-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathCvtKOMSMSVD.m
More file actions
193 lines (167 loc) · 7.49 KB
/
CvtKOMSMSVD.m
File metadata and controls
193 lines (167 loc) · 7.49 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
classdef CvtKOMSMSVD < handle
%% CvtKOMSM: Calculate KOMSM
properties (Access = public)
nDim;
nNum1;
nClass;
nSubDim1;
nOrthDim;
nSigma;
nAlpha;
nBeta;
X1;
A1;
E1;
C1;
D;
O;
W;
Flag;
end
methods (Access = public)
function obj = CvtKOMSMSVD(X1, nSubDim1,nSigma, varargin)
% Initialize instance variables
if nargin == 3
obj.nAlpha = 1;
obj.nBeta = 0;
elseif nargin == 4
obj.nAlpha = varargin{1};
obj.nBeta = 0;
elseif nargin == 5
obj.nAlpha = varargin{1};
obj.nBeta = varargin{2};
end
obj.Flag = 0;
obj.nSubDim1 = nSubDim1;
obj.nSigma = nSigma;
obj.X1 = X1;
[obj.nDim , obj.nNum1, obj.nClass] = size(X1);
obj.A1 = zeros(obj.nNum1,obj.nSubDim1,obj.nClass);
obj.E1 = zeros(obj.nSubDim1,obj.nClass);
obj.C1 = zeros(1, obj.nClass);
obj.D = zeros(obj.nSubDim1, obj.nSubDim1, obj.nClass,obj.nClass);
% Apply KPCA for each class
for I=1:obj.nClass
[obj.A1(:,:,I), ~, ~] = cvtKernelSVD(obj.X1(:,:,I),obj.nSigma, obj.nSubDim1);
end
% Generate non-linear subspace
for I1 = 1:obj.nClass
for I2 = I1:obj.nClass
K = cvtKernelGramMatrix(X1(:, :, I1), X1(:, :, I2), obj.nSigma);
if I1 == I2
obj.D(:,:,I1,I2) = eye(obj.nSubDim1,obj.nSubDim1);
else
obj.D(:,:,I1,I2) = obj.A1(:,:,I1)'*K* obj.A1(:,:,I2);
obj.D(:,:,I2,I1) = obj.D(:,:,I1,I2)';
end
end
end
obj.D = reshape(permute(obj.D,[1,3,2,4]), obj.nSubDim1 * obj.nClass, obj.nSubDim1 * obj.nClass);
[B,obj.W] = eig(obj.D);
obj.W = diag(obj.W/trace(obj.W));
[obj.W ind] = sort(obj.W,'descend');
B=B(:,ind);
obj.nOrthDim = find(cumsum(obj.W)/sum(obj.W)>=obj.nAlpha, 1 );
B=B(:,1:obj.nOrthDim);
obj.W = obj.W(1:obj.nOrthDim);
% Generate Kernel Orthogonal matrix
obj.O = diag(1./(obj.W+obj.nBeta))*B';
end
function [V2 E2 C2 A2 ] = TransformS(obj, X2,nSubDim2)
nSize = size(X2);
X2=X2(:,:,:);
[tmp, nNum2,nSet2] = size(X2);
A2 = zeros(nNum2,nSubDim2,nSet2);
E2 = zeros(nSubDim2,nSet2);
C2 = zeros(1,nSet2);
for I=1:nSet2
[A2(:,:,I) ,~ , ~] = cvtKernelSVD(X2(:,:,I),obj.nSigma,nSubDim2);
end
V2 = zeros(obj.nOrthDim,nSubDim2,nSet2);
for J = 1:nSet2
a = zeros( obj.nSubDim1, nNum2,obj.nClass);
for I = 1:obj.nClass
Z = cvtKernelGramMatrix(obj.X1(:, :, I), X2(:, :, J), obj.nSigma);
a(:,:,I) = obj.A1(:,:,I)' * Z;
end
a = permute(a,[1,3,2]);
a = reshape(a,size(a,1)*size(a,2),size(a,3));
V2(:,:,J) = orzGSO(obj.O*a*A2(:,:,J), nSubDim2);
end
V2 = reshape(V2,[obj.nOrthDim,nSubDim2,nSize(3:end),1]);
end
function [V2 E2 C2 Y2 ] = TransformV(obj, X2, nSubDim2)
% ���������������������������������������������������������������?������������������?�?
