Introduction to Orthogonal Transforms With Applications in Data Processing and Analysis

 
Introduction to Orthogonal Transforms With Applications in Data Processing and Analysis
Free Download Ruye Wang, "Introduction to Orthogonal Transforms: With Applications in Data Processing and Analysis"
English | ISBN: 0521516889 | 2012 | 590 pages | PDF | 9 MB
A systematic, unified treatment of orthogonal transform methods for signal processing, data analysis and communications, this book guides the reader from mathematical theory to problem solving in practice. It examines each transform method in depth, emphasizing the common mathematical principles and essential properties of each method in terms of signal decorrelation and energy compaction. The different forms of Fourier transform, as well as the Laplace, Z-, Walsh-Hadamard, Slant, Haar, Karhunen-Loève and wavelet transforms, are all covered, with discussion of how each transform method can be applied to real-world experimental problems. Numerous practical examples and end-of-chapter problems, supported by online Matlab and C code and an instructor-only solutions manual, make this an ideal resource for students and practitioners alike.


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Learning with Fractional Orthogonal Kernel Classifiers in Support Vector Machines Theory, Algorithms and Applications

 
Learning with Fractional Orthogonal Kernel Classifiers in Support Vector Machines Theory, Algorithms and Applications
Free Download Learning with Fractional Orthogonal Kernel Classifiers in Support Vector Machines: Theory, Algorithms and Applications by Jamal Amani Rad, Kourosh Parand, Snehashish Chakraverty
English | PDF,EPUB | 2023 | 312 Pages | ISBN : 9811965528 | 44.5 MB
This book contains select chapters on support vector algorithms from different perspectives, including mathematical background, properties of various kernel functions, and several applications. The main focus of this book is on orthogonal kernel functions, and the properties of the classical kernel functions-Chebyshev, Legendre, Gegenbauer, and Jacobi-are reviewed in some chapters. Moreover, the fractional form of these kernel functions is introduced in the same chapters, and for ease of use for these kernel functions, a tutorial on a Python package named ORSVM is presented. The book also exhibits a variety of applications for support vector algorithms, and in addition to the classification, these algorithms along with the introduced kernel functions are utilized for solving ordinary, partial, integro, and fractional differential equations.


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Classical Orthogonal Polynomials of a Discrete Variable

 
Classical Orthogonal Polynomials of a Discrete Variable
Classical Orthogonal Polynomials of a Discrete Variable by Arnold F. Nikiforov , Vasilii B. Uvarov , Sergei K. Suslov
English | PDF | 1991 | 388 Pages | ISBN : 3642747507 | 27.1 MB
Mathematical modelling of many physical processes involves rather complex dif ferential, integral, and integro-differential equations which can be solved directly only in a number of cases. Therefore, as a first step, an original problem has to be considerably simplified in order to get a preliminary knowledge of the most important qualitative features of the process under investigation and to estimate the effect of various factors. Sometimes a solution of the simplified problem can be obtained in the analytical form convenient for further investigation.


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