Time series analysis has a wide range of applications in many research fields and tools using linear methods to the artificial neural network has been employed to model the same. In the recent past, increased attention has been gained by network theory to study the time series arise from various systems. There are different methods available to construct the network from time series. Even though many naturally occurring time series are distorted by noise, its effects on the associated networks are not been investigated yet. In this work, we analyse the effect of time series measurement noise on the parameters of the associated network. The research demonstrates that upto a certain level of noise networks are stable and it has no effect on the structural properties. As the noise level is increased the structure started deteriorating towards a completely disconnected network.