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16

Digital Filtering

This chapter introduces the concept of filtering, compares analog and digital filters, discusses Finite Infinite Response (FIR) and Infinite Impulse Response (IIR) filters, and helps you determine how to choose the most appropriate digital filter.

What Is Filtering?

Filtering is the process by which the frequency content of a signal is altered. The implicit assumption is that the signal content of interest is separable from the raw signal. Classical linear filtering assumes that the signal content of interest is distinct from the remainder of the signal in the frequency domain (Fourier Transform). Filtering is one of the most commonly used signal processing techniques. For example, consider the bass and treble controls on your stereo system. The bass control alters the low-frequency content of a signal, and the treble control alters the high-frequency content. By varying these controls, you are filtering the audio signal. Removing noise and performing decimation (lowpass filtering the signal and reducing the sample rate) are other filtering applications.

Advantages of Digital Filtering over Analog Filtering

An analog filter has an analog signal at both its input and its output. Both the input, x(t), and output, y(t), are functions of a continuous variable t and can have an infinite number of values. Analog filter design is about

50 years older than digital filter design. This type of filter design is often reserved for specialists because it requires advanced mathematical knowledge and understanding of the processes involved in the system affecting the filter. Modern sampling and digital signal processing tools have made it possible to replace analog filters with digital filters in applications that require flexibility and programmability, such as audio, telecommunications, geophysics, and medical monitoring.

© National Instruments Corporation

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LabVIEW Measurements Manual

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