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| clear; clc; n=3; wpname=’db3’; % [b,a]=butter(8,[5/100 99/100]); % load a1_1-1; load k301_1-4; % Data=filter(b,a,Data); Data=Data-mean(Data); Data=detrend(Data); wpt1=wpdec(Data,n,wpname); %对数据进行小波包分解 for i=1:2^n %wpcoef(wpt1,[n,i-1])是求第n层第i个节点的系数 E(i)=norm(wpcoef(wpt1,[n,i-1]),2);%求第i个节点的范数平方，其实也就是平方和 end % disp(‘每个节点的能量E(i)’); % E % disp(‘小波包分解总能量E_total’); E_total=sum(E); %求总能量 for i=1:2^n pfir(i)= E(i)/E_total;%求每个节点的概率 end pfir % load a1_1-2; load k302_1-4; % Data=filter(b,a,Data); Data=Data-mean(Data); Data=detrend(Data); wpt2=wpdec(Data,n,wpname); %对数据进行小波包分解 for i=1:2^n %wpcoef(wpt1,[n,i-1])是求第n层第i个节点的系数 E(i)=norm(wpcoef(wpt2,[n,i-1]),2);%求第i个节点的范数平方，其实也就是平方和 end E_total=sum(E); %求总能量 for i=1:2^n psec(i)= E(i)/E_total;%求每个节点的概率 end psec % load a1_1-4; load k303_1-4; % Data=filter(b,a,Data); Data=Data-mean(Data); Data=detrend(Data); wpt3=wpdec(Data,n,wpname); %对数据进行小波包分解 for i=1:2^n %wpcoef(wpt1,[n,i-1])是求第n层第i个节点的系数 E(i)=norm(wpcoef(wpt3,[n,i-1]),2);%求第i个节点的范数平方，其实也就是平方和 end E_total=sum(E); %求总能量 for i=1:2^n pthi(i)= E(i)/E_total;%求每个节点的概率 end pthi |
格式：
y = detrend(x) % 消除时间序列中的线性趋势项
y = detrend(x,’constant’) % 消除时间序列中的均值
y = detrend(x,’linear’,bp) % 分段消除时间序列中的线性趋势项,bp为分段点向量
如
y = detrend(x) % 消除时间序列中的线性趋势项
y = detrend(x,’constant’) % 消除时间序列中的均值
y = detrend(x,’linear’,bp) % 分段消除时间序列中的线性趋势项,bp为分段点向量
如
detrend的一个实例
sig = [0 1 -2 1 0 1 -2 1 0]; % 无线性趋势的信号
trend = [0 1 2 3 4 3 2 1 0]; % 有两段线性的趋势
x = sig+trend; % 将上面趋势叠加到信号上
y = detrend(x,’linear’,5) % 根据指定的分段点去除两段线性趋势
y =
-0.0000 1.0000 -2.0000 1.0000 0 1.0000 -2.0000 1.0000 0.0000
trend = [0 1 2 3 4 3 2 1 0]; % 有两段线性的趋势
x = sig+trend; % 将上面趋势叠加到信号上
y = detrend(x,’linear’,5) % 根据指定的分段点去除两段线性趋势
y =
-0.0000 1.0000 -2.0000 1.0000 0 1.0000 -2.0000 1.0000 0.0000
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