Digital signal processing using Matlab

EXP. NO:7 IMPLEMENTATION OF LP AND HP FIR FILTER AIM: To implement LP FIR filter for a given sequence. Software: MATLAB THEORY: FIR filters are digital filters with finite impulse response. They are also known as non-recursive digital filters as they do not have the feedback An FIR filter has two important advantages over an TIR design: Firstly, there is no feedback loop in the structure of an FIR filter. Due to not having a feedback loop, an FIR filter is inherently stable. Meanwhile, for an IIR filter, we need to check the stability Secondly, an FIR filter can provide a linear-phase response. As a matter of fact, a lincar-phase response is the main advantage of an FIR filter over an IR design otherwise. for the same filtering specifications; an IR filter will lead to a lower order. FIR FILTER DESIGN An FIR filter is designed by finding the coefficients and filter order that meet certain specifications, which can be in the time-domain (e.g. a matched filter) and/or the frequency domain (most common). Matched filters perform a cross-correlation between the input signal and a known pulse-shape. The FIR convolution is a cross-correlation between the input signal and a time-reversed copy of the impulse-response. Therefore, the matched-filter's impulse response is "designed" by sampling the known pulse-shape and using those samples in reverse order as the coefficients of the filter When a particular frequency response is desired several different design methods are common: 1 Window design method 2. Frequency Sampling method Weighted least squares design WINDOW DESIGN METHOD In the window design method, one first designs an ideal IIR filter and then truncates the infinite impulse response by multiplying it with a finite length window function. The result is a finite impulse response filter whose frequency response is modified from that of the IIR filter TOUT Min. Step band Attention Matlab Command 21db B-FIRIN.We.borear) 250 B-FIRIN.Wahari) Window Transition width Narbe Approximate Exact values 1. Rectangular M M SI 6.in Bartlett M M en 62n Hanning M M ST 6611 Hamming M 1211 Hin Hackman M == " = =" 44db 3-FIRIN, Wohanning) db B-FIRIN.W.humming) 74db PIRIN,Ww.blackman) Algorithm: Step Step Step Step IV Step V Step V1 Step VII Enter the pass band frequency (f) and stop bund frequency) Od the sampling frequency length of window (1) Calculate the cut of frequency Use borear, haming, blackman Commands to design window. Design filter by using above parameters Find frequency response of the filtering matlab command from Plot the magnitude response and phase response of the filter MI dose all fp200 fq-300 f-1000 fus window blackman Erwinden IH WI-,1,12 wag, 1.0) plot(W/ uterugiate pane label pain in db)); sahel romaled frequency ullee.,2) plocWunded midlephant response of bende) Nabermained frequency IMPLEMENTATION OF HP FIR FILTER AIM: To implement HIP FIR filter for a given sequence Software: MATLAB lanritun de response op: labellinin dhe abelinomed frequency Step 1 Step II Step IV V Step Vi Step VII sple(2,1... plor/pande title(phase response ollp). yatlande: slabe normalized free); IMPLEMENTATION OF HP FIR FILTER AIM: To implement HP FIR filter for a given sequence Software: MATLAR Algorithm: Enter the pass band frequency (fp) and stop band frequency (fig : Get the sampling frequency (5), length of window) Step II Calculate cut off frequency Use boxcar, humming, Blackman Commands to design window Step Design filter by using above parameters. Find frequency response of the filter using matlab command frage. Plot the magnitude response and phase response of the filter che: dear alt: close all: -20; fp-300 [q-200 -1000, fu-2"pis: window-blackmanin.1): b-farfo.fn, high window): IH WI-freqrth, 1,128 subplot(2,1,1); plot(W/pias(); ting res of lpl): label in db-> xabel (normaled frequency plot/pande): title(phase resep labelude slabeloomed frequency EXP. NO:7 IMPLEMENTATION OF LP AND HP FIR FILTER AIM: To implement LP FIR filter for a given sequence. Software: MATLAB THEORY: FIR filters are digital filters with finite impulse response. They are also known as non-recursive digital filters as they do not have the feedback An FIR filter has two important advantages over an TIR design: Firstly, there is no feedback loop in the structure of an FIR filter. Due to not having a feedback loop, an FIR filter is inherently stable. Meanwhile, for an IIR filter, we need to check the stability Secondly, an FIR filter can provide a linear-phase response. As a matter of fact, a lincar-phase response is the main advantage of an FIR filter over an IR design otherwise. for the same filtering specifications; an IR filter will lead to a lower order. FIR FILTER DESIGN An FIR filter is designed by finding the coefficients and filter order that meet certain specifications, which can be in the time-domain (e.g. a matched filter) and/or the frequency domain (most common). Matched filters perform a cross-correlation between the input signal and a known pulse-shape. The FIR convolution is a cross-correlation between the input signal and a time-reversed copy of the impulse-response. Therefore, the matched-filter's impulse response is "designed" by sampling the known pulse-shape and using those samples in reverse order as the coefficients of the filter When a particular frequency response is desired several different design methods are common: 1 Window design method 2. Frequency Sampling method Weighted least squares design WINDOW DESIGN METHOD In the window design method, one first designs an ideal IIR filter and then truncates the infinite impulse response by multiplying it with a finite length window function. The result is a finite impulse response filter whose frequency response is modified from that of the IIR filter TOUT Min. Step band Attention Matlab Command 21db B-FIRIN.We.borear) 250 B-FIRIN.Wahari) Window Transition width Narbe Approximate Exact values 1. Rectangular M M SI 6.in Bartlett M M en 62n Hanning M M ST 6611 Hamming M 1211 Hin Hackman M == " = =" 44db 3-FIRIN, Wohanning) db B-FIRIN.W.humming) 74db PIRIN,Ww.blackman) Algorithm: Step Step Step Step IV Step V Step V1 Step VII Enter the pass band frequency (f) and stop bund frequency) Od the sampling frequency length of window (1) Calculate the cut of frequency Use borear, haming, blackman Commands to design window. Design filter by using above parameters Find frequency response of the filtering matlab command from Plot the magnitude response and phase response of the filter MI dose all fp200 fq-300 f-1000 fus window blackman Erwinden IH WI-,1,12 wag, 1.0) plot(W/ uterugiate pane label pain in db)); sahel romaled frequency ullee.,2) plocWunded midlephant response of bende) Nabermained frequency IMPLEMENTATION OF HP FIR FILTER AIM: To implement HIP FIR filter for a given sequence Software: MATLAB lanritun de response op: labellinin dhe abelinomed frequency Step 1 Step II Step IV V Step Vi Step VII sple(2,1... plor/pande title(phase response ollp). yatlande: slabe normalized free); IMPLEMENTATION OF HP FIR FILTER AIM: To implement HP FIR filter for a given sequence Software: MATLAR Algorithm: Enter the pass band frequency (fp) and stop band frequency (fig : Get the sampling frequency (5), length of window) Step II Calculate cut off frequency Use boxcar, humming, Blackman Commands to design window Step Design filter by using above parameters. Find frequency response of the filter using matlab command frage. Plot the magnitude response and phase response of the filter che: dear alt: close all: -20; fp-300 [q-200 -1000, fu-2"pis: window-blackmanin.1): b-farfo.fn, high window): IH WI-freqrth, 1,128 subplot(2,1,1); plot(W/pias(); ting res of lpl): label in db-> xabel (normaled frequency plot/pande): title(phase resep labelude slabeloomed frequency