A very simple but effective method of obtaining a discrete equivalent to a continuous transfer function is to be found by extrapolation of the relation derived in Chapter 2 between the s-and z-planes. If we take the z-transform of samples of a continuous signal e( t), then the poles of the discrete transform
Discrete vs. Continuous Variables. If a variable can take on any value between two specified values, it is called a continuous variable; otherwise, it is called a discrete variable. Some examples will clarify the difference between discrete and continuous variables.
Just like variables, probability distributions can be classified as discrete or continuous. If a random variable is a discrete variable, its probability distribution is called a discrete probability distribution. An example will make this clear. Suppose you flip a coin two times.
These formulas for discrete equivalents are particularly simple and conve nient when expressed in state-variable form and used with a computer-aided design package. For example, suppose we have a vector-matrix description of a continuous design in the form of the equations x = Ax+Be, u = Cx+De.
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