local field distribution of the neurons in stationary state of associative memory neural networks, the role of the analog neuron transfer function in affecting the neural network performance is re-investigated. Different from the research done before, we find that the analog transfer function has no obvious advantages over the hard limit transfer function. Furthermore, analog transfer function sometimes produces a negative impact on certain functions of the network, such as the maximal storage capacity. We show that in pursuing the same performance a proper design rule is more essential than the choice of the transfer function.