(New page: Can we ever reconstruct a a signal by its sampling? No, we generally never can but we can approximate. 1. The easiest way to reconstruct a signal is by zero-order interpolation which loo...) |
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No, we generally never can but we can approximate. | No, we generally never can but we can approximate. | ||
| − | 1. The easiest way to reconstruct a signal is by zero-order interpolation which looks like step functions. | + | 1. The easiest way to "reconstruct" a signal is by zero-order interpolation which looks like step functions. |
<math> x(t) = \sum^{\infty}_{k = -\infty} x(kT) (u[t-kT]-u[t-(k+1)T])</math> | <math> x(t) = \sum^{\infty}_{k = -\infty} x(kT) (u[t-kT]-u[t-(k+1)T])</math> | ||
| − | 2. To step it up we can | + | 2. To step it up we can use 1st order interpolation. She gave an example about a kid going to an interview and they asked him if he has ever heard o splines and peace-wise polynomial functions and that is what this is. |
Revision as of 15:04, 10 November 2008
Can we ever reconstruct a a signal by its sampling? No, we generally never can but we can approximate.
1. The easiest way to "reconstruct" a signal is by zero-order interpolation which looks like step functions.
$ x(t) = \sum^{\infty}_{k = -\infty} x(kT) (u[t-kT]-u[t-(k+1)T]) $
2. To step it up we can use 1st order interpolation. She gave an example about a kid going to an interview and they asked him if he has ever heard o splines and peace-wise polynomial functions and that is what this is.
