Robustness in Statistical Pattern Recognition
āĻŽāĻžāĻ°ā§āĻ ā§¨ā§Ļā§§ā§Š ¡ Mathematics and Its Applications āĻŦāĻ 380 ¡ Springer Science & Business Media
āĻ-āĻŦā§āĻ
302
āĻĒā§āĻˇā§āĻ āĻž
reportāĻ°ā§āĻāĻŋāĻ āĻ āĻ°āĻŋāĻāĻŋāĻ āĻ¯āĻžāĻāĻžāĻ āĻāĻ°āĻž āĻšā§āĻ¨āĻŋ Â āĻāĻ°āĻ āĻāĻžāĻ¨ā§āĻ¨
āĻāĻ āĻ-āĻŦā§āĻā§āĻ° āĻŦāĻŋāĻˇā§ā§
This book is concerned with important problems of robust (stable) statistical pat tern recognition when hypothetical model assumptions about experimental data are violated (disturbed). Pattern recognition theory is the field of applied mathematics in which prin ciples and methods are constructed for classification and identification of objects, phenomena, processes, situations, and signals, i. e. , of objects that can be specified by a finite set of features, or properties characterizing the objects (Mathematical Encyclopedia (1984)). Two stages in development of the mathematical theory of pattern recognition may be observed. At the first stage, until the middle of the 1970s, pattern recogni tion theory was replenished mainly from adjacent mathematical disciplines: mathe matical statistics, functional analysis, discrete mathematics, and information theory. This development stage is characterized by successful solution of pattern recognition problems of different physical nature, but of the simplest form in the sense of used mathematical models. One of the main approaches to solve pattern recognition problems is the statisti cal approach, which uses stochastic models of feature variables. Under the statistical approach, the first stage of pattern recognition theory development is characterized by the assumption that the probability data model is known exactly or it is esti mated from a representative sample of large size with negligible estimation errors (Das Gupta, 1973, 1977), (Rey, 1978), (Vasiljev, 1983)).
āĻ-āĻŦā§āĻā§ āĻ°ā§āĻāĻŋāĻ āĻĻāĻŋāĻ¨
āĻāĻĒāĻ¨āĻžāĻ° āĻŽāĻ¤āĻžāĻŽāĻ¤ āĻāĻžāĻ¨āĻžāĻ¨āĨ¤
āĻĒāĻ āĻ¨ āĻ¤āĻĨā§āĻ¯
āĻ¸ā§āĻŽāĻžāĻ°ā§āĻāĻĢā§āĻ¨ āĻāĻŦāĻ āĻā§āĻ¯āĻžāĻŦāĻ˛ā§āĻ
Android āĻāĻŦāĻ iPad/iPhone āĻāĻ° āĻāĻ¨ā§āĻ¯ Google Play āĻŦāĻ āĻ
ā§āĻ¯āĻžāĻĒ āĻāĻ¨āĻ¸ā§āĻāĻ˛ āĻāĻ°ā§āĻ¨āĨ¤ āĻāĻāĻŋ āĻāĻĒāĻ¨āĻžāĻ° āĻ
ā§āĻ¯āĻžāĻāĻžāĻāĻ¨ā§āĻā§āĻ° āĻ¸āĻžāĻĨā§ āĻ
āĻā§āĻŽā§āĻāĻŋāĻ āĻ¸āĻŋāĻā§āĻ āĻšā§ āĻ āĻāĻĒāĻ¨āĻŋ āĻ
āĻ¨āĻ˛āĻžāĻāĻ¨ āĻŦāĻž āĻ
āĻĢāĻ˛āĻžāĻāĻ¨ āĻ¯āĻžāĻ āĻĨāĻžāĻā§āĻ¨ āĻ¨āĻž āĻā§āĻ¨ āĻāĻĒāĻ¨āĻžāĻā§ āĻĒā§āĻ¤ā§ āĻĻā§ā§āĨ¤
āĻ˛ā§āĻ¯āĻžāĻĒāĻāĻĒ āĻ āĻāĻŽā§āĻĒāĻŋāĻāĻāĻžāĻ°
Google Play āĻĨā§āĻā§ āĻā§āĻ¨āĻž āĻ
āĻĄāĻŋāĻāĻŦā§āĻ āĻāĻĒāĻ¨āĻŋ āĻāĻŽā§āĻĒāĻŋāĻāĻāĻžāĻ°ā§āĻ° āĻā§ā§āĻŦ āĻŦā§āĻ°āĻžāĻāĻāĻžāĻ°ā§ āĻļā§āĻ¨āĻ¤ā§ āĻĒāĻžāĻ°ā§āĻ¨āĨ¤
eReader āĻāĻŦāĻ āĻ
āĻ¨ā§āĻ¯āĻžāĻ¨ā§āĻ¯ āĻĄāĻŋāĻāĻžāĻāĻ¸
Kobo eReaders-āĻāĻ° āĻŽāĻ¤ā§ e-ink āĻĄāĻŋāĻāĻžāĻāĻ¸ā§ āĻĒāĻĄāĻŧāĻ¤ā§, āĻāĻĒāĻ¨āĻžāĻā§ āĻāĻāĻāĻŋ āĻĢāĻžāĻāĻ˛ āĻĄāĻžāĻāĻ¨āĻ˛ā§āĻĄ āĻ āĻāĻĒāĻ¨āĻžāĻ° āĻĄāĻŋāĻāĻžāĻāĻ¸ā§ āĻā§āĻ°āĻžāĻ¨ā§āĻ¸āĻĢāĻžāĻ° āĻāĻ°āĻ¤ā§ āĻšāĻŦā§āĨ¤ āĻŦā§āĻ¯āĻŦāĻšāĻžāĻ°āĻāĻžāĻ°ā§āĻ° āĻāĻĻā§āĻĻā§āĻļā§āĻ¯ā§ āĻ¤ā§āĻ°āĻŋ āĻ¸āĻšāĻžā§āĻ¤āĻž āĻā§āĻ¨ā§āĻĻā§āĻ°āĻ¤ā§ āĻĻā§āĻā§āĻž āĻ¨āĻŋāĻ°ā§āĻĻā§āĻļāĻžāĻŦāĻ˛ā§ āĻ
āĻ¨ā§āĻ¸āĻ°āĻŖ āĻāĻ°ā§ āĻ¯ā§āĻ¸āĻŦ eReader-āĻ āĻĢāĻžāĻāĻ˛ āĻĒāĻĄāĻŧāĻž āĻ¯āĻžāĻŦā§ āĻ¸ā§āĻāĻžāĻ¨ā§ āĻā§āĻ°āĻžāĻ¨ā§āĻ¸āĻĢāĻžāĻ° āĻāĻ°ā§āĻ¨āĨ¤
