What is FIR filter ?

What is an FIR filter?

Depending on the form of the unit pulse response of the system, digital filters can be classified as→

Finite Duration Unit Pulse Response (FIR) Filters - If the impulse response of a digital filter is determined for some finite number of sample points, then these filters are called FIR digital filters. These filters can readily be designed to have constant delay as well as prescribed loss specifications. These filters can be designed by Fourier series method or numerical analysis methods. In the designing of FIR digital filters, window functions are also used.

 

Steps involved in FIR filter design

Many steps in designing the FIR filter are given as follows

(i) Filter specification may include stating the type of filter, for example, lowpass filter, the desired magnitude response, phase response, the tolerances we are prepared to accept, the sampling frequency, and the word length of the input data.

(ii) In coefficient calculation, we determine the coefficients of a transfer function H(z).

(iii) Realization involves converting the transfer function H(z) obtained into a suitable filter structure.

(iv) The next step is an analysis of finite word length effects. In this, we analyze the effect of quantizing the filter coefficients and the input data as well as the effect of carrying out the filtering operation using fixed word lengths on the filter performance.

 

 

(v) Implementation involves producing the software code or hardware code and performing the actual filtering. These five interrelated steps are shown above in fig. 

 

Advantages -

There are the following advantages of FIR filters -

(i) The FIR filters with exactly linear phases can be easily designed. It simplifies the approximation problem in many cases when one is interested in designing a filter that approximates an arbitrary magnitude response.

(ii) The linear phase filters are important for applications where frequency dispersion due to non-linear phase is harmful, for example, speed processing and data transmission.

(iii) For recursive and nonrecursive structures, the effective realization of FIR filters exists.

(iv) For nonrecursive realization of FIR filters round-off noise, which is inherent in realization with finite precision arithmetic, can easily be made small.

(v) Nonrecursively realized FIR filters are always stable.

 

Disadvantages -

There are the following disadvantages of FIR filters -

(i) A large value of order N the impulse response duration is required to adequately approximate sharp cut-off filters.

(ii) A large amount of processing is required to realize such filters when realized via slow convolution.

(iii) The delay of linear phase FIR filters need not always be an integer number of samples. (iv) The nonintegral delay can lead to problems in some signal processing applications.

 

What are the requirements to design an FIR filter?

The requirements for the design FIR filter are as follows-

(i) The filter should have a specific phase shift or group delay.

(ii) The filter should have a specific frequency response.

(iii) The filter should have a specific impulse response.

(iv) The filter should be causal, stable, and localized.

(v) The computational complexity of the filter should be low.

(vi) The filter should be implemented in particular hardware or software.

Do you dream of turning your thoughts and words into income ? join us now and become blogger now.

PUBLICBLOGS.IN