Memristor is defined as the fourth basic electronic element, the studies on its models exhibit diversity. Now, the matching extent between memristor model and natural memristor has received researchers' wide attention. A new memristor model is proposed by changing the ion diffusion term of the WOx memristor, namely, adding another two internal state variables τ and μ which denote the relaxation time and retention, respectively, and the improved model can simulate natural memristor better. Firstly, the new one is able to not only describe the general characteristics of a memrsitor, but also capture the memory loss behavior. In addition, the new memristor can be considered as a neural synapse, under the action of the input pulses with different amplitudes, duration and intervals, the spike rate dependent plasticity, short-term plasticity (STP), and long-term plasticity (LTP) are analyzed, and the ''learning experience'' phenomenon which is very similar to the biological system is discovered, most of which is due to the back diffusion of the oxygen vacancies during the intervals of the input pulses which are caused by the concentration difference. Moreover, an exponential decay equation is built to describe the relaxation process of STP. Finally, taking into consideration the relationship between temperature and ion diffusion coefficient, the effect of temperature on the relaxation process of STP is discussed. Experimental results show that the new memristor model can better match the actual behavior characteristics, and more suitably acts as a synapse for being applied to neuromorphic systems.