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equal() returns true if the two sequences are equal for the number of elements contained within the range [first,last) If the second sequence contains additional elements, those are not considered If we wish to guarantee that both sequences are equivalent, we need to write

If the set of all individuals in the database is referred to as I = {i1 , i2 , , ij } with J number of individuals, then for every individual i in I a set Si has to be extracted To achieve this, all the images in the database depicting individual i are marked as positives, and the ones not depicting that individual are marked as negatives Let the set of positive images be referred to as Pi (with L number of images) and let the set of negatives be referred to as N (with K number of images) Thus, Si = {G1i , G2,i , , Gmi }, Pi = {p1i , p2i , , pli }, and Ni = {n1i , n2i , , nki } are the sets of Gabor lters, positive images, and negatives images set, respectively, for the individual i The Distance Measure D.

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if ( vec1size() == vec2size() && equal( vec1begin(), vec1end(), vec2begin() );

or use the container equality operator, as in vec1==vec2 If the second container holds less elements than the first, and the algorithm should iterate past its end, the run-time behavior is undefined By default, the equality operator of the underlying element type is used for comparison; the second version applies pred

A parent trying to recognize an individual i with a Gabor lter set Si can be thought of as a transformation that projects all of the face images from the image space to a M-dimensional space, where the dimensions are de ned by the M Gabor lters in the set Si Thus, all of the images in the two sets Pi and Ni can be considered as points on this M-dimensional space Since the goal of the genetic algorithm is to nd the set Si that best distinguishes the individual i from others, in our method we search for the M-dimensional space (de ned by a parent) that best separates the points formed by the sets Pi and Ni Figure 5.

#include <algorithm> #include <list> #include <iostreamh> class equal_and_odd{ public: bool operator()( int val1, int val2 ) { return ( val1 == val2 && ( val1 == 0 || val1 % 2 )); } }; int main() { int ia[] = { 0,1,1,2,3,5,8,13 }; int ia2[] = { 0,1,1,2,3,5,8,13,21,34 }; bool res; // true: both are equal to the length of ia // generates: int ia[7] equal to int ia2[9] true res = equal( &ia[0], &ia[7], &ia2[0] ); cout "int ia[7] equal to int ia2[9] " ( res "true" : "false" ) "\n"; list< int, allocator > ilist( ia, ia+7 ); list< int, allocator > ilist2( ia2, ia2+9 ); // generates: list ilist equal to ilist2 true res = equal( ilistbegin(), ilistend(), ilist2begin() ); cout "list ilist equal to ilist2 " ( res "true" : "false" ) "\n"; // false: 0, 2, 8 are not equal and odd // generates: list ilist equal_and_odd() to ilist2 false res = equal( ilistbegin(), ilistend(), ilist2begin(), equal_and_odd() ); cout "list ilist equal_and_odd() to ilist2 " ( res "true" : "false" ) "\n"; return 0; } equal_range() template< class ForwardIterator, class Type > pair< ForwardIterator, ForwardIterator > equal_range( ForwardIterator first,

file:///F|/WinDDK/resources/CPPPrimer/c++primerhtm (1018 / 1065) [2001-3-29 11:32:15]

13 is an illustration of hypothetical set of face images projected on a two-dimensional space de ned by a set of 2 Gabor lters Si = {G0 , G1 } As shown in the gure, the measure D is the minimum of all the Euclidian distances between every positive and negative points..

ForwardIterator last, const Type &value ); template< class ForwardIterator, class Type, class Compare > pair< ForwardIterator, ForwardIterator > equal_range( ForwardIterator first, ForwardIterator last, const Type &value, Compare comp );

equal_range() returns a pair of iterators The first iterator represents the iterator value returned by lower_bound(); the second iterator represents the iterator value returned by upper_bound(); see the respective algorithms for a description of their semantics For example, given the following sequence:

Several accounting data collection methods are implemented in the industry. Examples are the polling model and the event-driven model. In the following sections we provide a short description for a few of these models.

int ia[] = {12,15,17,19,20,22,23,26,29,35,40,51};

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