Implementation and Performance Comparison Study of 1-D and 2-D FIR Filter using MATLAB
Jyotsna Yadav1, Arpita Bharti2, Rohit Patel3, Mukesh Kumar4
1Jyotsna Yadav, M. Tech, SSET, SHIATS, Allahabad, India.
2Arpita Bharti, M. Tech, SSET, SHIATS, Allahabad, India.
3Rohit Patel, M. Tech, SSET, SHIATS, Allahabad, India.
4Mukesh Kumar, Assistant Professor, ECED, SSET, SHIATS Allahabad, India.
Manuscript received on January 17, 2013. | Revised Manuscript received on February 07, 2013. | Manuscript published on February 28, 2013. | PP: 533-535 | Volume-2 Issue-3, February 2013. | Retrieval Number: C1182022313/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: FIR filters have only a finite number of terms in their impulse response. These filters have a number of advantages over the IIR filter types. FIR filter is always stable, realizable, and provides a linear phase response under specific conditions. These characteristics make FIR filters attractive to many filter designers. However, the major disadvantage of FIR filters is that the number of coefficients needed to implement a specific filter is often much larger than for IIR designs. Finite Impulse Response (FIR) filter is a filter structure that can be used to implement almost any sort of frequency response digitally. An FIR filter is usually implemented by using a series of delays, multipliers, and adders to create the filter’s output. A Multirate digital signal processing is required in digital system where more than one Sampling Rate is required. This paper brings the performance comparison between the FIR designing methodologies like the 1-D, 2- D FIR Filters. In this paper 1-D, 2-D FIR filters using their operation have been implemented and simulated in the MATLAB and Simulink environment and their response has been studied in the waveforms. Simulation result shows that 2-D filter has increased computation speed as compared to 1-D, and is more efficient in reducing the noise in the signal.
Keywords: Digital Filters, FIR Filters, 2-D FIR Filters, MATLAB.