Introduction: Basic concepts, Design concepts, Examples; Decision functions: Linear decision functions, Generalized decision functions; Pattern classification by distance functions: Minimum distance pattern classification, Cluster seeking; Pattern classification by likelihood functions: Bayes classifier; Structural pattern representation: Grammars for pattern representation, Picture description language and grammars, Stochastic grammars; Structural pattern recognition: String to string distance; Matching other structures: Relational structures, Graph matching, Matching by relaxation, Random graph