Shannon's Sampling Theorem

$ \def \hieruit {\quad \Longrightarrow \quad} \def \slechts {\quad \Longleftrightarrow \quad} \def \sinc {\operatorname{sinc}} $ We are going to consider a uniform comb of sinc functions. The width $\,\sigma\,$ of such a sinc function is defined, rather arbitrary, as the place most close to $\,x=0\,$ where it is zero: $$ \sinc(q\,\sigma) = 0 \hieruit q\,\sigma = \pi \hieruit q = \frac{\pi}{\sigma} $$ And this function must be normed: $$ \int_{-\infty}^{+\infty} \sinc\left(\frac{\pi}{\sigma} x\right) \, dx = \frac{\sigma}{\pi} \int_{-\infty}^{+\infty} \sinc\left(\frac{\pi}{\sigma} x\right) \, d\left(\frac{\pi}{\sigma} x \right) = \frac{\sigma}{\pi} \pi = \sigma $$ So the normed sinc function with spread $\,\sigma\,$ is: $$ \frac{1}{\sigma} \sinc\left(\frac{\pi}{\sigma} x\right) $$ In order to be able to proceed, the Fourier integral of it shall be calculated: $$ \frac{1}{\sigma} \int_{-\infty}^{+\infty} \sinc\left(\frac{\pi}{\sigma} x\right) \cos(y x)\, dx = \frac{1}{\sigma} \frac{\sigma}{\pi} \int_{-\infty}^{+\infty} \sinc(\xi) \cos\left(\left[\frac{\sigma}{\pi}y\right] \xi\right) \, d\xi $$ Where we have put $\,\pi x/\sigma = \xi\,$. The latter outcome is equal to a block function $\,B_\sigma (y)\,$, where: $$ B_\sigma (y) = \left\{ \begin{array}{lll} 0 & \mbox{for} & \sigma/\pi y < -1 \\ \pi/\pi & \mbox{for} & -1 < \sigma/\pi y < +1 \\ 0 & \mbox{for} & +1 < \sigma/\pi y \end{array} \right. $$ Written otherwise: $$ B_\sigma (y) = \left\{ \begin{array}{lll} 0 & \mbox{for} & y < -\pi/\sigma \\ 1 & \mbox{for} & -\pi/\sigma < y < +\pi/\sigma \\ 0 & \mbox{for} & +\pi/\sigma < y \end{array} \right. $$ Conclusion - remember that $\,\omega = 2\pi/\Delta\,$: $$ \sum_{L=-\infty}^{+\infty} \frac{\Delta}{\sigma} \sinc\left(\frac{\pi}{\sigma}\left[ x - L \Delta \right]\right) = 1 + 2 \times \sum_{k=1}^\infty B_\sigma(k\omega) \cos(k\omega x) $$

The right hand side is exactly equal to one iff for all $\,k > 1\,$: $$ +\pi/\sigma < k\omega \slechts \pi \frac{\Delta}{2\pi} < \sigma \slechts \sigma > \frac{\Delta}{2} $$ A true miracle has happened. There is no error present, at all, in the following formula. Which thus holds exactly, for any $\,\sigma > \Delta/2\,$: $$ \sum_{k=-\infty}^{+\infty} \frac{\Delta}{\sigma} \sinc\left(\frac{\pi}{\sigma}\left[ x - k \Delta \right]\right) = 1 $$ Where have we seen this before .. ? Let $\,f(x) = 1$ and $f_k = f(k\Delta)\,$ and do a trivial rewrite: $$ \sum_{k=-\infty}^{+\infty} \frac{\Delta}{\sigma}\, f_k \, \sinc\left(\frac{\pi}{\sigma}\left[ x - k \Delta \right]\right) = f(x) $$ Now take a look at Shannon's Sampling Theorem. It should be obvious that there exists a correspondence with our own theory. It is also clear that the Special Theory of Continuity can, in principle, be modified as to include general function behaviour as well: $\,f(x) \neq 1\,$. And there is a section Nonuniform sampling in that web page, where we can read about a second item on our To Do list: the sampling theory of Shannon can be generalized for the case of nonuniform samples.