**Sampling Theorem 1-D:**

One of the most important applications of digital filtering is the processing of sequences of samples derived from continuous or analog signals. This is made possible due to the results and implications of the sampling theorem.

This theorem can be stated as follows:

“A continuous analogue function x(t) which has a limited Fourier spectrum, that is a spectrum x(jω) such that x(jω) = 0 for ω > ω_{m}, is uniquely described from a knowledge of its values at uniformly spaced time instants T units apart, where T = 2π/ω_{s}, and ω_{s }≥ 2ω_{m}“

**Sampling Theorem 2-D:**

This theorem can be stated as follows.

A function of two variables, x(x_{1}, x_{2}) whose 2-D Fourier transform is equal to zero for ω_{1} > ω_{1m}, and ω_{2} > ω_{2m}, is uniquely determined by the values taken at uniformly spaced points in the x_{1} and x_{2} plane, if the spacing x_{1} and x_{2} satisfy the conditions x_{1} ≤ π/ω_{1m}, and x_{2} ≤ π/ω_{2m}.

**1-D Z-Transform:**

Given a sequence { x(n)} with -∞≤ n ≤∞, its Z-transform is defined as

where Z is a complex variable.

The Z-transform can be inverted and x(n) can be obtained as

where C is the counter clockwise closed contour in the region of convergence of X(Z) and encircling the origin of the Z-plane.