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

By B. V. K. Vijaya Kumar

ISBN-10: 0521571030

ISBN-13: 9780521571036

Correlation is a strong and normal approach for trend attractiveness and is utilized in many purposes, equivalent to computerized aim reputation, biometric attractiveness and optical personality reputation. The layout, research and use of correlation development popularity algorithms calls for heritage details, together with linear platforms thought, random variables and strategies, matrix/vector tools, detection and estimation conception, electronic sign processing and optical processing. This 2005 publication presents a wanted assessment of this various heritage fabric and develops the sign processing thought, the development popularity metrics, and the sensible program information from simple premises. It exhibits either electronic and optical implementations. It additionally includes expertise provided by way of the staff that constructed it and contains case stories of important curiosity, equivalent to face and fingerprint popularity. appropriate for graduate scholars taking classes in trend reputation thought, when attaining technical degrees of curiosity to the pro practitioner.

Show description

Read or Download Correlation Pattern Recognition PDF

Best computer vision & pattern recognition books

Download e-book for iPad: Introduction to Information Optics (Optics and Photonics) by Francis T.S. Yu, Suganda Jutamulia, Shizuhuo Yin

Whereas there are books treating person subject matters contained during this publication, this may be the 1st unmarried quantity supplying a cohesive therapy in this topic as a complete. This is going past optical communications in that it contains comparable subject matters reminiscent of sensing, monitors, computing, and knowledge garage.

Download PDF by Prof. S. Lakshmivarahan (auth.): Learning Algorithms Theory and Applications

Studying constitutes some of the most vital part of the complete mental techniques and it's crucial in lots of methods for the incidence of helpful alterations within the habit of changing organisms. In a huge experience impression of earlier habit and its end result upon next habit is mostly permitted as a definition of studying.

Andrew R. Webb(auth.)'s Statistical Pattern Recognition, Second Edition PDF

Statistical development attractiveness is a truly lively zone of analysis and examine, which has obvious many advances in recent times. New and rising functions - comparable to info mining, net looking, multimedia information retrieval, face reputation, and cursive handwriting acceptance - require strong and effective development attractiveness suggestions.

Get Two-Dimensional Change Detection Methods: Remote Sensing PDF

Swap detection utilizing remotely sensed photographs has many purposes, equivalent to city tracking, land-cover swap research, and catastrophe administration. This paintings investigates two-dimensional switch detection equipment. the prevailing tools within the literature are grouped into 4 different types: pixel-based, transformation-based, texture analysis-based, and structure-based.

Additional info for Correlation Pattern Recognition

Sample text

34) would be q=0. For a non-trivial solution of Eq. , jA À lIj ¼ 0 (2:35) 22 Mathematical background Expanding the determinant in Eq. 35) yields a polynomial (of degree less than or equal to N when A is an N Â N matrix) in l, and that polynomial is known as the characteristic polynomial of A. The roots of the characteristic polynomial are the eigenvalues li, which can be back-substituted into Eq. 34) to obtain the corresponding eigenvectors qi. Note from Eq. 33) that if q is an eigenvector of A, then q is also an eigenvector of A when is a scalar.

The (i, j)th entry of A is aij. Let us first consider the case of M ¼ N where the transformation matrix A is invertible. The Jacobian (defined as the determinant of the matrix containing qyi as its (i, j) element) of this transformation is jAj, the determinant of the qxj transformation matrix. 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.

Their joint PDF is a function only of X 2 þ Y 2 ), then they are Gaussian with zero means n o andÈ equal É variances. It is easy to verify that E jZj2 ¼ E X 2 þ Y 2 ¼ 22 whereas E{Z2} ¼ E{X2 À Y2} ¼ 0. Finally, it is useful to realize that the central limit theorem applies to complex RVs also, in the sense that adding many identical and independent complex RVs results in Gaussian complex RVs. This can be seen by applying the central limit theorem to the real part and imaginary part separately.

Download PDF sample

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


by James
4.0

Rated 4.72 of 5 – based on 27 votes