Sampling and reconstruction are two of the most essential and widely used operations in signal-processing systems. In this lesson you will be introduced to the roles of sampling and reconstruction in signal processing and the questions that will be addressed in subsequent lessons.
All signals in the physical world, e.g., sound or light intensity, have continuous independent variables, such as time or location. Computers can only manipulate numbers. Sampling converts a signal with a continuous independent variable to one with a discrete independent variable, that is, to a sequence of numbers. This allows use of a computer for processing. Reconstruction converts a sequence of numbers representing a signal with a discrete independent variable to a signal with a continuous independent variable.
Sampling involves a mixture of continuous- and discrete-time signals. The Fourier transform is normally used to analyze the impact of such mixtures and answer questions about how frequently one should sample.
