Searching in Compressed Dictionaries
نویسندگان
چکیده
The problem of Compressed Pattern Matching , introduced by Amir and Benson [1], is of performing pattern matching directly in a compressed text without any decompressing. More formally, for a given text T , pattern P and complementary encoding and decoding functions E and D, respectively, our aim is to search for E(P ) in E(T ), rather than the usual approach which searches for the pattern P in the decompressed text D(E(T )).
منابع مشابه
Frames for compressed sensing using coherence
We give some new results on sparse signal recovery in the presence of noise, for weighted spaces. Traditionally, were used dictionaries that have the norm equal to 1, but, for random dictionaries this condition is rarely satised. Moreover, we give better estimations then the ones given recently by Cai, Wang and Xu.
متن کاملJPEG-LS Based Two-Dimensional Compressed Pattern Matching
With the phenomenal advances in data acquisition techniques via satellites and in medical diagnostics and forensic sciences, we have encountered a massive growth of image data. On account of efficiency (in terms of both space and time), there is a need to keep the data in compressed form for as much as possible, even when it is being searched. The class of images we are concerned in this paper ...
متن کاملOrthogonal Matching Pursuit with random dictionaries
In this paper we investigatet the efficiency of the Orthogonal Matching Pursuit for random dictionaries. We concentrate on dictionaries satisfying Restricted Isometry Property. We introduce a stronger Homogenous Restricted Isometry Property which is satisfied with overwhelming probability for random dictionaries used in compressed sensing. We also present and discuss some open problems about OMP.
متن کاملA Breadth-First Representation for Tree Matching in Large Scale Forest-Based Translation
Efficient data structures are necessary for searching large translation rule dictionaries in forest-based machine translation. We propose a breadth-first representation of tree structures that allows trees to be stored and accessed efficiently. We describe an algorithm that allows incremental search for trees in a forest and show that its performance is orders of magnitude faster than iterative...
متن کاملLearning of Graph Compressed Dictionaries for Sparse Representation Classification
Despite the limited target data available to design face models in video surveillance applications, many faces of non-target individuals may be captured in operational environments, and over multiple cameras, to improve robustness to variations. This paper focuses on Sparse Representation Classification (SRC) techniques that are suitable for the design of still-to-video FR systems based on unde...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2002