How to realize quadruple decimation of multistage CIC filter based on FPGA
Based on FPGA multi-stage CIC filter how to achieve quadruple decimation one, many novices are not very clear about this, in order to help you solve this problem, the following editor will explain in detail for you, people with this need can come to learn, I hope you can get something.
Before implementing multistage CIC filters, we first understand the principles of moving average filters, differentiators, integrators and comb filters. CIC filter has important applications in communication signal processing.
1 moving average filter
Fig. 18 structure of weighted moving average filter
The ownership coefficients of the moving average filter (Moving Average Filter) are all 1, which can smooth the signal and has low-pass characteristics.
Matlab:
Close all
Clear all
Clc
% set system parameter
Fs = 1000;% The frequency of the local oscillator signal
Fs = 44100;% sampling frequency
N = 24;% Quantitative bits
L = 8192
% Generating an input signal
T = 0:1/Fs: (1/Fs) * (Lmur1);% Generating the time series of sampling frequencies
Sc = sin (2*pi*fs*t);% a sinusoidal input signal that produces a random starting phase
% moving average filter
B = [1, 1, 1, 1, 1, 1]
A = 1
Sf=filter (bmaine a dint sc). * (1Compare 8)
Fig. 2 amplitude-frequency characteristics of moving average filter
2 differentiator
Fig. 3 structure of differentiator
The differentiator has a filter with weight coefficients of 1 and-1, and the filter has a simple high-pass amplitude-frequency response.
Y (k) = x (k)-x (k Mel 1)
Matlab:
Close all
Clear all
Clc
% set system parameter
Fs = 1000;% The frequency of the local oscillator signal
Fs = 44100;% sampling frequency
N = 24;% Quantitative bits
L = 8192
% Generating an input signal
T = 0:1/Fs: (1/Fs) * (Lmur1);% Generating the time series of sampling frequencies
Sc = sin (2*pi*fs*t);% a sinusoidal input signal that produces a random starting phase
% differential filter
B = [1jinmei 1]
A = 1
Sf=filter (bmeme arecrsc)
Fig. 4 amplitude-frequency response characteristics of differentiator
3 integrator
Fig. 5 structure of digital integrator
The digital integrator is an IIR filter with only one coefficient. The filter has the amplitude-frequency response characteristics of a low-pass filter.
Q (k) = p (k) + Q (k Mel 1)
Matlab:
Close all
Clear all
Clc
% set system parameter
Fs = 1000;% The frequency of the local oscillator signal
Fs = 44100;% sampling frequency
N = 24;% Quantitative bits
L = 8192
% Generating an input signal
T = 0:1/Fs: (1/Fs) * (Lmur1);% Generating the time series of sampling frequencies
Sc = sin (2*pi*fs*t);% a sinusoidal input signal that produces a random starting phase
% integral filter
B = 1
A = [1mai Mui 1]
Sf=filter (bmeme arecrsc)
Fig. 6 amplitude-frequency response characteristics of integrator
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