The invention discloses a memristor-based perceptron neural network circuit and an adjusting method thereof. The circuit comprises a memristor module, a weight conversion module, a net input module and a mapping function module, wherein the memristor module is connected with the weight conversion module, the weight conversion module is connected with the net input module, and the net input moduleis connected with the mapping function module. According to the method, firstly, an image of a resistance value and time relation of the memristor is adjusted to be approximate to a straight line, andthen an image of a weight value and time relation is adjusted to be approximate to a straight line. The memristor resistance value which is linearly changed can more accurately replace the synaptic weight value of the neural network, and the trained synaptic weight value of the neural network is stored by utilizing the resistance value of the memristor, so that the conversion between the memristor resistance value and the neuron synaptic weight value is realized, and the problem that a traditional neuron circuit cannot accurately adjust the synaptic weight value is solved.