之前說到來至加拿大的算賬機器人用到CouchDB是一個開源的面向文檔的數據庫管理系統，PC-28算賬機器人軟件用到的CouchDB的問

 

然而也用到了OpenCV可以運行在Linux、Windows、Android和Mac OS操作系統上。

 

官方：http://pc16888.com

 

OpenCV的全稱是：Open Source Computer Vision Library。OpenCV是一個基于BSD許可（開源）發行的跨平臺計算機視覺庫，可以運行在Linux、Windows、Android和Mac OS操作系統上。

 

過程提示：

 

1001622374850687%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%------------------------------------------------------------------------------------%

%************************************** Filter **************************************%

%------------------------------------------------------------------------------------%

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% Date:2018.8.25

% Author:flypassion

% Version:1.0

clear all

close all

clc

%% Parameter Interface

Frequence0 = 60; %單位：Hz

Frequence1 = 130; %單位：Hz

Frequence2 = 1e3; %單位：Hz

SampleFre = 4e3; %單位：Hz

SampleLen = SampleFre; %采樣點數

%% Main

%-------------------產生三路信號

t = 0:1/SampleLen:1/SampleFre*(SampleLen-1);

SignalData0 = sin(2*pi*Frequence0*t);

SignalData1 = sin(2*pi*Frequence1*t);

SignalData2 = sin(2*pi*Frequence2*t);

SignalData3 = SignalData0+SignalData1+SignalData2;

figure;hold on

plot(t(1:150),SignalData0(1:150),'b')

plot(t(1:150),SignalData1(1:150),'r')

plot(t(1:150),SignalData2(1:150),'k')

hold off

figure;plot(t(1:150),SignalData3(1:150))

title('三路信號求和')

%-------------------頻譜分析

FFT_Data = fft(SignalData3);

Amplitude = abs(FFT_Data);

Amplitude = Amplitude/length(Amplitude);

Amplitude(2:end) = 2*Amplitude(2:end);

Frequence = (0:(length(Amplitude)/2-1))/length(Amplitude)*SampleFre;

figure;plot(Frequence,Amplitude(1:length(Frequence)))

title('三路信號疊加頻譜')

%-------------------低通濾波

LPF_Coe = load('LPF_60M.mat');

LPF_Data = filter(LPF_Coe.LPF_60M,1,SignalData3);

figure;plot(t,LPF_Data)

title('低通濾波之后的波形')

%-------------------低通濾波之后頻譜分析

FFT_LPF_Data = fft(LPF_Data);

Amplitude_LPF = abs(FFT_LPF_Data);

Amplitude_LPF = Amplitude_LPF/length(Amplitude_LPF);

Amplitude_LPF(2:end) = 2*Amplitude_LPF(2:end);

Frequence = (0:(length(Amplitude_LPF)/2-1))/length(Amplitude_LPF)*SampleFre;

figure;plot(Frequence,Amplitude_LPF(1:length(Frequence)))

title('低通濾波之后的頻譜')

%-------------------帶通濾波

BPF_Coe = load('BPF_130M.mat');

BPF_Data = filter(BPF_Coe.BPF_130M,1,SignalData3);

figure;plot(t,BPF_Data)

title('帶通濾波之后的波形')

%-------------------帶通濾波之后頻譜分析

FFT_BPF_Data = fft(BPF_Data);

Amplitude_BPF = abs(FFT_BPF_Data);

Amplitude_BPF = Amplitude_BPF/length(Amplitude_BPF);

Amplitude_BPF(2:end) = 2*Amplitude_BPF(2:end);

Frequence = (0:(length(Amplitude_BPF)/2-1))/length(Amplitude_BPF)*SampleFre;

figure;plot(Frequence,Amplitude_BPF(1:length(Frequence)))

title('帶通濾波之后的頻譜')