Analytic Approach to Pattern Matching
ثبت نشده
چکیده
7.0 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327 7.1 Probabilistic models . . . . . . . . . . . . . . . . . . . . . . . . . 330 7.2 Exact string matching . . . . . . . . . . . . . . . . . . . . . . . . 333 7.2.1 Languages representations . . . . . . . . . . . . . . . . . 334 7.2.2 Generating functions . . . . . . . . . . . . . . . . . . . . 337 7.2.3 Moments and limit laws . . . . . . . . . . . . . . . . . . 339 7.2.4 Waiting times . . . . . . . . . . . . . . . . . . . . . . . . 346 7.3 Generalized string matching . . . . . . . . . . . . . . . . . . . . 347 7.3.1 String matching over reduced set of patterns . . . . . . . 348 7.3.2 Analysis of the generalized string matching . . . . . . . 353 7.3.3 Forbidden words and (l, k) sequences . . . . . . . . . . . 362 7.4 Subsequence pattern matching . . . . . . . . . . . . . . . . . . . 364 7.4.1 Mean and variance analysis . . . . . . . . . . . . . . . . 366 7.4.2 Autocorrelation polynomial revisited . . . . . . . . . . . 371 7.4.3 Central limit laws . . . . . . . . . . . . . . . . . . . . . . 371 7.4.4 Limit laws for fully constrained pattern . . . . . . . . . 374 7.5 Generalized subsequence problem . . . . . . . . . . . . . . . . . 375 7.5.1 Generating operators for dynamic sources . . . . . . . . 376 7.5.2 Mean and variance . . . . . . . . . . . . . . . . . . . . . 379 7.6 Self-repetitive pattern matching . . . . . . . . . . . . . . . . . . 381 7.6.1 Formulation of the problem . . . . . . . . . . . . . . . . 381 7.6.2 Random tries resemble suffix tries . . . . . . . . . . . . . 384 Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 392 Notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393
منابع مشابه
Pattern Matching : From DNA to Twitter
How do you distinguish a cat from a dog by their DNA? Did Shakespeare really write all his plays? Pattern matching techniques can offer answers to these questions and to many others, in contexts from molecular biology to telecommunications to the classification of Twitter content. This book, intended for researchers and graduate students, demonstrates the probabilistic approach to pattern match...
متن کاملEvaluation of Similarity Measures for Template Matching
Image matching is a critical process in various photogrammetry, computer vision and remote sensing applications such as image registration, 3D model reconstruction, change detection, image fusion, pattern recognition, autonomous navigation, and digital elevation model (DEM) generation and orientation. The primary goal of the image matching process is to establish the correspondence between two ...
متن کاملAn Eigendecomposition Approach to Weighted Graph Matching Problems
Absfruct-This paper discusses an approximate solution to the weighted graph matching prohlem (WGMP) for both undirected and directed graphs. The W G M P is the problem of f inding the opt imum matching between two weighted graphs, which are graphs with weights at each arc. The proposed method employs an analytic, instead of a combinatorial or iterative, approach to the opt imum matching problem...
متن کاملLocal Derivative Pattern with Smart Thresholding: Local Composition Derivative Pattern for Palmprint Matching
Palmprint recognition is a new biometrics system based on physiological characteristics of the palmprint, which includes rich, stable, and unique features such as lines, points, and texture. Texture is one of the most important features extracted from low resolution images. In this paper, a new local descriptor, Local Composition Derivative Pattern (LCDP) is proposed to extract smartly stronger...
متن کامل