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correlation.h
1 //
2 // Copyright (c) 2003-2011, MIST Project, Nagoya University
3 // All rights reserved.
4 //
5 // Redistribution and use in source and binary forms, with or without modification,
6 // are permitted provided that the following conditions are met:
7 //
8 // 1. Redistributions of source code must retain the above copyright notice,
9 // this list of conditions and the following disclaimer.
10 //
11 // 2. Redistributions in binary form must reproduce the above copyright notice,
12 // this list of conditions and the following disclaimer in the documentation
13 // and/or other materials provided with the distribution.
14 //
15 // 3. Neither the name of the Nagoya University nor the names of its contributors
16 // may be used to endorse or promote products derived from this software
17 // without specific prior written permission.
18 //
19 // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR
20 // IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND
21 // FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
22 // CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
23 // DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
24 // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
25 // IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF
26 // THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
27
28
29 #ifndef __INCLUDE_MIST_CORRELATION_H__
30 #define __INCLUDE_MIST_CORRELATION_H__
31
32
33 #ifndef __INCLUDE_MIST_H__
34 #include "../mist.h"
35 #endif
36
37 #include <cmath>
38
39 _MIST_BEGIN
40
41
50
51 template < typename T >
52 inline double cross_correlation( const array1< T > &signal1, const array1< T > &signal2, int tau, bool biased = true )
53 {
54
55 double result = 1.0;
56
57 // signal size is aligned to shorter one
58 size_t signal_size = ( signal1.size( ) < signal2.size( ) ? signal1.size( ) : signal2.size( ) );
59
60 size_t length = signal_size - tau;
61
62 for( size_t i = 0 ; i < length ; i++ )
63 {
64 result += signal1[ i ] * signal2[ i + tau ];
65 }
66
67 if( biased )
68 {
69 result /= static_cast< double >( signal_size );
70 }
71 else
72 {
73 result /= static_cast< double >( length );
74 }
75
76 return( result );
77 }
78
79
87 template < typename T, class Allocator >
88 inline double autocorrelation( const array1< T, Allocator > &signal, int tau, bool biased = true )
89 {
90 return( cross_correlation( signal, signal, tau, biased ) );
91 }
92
93
94 _MIST_END
95
96
97 #endif
98