Abstract

The term “filter” is used for LTI systems that alter their input signals in a prescribed way. Frequency-selective filters, the subject of this chapter, are designed to pass a set of desired frequency components from a mixture of desired and undesired components or to shape the spectrum of the input signal in a desired way. In this case, the filter design specifications are given in the frequency domain by a desired frequency response. The filter design problem consists of finding a practically realizable filter whose frequency response best approximates the desired ideal magnitude and phase responses within specified tolerances. The design of FIR filters requires finding a polynomial frequency response function that best approximates the design specifications; in contrast, the design of IIR filters requires a rational approximating function. Thus, the algorithms used to design FIR filters are different from those used to design IIR filters. In this chapter we concentrate on FIR filter design techniques while in Chapter 11 we discuss IIR filter design techniques. The design of FIR filters is typically performed either directly in the discrete-time domain using the windowing method or in the frequency domain using the frequency sampling method and the optimum Chebyshev approximation method via the Parks–McClellan algorithm. Study objectives After studying this chapter you should be able to: Understand how to set up specifications for design of discrete-time filters. Understand the conditions required to ensure linear phase in FIR filters and how to use them to design FIR filters by specifying their magnitude response. […] […]

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