I came across this example the stream processing chapter of a programming book that I'm reading:
Streams as signals
We began our discussion of streams by describing them as computational analogs of the signals in signal-processing systems. In fact, we can use streams to model signal-processing systems in a very direct way, representing the values of a signal at successive time intervals as consecutive elements of a stream. For instance, we can implement an integrator or summer that, for an input stream $x = (x_i)$, an initial value $C$, and a small increment $\mathrm{d}t$, accumulates the sum
$$S_i = C + \sum_{j=1}^{i} x_j \ \mathrm{d}t$$
and returns the stream of values $S = (S_i)$.
This corresponds to the following signal processing system:
I don't know anything about signal processing, so I'm not sure quite sure how to interpret the formula shown above for finding $S_i$.
At first I thought it was just the approximation of the solution to the definite integral $\int_0^i f(t) \: \mathrm{d}t$, i.e. $\sum_{j=0}^i x_j \, \Delta t$. But then that would mean $C = x_0 \Delta t$, whereas in the Henderson diagram shown above, the initial value $x_0$ is not scaled by anything.
So, what exactly is $C$? And is it correct to think about $S_i$ as an approximation of $\int_0^i f(t) \: \mathrm{d}t$, i.e. $\sum_{j=0}^i x_j \, \Delta t$?