Instruction to Statistical Pattern Recognition is popular PDF and ePub book, written by Keinosuke Fukunaga in 1972-01-01, it is a fantastic choice for those who relish reading online the Technology & Engineering genre. Let's immerse ourselves in this engaging Technology & Engineering book by exploring the summary and details provided below. Remember, Instruction to Statistical Pattern Recognition can be Read Online from any device for your convenience.
Instruction to Statistical Pattern Recognition Book PDF Summary
Introduction to Statistical Pattern Recognition introduces the reader to statistical pattern recognition, with emphasis on statistical decision and estimation. Pattern recognition problems are discussed in terms of the eigenvalues and eigenvectors. Comprised of 11 chapters, this book opens with an overview of the formulation of pattern recognition problems. The next chapter is devoted to linear algebra, with particular reference to the properties of random variables and vectors. Hypothesis testing and parameter estimation are then discussed, along with error probability estimation and linear classifiers. The following chapters focus on successive approaches where the classifier is adaptively adjusted each time one sample is observed; feature selection and linear mapping for one distribution and multidistributions; and problems of nonlinear mapping. The final chapter describes a clustering algorithm and considers criteria for both parametric and nonparametric clustering. This monograph will serve as a text for the introductory courses of pattern recognition as well as a reference book for practitioners in the fields of mathematics and statistics.
Detail Book of Instruction to Statistical Pattern Recognition PDF
- Author : Keinosuke Fukunaga
- Release : 01 January 1972
- Publisher : Elsevier
- ISBN : 9780323162784
- Genre : Technology & Engineering
- Total Page : 386 pages
- Language : English
- PDF File Size : 15,9 Mb
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