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I.Pattern Recognition System
Two processes
Recognition Process: data acquisition and pretreatment→feature generation→feature extraction and selection→recognition and classification→result
Training Process： data acquisition and pretreatment→feature generation→feature extraction and selection→classifiter design（→recognition and classification→result）
II.Pattern Recognition Method
1.Supervised Learning and Unsupervised Learning
Supervised Learning:it need to know the category of every samples.
Unsupervised Leearning:it don‘t need the category of any sample and even the number of samples.
2.Identification model and Production model
The identification model consists of linear and nonlinear.
Identification model:it think that the samples which belong to different category are situated at different regions.
production model:The schema is considered as a random vector in feature space，and every different schema appears in space by probability.
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原文地址：http://www.cnblogs.com/Renxj/p/5503672.html
