>Given I have an input sequence [ 1 0 1 0 1 0 1 0 ], the DFS is x[n] =
>0.5 + 0.5*exp(j*pi*n).  The sampling (Ts) is 100 secs.
>
>Am I correct in saying that the spectral coefficient 0.5 at pi is
>equivalent to saying the DFS has a 0.5 peak every 200 secs?
>
>My reasoning is between adjacent x[n] samples a time Ts has passed
>which corresponds to 2*pi of the sampling period.  Therefore, half,
>i.e. pi, is 2 * Ts.
>
>Thanks,
>
>Aaron
>

In your statement you are confusing some things.
First of all the the discrete fourier series refers to
the fourier coefficients; saying: "the DFS has a 0.5 peak every
200 secs" is weird.  To say that 
".. the coefficient 0.5 is equivalent ...",
is also a bit confusing.
A spectral coefficient of 0.5 at the nyquist frequency indicates
that you have a component in your time domain signal which alternates
between -0.5/N and 0.5/N with every sample.
Maybe that has something to do with what you want to say.

I am just saying that it is hard to see whether your _thought_
is correct or not, since alone your formulation is flawed.

gr.
Bjoern

Given I have an input sequence [ 1 0 1 0 1 0 1 0 ], the DFS is x[n] =
0.5 + 0.5*exp(j*pi*n).  The sampling (Ts) is 100 secs.

Am I correct in saying that the spectral coefficient 0.5 at pi is
equivalent to saying the DFS has a 0.5 peak every 200 secs?

My reasoning is between adjacent x[n] samples a time Ts has passed
which corresponds to 2*pi of the sampling period.  Therefore, half,
i.e. pi, is 2 * Ts.

Thanks,

Aaron