This volume, containing contributions by experts from all over the world, is a collection of 21 articles which present review and research material describing the evolution and recent developments of various pattern recognition methodologies, ranging from statistical, syntactic/linguistic, fuzzy-set-theoretic, neural, genetic-algorithmic and rough-set-theoretic to hybrid soft computing, with significant real-life applications. In addition, the book describes efficient soft machine learning algorithms for data mining and knowledge discovery. With a balanced mixture of theory, algorithms and applications, as well as up-to-date information and an extensive bibliography, Pattern Recognition: From Classical to Modern Approaches is a very useful resource.Contents: Pattern Recognition: Evolution of Methodologies and Data Mining (A Pal & S K Pal)Adaptive Stochastic Algorithms for Pattern Classification (M A L Thathachar & P S Sastry)Shape in Images (K V Mardia)Decision Trees for Classification: A Review and Some New Results (R Kothari & M Dong)Syntactic Pattern Recognition (A K Majumder & A K Ray)Fuzzy Sets as a Logic Canvas for Pattern Recognition (W Pedrycz & N Pizzi)Neural Network Based Pattern Recognition (V David Sanchez A)Networks of Spiking Neurons in Data Mining (K Cios & D M Sala)Genetic Algorithms, Pattern Classification and Neural Networks Design (S Bandyopadhyay et al.)Rough Sets in Pattern Recognition (A Skowron & R Swiniarski)Automated Generation of Qualitative Representations of Complex Objects by Hybrid Soft-Computing Methods (E H Ruspini & I S Zwir)Writing Speed and Writing Sequence Invariant On-line Handwriting Recognition (S-H Cha & S N Srihari)Tongue Diagnosis Based on Biometric Pattern Recognition Technology (K Wang et al.)and other papersReadership: Graduate students, researchers and academics in pattern recognition.Key Features:The theory of PN spaces is relevant as a generalization of deterministic results of linear normed spaces and also in the study of random operator equationsDeals with all the developed ideas in PN spacesA good reference book for post graduate students and researchers in this field as it identifies the developments and open problems in PN spaces