phaspa2voltcoef.m

混沌时间序列的Volterra一步预测的Matlab程序

function [Un] = PhaSpa2VoltCoef(xn,p)
% 构造 Volterra 自适应 FIR 滤波器的输入信号矢量 Un
% [Un, len_filter] = PhaSpa2VoltCoef(xn, p)
% 输入参数：    xn           相空间中的点序列(每一列为一个点)
%               p            Volterra 级数阶数
% 输出参数：    Un           Volterra 自适应 FIR 滤波器的输入信号矢量 Un

[m,xn_cols] = size(xn);
Un(1,:) = ones(1,xn_cols);
h_cols_1 = 0;

for k = 1:p

    clear h;
    h(1,:) = zeros(1,k);
    i = 1;
    
    while h(i,end)<m-1
        i = i + 1;
        for j = k:-1:1
            if (h(i-1,j)==m-1)
                h(i,1:j+1) = ones(1,j+1) * (h(i-1,j+1)+1);
                h(i,j+2:end) = h(i-1,j+2:end);
                break;
            else
                h(i,1) = h(i-1,1)+1;
                h(i,2:end) = h(i-1,2:end);
            end
        end
    end
    h;
    h_cols_1 = [h_cols_1;h(:,1)];
    
    index = m - h;
    [index_rows,index_cols] = size(index);

    array = zeros(index_rows,index_cols);
    un = zeros(index_rows,xn_cols);
    for q = 1:xn_cols
        vector = xn(:,q);
        for u = 1:index_rows
            for v = 1:index_cols
                array(u,v) = vector(index(u,v));
            end 
        end
        un(:,q) = prod(array,2);
    end
    Un = [Un;un];
    clear un;
end

h_cols_1;
[temp,index_rows]  = sort(h_cols_1);
Un = Un(index_rows,:);