Implementation of FIR Filters Using Rectangular Window

Ahlad Kumar

14711
 

Frequency response of band-reject filter with N=91, ω1=1.2 and ω2=2.1 is shown in Fig. 5.

Fig. 5: Frequency response of band-reject filter with N=91, ω1=1.2 and ω2=2.1

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Further, it may be observed that when ‘N’ increases, the width of the pass-band decreases and the slope of the transition band increases. The number of ripples increases in the pass-band with the amplitude of the end-ripple remaining the same, which however gets shifted towards the edge and finally out of the pass-band for larger values of ‘N.’ The width of the lobes decreases in the band-reject and the band-reject attenuation also increases with the increase in ‘N’ as more lobes enter the transition band. Moreover, the relative amplitude of the lobes remains constant.

Future applications
These filters can be used in a wide variety of applications like noise removal, selective passing of frequency contents in voice or any real-time waveforms. Using these filters’ sub-routine, you can design your own software for DSP applications or use this code to be translated in a hardware description language like Verilog or VHDL so it can be burnt into FPGA.


The author is an M. Tech from ABV-Indian Institute of Information Technology and Management, Gwalior, and B.Tech from Jamia Millia Islamia in New Delhi

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