Download PDF by B. V. K. Vijaya Kumar: Correlation Pattern Recognition

By B. V. K. Vijaya Kumar

ISBN-10: 0521571030

ISBN-13: 9780521571036

Correlation is a strong and common procedure for development acceptance and is utilized in many functions, similar to computerized objective popularity, biometric popularity and optical personality popularity. The layout, research and use of correlation trend popularity algorithms calls for historical past details, together with linear structures concept, random variables and techniques, matrix/vector tools, detection and estimation thought, electronic sign processing and optical processing. This publication offers a wanted assessment of this various heritage fabric and develops the sign processing concept, the trend acceptance metrics, and the sensible program information from simple premises. It exhibits either electronic and optical implementations. It additionally includes expertise offered by means of the group that built it and contains case stories of important curiosity, akin to face and fingerprint reputation. compatible for graduate scholars taking classes in development reputation concept, while attaining technical degrees of curiosity to the pro practitioner.

Show description

Read or Download Correlation Pattern Recognition PDF

Best computer vision & pattern recognition books

Get Geometric computations with Clifford algebras PDF

This monograph-like anthology introduces the recommendations and framework of Clifford algebra. It offers a wealthy resource of examples of the way to paintings with this formalism. Clifford or geometric algebra exhibits powerful unifying facets and became out within the Sixties to be a such a lot enough formalism for describing diversified geometry-related algebraic structures as specializations of 1 "mother algebra" in a number of subfields of physics and engineering.

Read e-book online Pattern Recognition with Neural Networks in C++ PDF

The addition of synthetic community computing to standard development popularity has given upward push to a brand new, assorted, and extra strong method that's provided during this useful consultant to the applying of man-made neural networks. the cloth lined within the publication is obtainable to operating engineers with very little particular historical past in neural networks.

Wavelets mit Anwendungen in Signal- und Bildverarbeitung by Jöran Bergh, Fredrik Ekstedt, Martin Lindberg, M. Stern PDF

Gelungene Kombination aus Monografie und Handbuch: Sie spricht Leser an, die sich mit den grundlegenden mathematischen Ideen und Techniken der Wavelets vertraut machen und zugleich wissen m? chten, wie die Theorie derzeit angewendet wird. Das Buch setzt Kenntnisse ? ber Anwendungen der linearen Algebra, der Fourierreihen und Fourierschen Integrale voraus, weitere Kenntnisse sind ebenso w?

Read e-book online Discrete Geometry for Computer Imagery: 15th IAPR PDF

This booklet constitutes the refereed lawsuits of the fifteenth IAPR foreign convention on Discrete Geometry for computing device Imagery, DGCI 2009, held in Montr? al, Canada, in September/October 2009. The forty two revised complete papers have been conscientiously reviewed and chosen from a variety of submissions. The papers are equipped in topical sections on discrete form, illustration, acceptance and research; discrete and combinatorial instruments for picture segmentation and research; discrete and combinatorial Topology; versions for discrete geometry; geometric transforms; and discrete tomography.

Additional resources for Correlation Pattern Recognition

Sample text

Thus the PDF of y can be related to the PDF of x as follows: fY ðyÞ ¼ 1 À À1 Á fX A y jAj (2:104) Applying the above result and the N-variate Gaussian PDF in Eq. 101), we can see that the transformed random vector is also Gaussian, but with a new mean vector and new covariance matrix. 5 Probability and random variables ! ÁT À1 À À1 Á 1 1 1 À À1 qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi exp À A y À mX CX A y À mX fY ðyÞ ¼ 2 jAj ð2pÞN jCX j ! 1 1 T À1 ¼ qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi exp À ðy À mY Þ CY ðy À mY Þ 2 ð2pÞN jCY j 45 (2:105) where mY ¼ AmX and CY ¼ ACX AT The above result clearly shows that the result of an invertible affine transformation is also a Gaussian vector.

0]) as the eigenvectors. Let E denote a square matrix whose columns are ei, the normalized eigenvectors, and let L denote a diagonal matrix whose diagonal entries are the N eigenvalues. Then Eq. , A ¼ ET. If y ¼ Ax, then the new covariance is a diagonal matrix as shown below. CY ¼ ACX AT ¼ ET CX E ¼ ET EL ¼ L ¼ Diagfl1 ; l2 ; : : : ; lN g (2:108) Thus, using A ¼ ET results in new RVs y that are uncorrelated since the new covariance matrix is diagonal. If the random vector x is Gaussian, then A ¼ ETx is also Gaussian since the transformation is linear.

This experiment has a random outcome in that the output can be any one of the six numbers. We define an event as a set containing some of these outcomes. , {2, 4, 6}). , the set with no elements in it. Probability theory provides a framework to define probabilities of such events. 5 Probability and random variables 29 every event. The probability of null event 1 is zero and the probability of the sample set S is one, because the set S includes all possible outcomes. We also need a method to determine the probabilities of more complicated events such as {A \ B}.

Download PDF sample

Correlation Pattern Recognition by B. V. K. Vijaya Kumar

by Daniel

Rated 4.12 of 5 – based on 37 votes