% ������������������������ ?�?PCA
nSize = size(X2);
X2=X2(:,:,:);
[tmp nNum2,nSet2] = size(X2);
Y2 = zeros(obj.nOrthDim,nNum2,nSet2);
for J=1:nSet2
a = zeros( obj.nSubDim1,nNum2,obj.nClass);
for I = 1:obj.nClass
Z = cvtKernelGramMatrix(X1(:, :, I), X2(:, :, J), obj.nSigma);
a(:,:,I) = obj.A1(:,:,I)' * Z;
end
a = permute(a,[1,3,2]);
a = reshape(a,obj.nSubDim1*obj.nClass,nNum2);
Y2(:,:,J) = obj.O*a;
end
V2 = zeros(obj.nOrthDim,nSubDim2,nSet2);
E2 = zeros(nSubDim2,nSet2);
C2 = zeros(nSet2);
for J=1:nSet2
[tmp V2(:,:,J) E2(:,J) C2(J)] = cvtPCA(Y2(:,:,J),nSubDim2,'R');
end
Y2 = reshape(Y2,[obj.nOrthDim,nNum2,nSize(3:end),1]);
V2 = reshape(V2,[obj.nOrthDim,nSubDim2,nSize(3:end),1]);
end
function [V2 E2 C2 Y2 ] = TransformU(obj, X2, nSubDim2)
% ���������������������������������������������������������������?������������������?�?
% ������������������������ ?�?������?�??��������� ?�?PCA
nSize = size(X2);
X2=X2(:,:,:);
[tmp nNum2,nSet2] = size(X2);
Y2 = zeros(obj.nOrthDim,nNum2,nSet2);
for J=1:nSet2
a = zeros( obj.nSubDim1,nNum2,obj.nClass);
for I = 1:obj.nClass
Z = cvtKernelGramMatrix(X1(:, :, I), X2(:, :, J), obj.nSigma);
a(:,:,I) = obj.A1(:,:,I)' * Z;
end
a = permute(a,[1,3,2]);
a = reshape(a,obj.nSubDim1*obj.nClass,nNum2);
Y2(:,:,J) = obj.O*a;
% Y2(:,:,J) = a;
end
Y2 = CvtNormalize(Y2);
V2 = zeros(obj.nOrthDim,nSubDim2,nSet2);
E2 = zeros(nSubDim2,nSet2);
C2 = zeros(nSet2);
for J=1:nSet2
[tmp V2(:,:,J) E2(:,J) C2(J)] = cvtPCA(Y2(:,:,J),nSubDim2,'R');
end
Y2 = reshape(Y2,[obj.nOrthDim,nNum2,nSize(3:end),1]);
V2 = reshape(V2,[obj.nOrthDim,nSubDim2,nSize(3:end),1]);
end
function [Y2] = Transform(obj, X2)
% ���������������������������������������������������?�??�?�
% ������������������������
nSize = size(X2);
X2=X2(:,:,:);
[tmp nNum2,nSet2] = size(X2);
Y2 = zeros(obj.nOrthDim,nNum2,nSet2);
for J=1:nSet2
a = zeros( obj.nSubDim1,nNum2,obj.nClass);
for I = 1:obj.nClass
Z = cvtKernelGramMatrix(obj.X1(:, :, I), X2(:, :, J), obj.nSigma);
a(:,:,I) = obj.A1(:,:,I)' * Z;
end
a = permute(a,[1,3,2]);
a = reshape(a,obj.nSubDim1*obj.nClass,nNum2);
Y2(:,:,J) = obj.O*a;
end
Y2 = reshape(Y2,[obj.nOrthDim,nNum2,nSize(3:end),1]);
end
end
end