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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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