%AOLMM多步預(yù)測函數(shù)
function [FChaosPredict] = FunctionChaosPredict(Data,N,mtbp,deltaT,tao,d,MaxStep)
%Data是一維信號時間序列，N是信號數(shù)據(jù)長度，mtbp,deltaT,tao,d分別是重構(gòu)相空間的平均時間序列、采樣周期、時延及嵌入維

roll=Data;%取橫搖數(shù)據(jù)
M = N - (d - 1)*tao;
for i = 1 : M
    for j = 1 : d
        MatrixX(i,j) = roll(i + (j - 1)*tao);
    end
end

%計(jì)算相空間中第M點(diǎn)與各點(diǎn)的距離

%用最小二乘法計(jì)算a[],b[]
for step=1:1:MaxStep
    x=MatrixX(1:M-1-step,:);
    y=MatrixX(1+step:M-1,:);
    xt=MatrixX(M,:);
    yy=calculatey(x,y,xt); 
   
    
    

%誤差修正
%     if M-tao+step+(d-1)*tao < N+1
%         for j=1:d-1
%             err(j)=MatrixX(M + step,j)-roll(M+step+(j-1)*tao);
%         end
%         ppp=1:d-1;ttt=err;neterr=newrbe(ppp,ttt);xxx=2:d;errp=sim(neterr,xxx);
%         PredictedData(step) = MatrixX(M + step,d) - errp(d-1);
%         roll(N+step)=PredictedData(step);
%     else    PredictedData(step) = MatrixX(M + step,d);
%     end%        roll(N+k)=PredictedData(k);
%  PredictedData(step) = MatrixX(M + step,d);
% FChaosPredict(step) = PredictedData(step);
 FChaosPredict(step) = yy(end);
end