The concepts of systems and Fourier transforms are easily applied to signals with more than one independent variable, or dimension. Images and movies are common multidimensional signals. This lesson shows you how to extend your knowledge of one dimensional continuous-time signals to two dimensional continuous-space signals. You will learn the form for two-dimensional convolution and the two-dimensional Fourier […]
This lesson introduces you to the steps that are involved in converting a signal from analog, or continuous time and continuous amplitude, format to a format that can be manipulated with a digital computer. Digital computers represent numbers using a finite number of bits. This implies that only a finite number of signal levels are […]
Quantization introduces error between the original signal and the quantized version. This error is viewed as a noise that contaminates the signal. In this lesson you will learn how quantization noise is usually modeled. You will also learn how the signal-to-quantization-noise ratio depends on the number of bits used to represent the signal.