# What is the difference between t=n*Ts sampling vs impulse train sampling?

I know that if I sampling with impulse train so I get in the frequency plane X(f)*h(f) (when x(f) is my signal, * means convolution and h(f) is fourier transform of impulse train).

what the difference between this way to x(t=n*Ts) sampling way?

If I can get explenation in the "frequency plane" it will be great.

I cannot recall a meaningful difference between the ideal impulse train sampling and the uniform sampling relation indicated by the expression $$t_n = n T_s$$.
Given a continuous-time bandlimited signal $$x_c(t)$$, when you sample this with an ideal impulse train $$\delta_{T_s}(t) = \sum_k \delta(t - k T_s)$$, then the relation between the obtained discrete-time sequence $$x[n]$$ and the continuous-time signal will be given by :
$$x[n] = x_c(t_n) = x_c(n T_s)$$
• I think the only difference is that using deltas allows one to write the interpolator as a low-pass filter: if the filter impulse response is $\text{sinc}(t/T)$, and the input is $\sum x(nT) \delta(t-nT)$, then the Shannon interpolation formula follows immediately.