Efficient algorithm for two dimensional pattern matching problem (non-square pattern)

2012 ◽  
Author(s):  
Jaber Alwidian ◽  
Hussein Abu-Mansour ◽  
Moshira Ali
Keyword(s):  
Pattern Matching ◽  
Efficient Algorithm ◽  
Two Dimensional ◽  
Matching Problem

scholarly journals An Efficient Algorithm for 2-Dimensional Pattern Matching Problem

2020 ◽  
Vol 50 (2) ◽  
pp. 295-313
Author(s):  
Sushil Chandra Dimri ◽  
Umesh Kumar Tiwari ◽  
Mangey Ram
Keyword(s):  
Computer Science ◽  
Prime Number ◽  
Pattern Matching ◽  
Efficient Algorithm ◽  
Matching Problem ◽  
Decimal Number ◽  
2D Pattern ◽  
Decimal Numbers ◽  
The Given

AbstractPattern matching is the area of computer science which deals with security and analysis of data. This work proposes two 2D pattern matching algorithms based on two different input domains. The first algorithm is for the case when the given pattern contains only two symbols, that is, binary symbols 0 and 1. The second algorithm is in the case when the given pattern contains decimal numbers, that is, the collection of symbols between 0 and 9. The algorithms proposed in this manuscript convert the given pattern into an equivalent binary or decimal number, correspondingly find the cofactors of the same dimension and convert these cofactors into numbers if a particular cofactor number matches indicate the matching of the pattern. Furthermore, the algorithm is enhanced for decimal numbers. In the case of decimal numbers, each row of the pattern is changed to its decimal equivalent, and then, modulo with a suitable prime number changes the decimal equivalent into a number less than the prime number. If the number mismatched pattern does not exist, the complexity of the proposed algorithm is very low as compared to other traditional algorithms.

Two Dimensional Matching

1997 ◽  
Author(s):  
A. Amir ◽  
M. Farach
Keyword(s):  
Pattern Matching ◽  
String Matching ◽  
Higher Dimensions ◽  
Natural Generalization ◽  
Theoretical Problem ◽  
Two Dimensional ◽  
Exact Matching ◽  
Matching Problem ◽  
Deterministic Algorithms ◽  
Special Case

String matching is a basic theoretical problem in computer science, but has been useful in implementating various text editing tasks. The explosion of multimedia requires an appropriate generalization of string matching to higher dimensions. The first natural generalization is that of seeking the occurrences of a pattern in a text where both pattern arid text are rectangles. The last few years saw a tremendous activity in two dimensional pattern matching algorithms. We naturally had to limit the amount of information that entered this chapter. We chose to concentrate on serial deterministic algorithms for some of the basic issues of two dimensional matching. Throughout this chapter we define our problems in terms of squares rather than rectangles, however, all results presented easily generalize to rectangles. The Exact Two Dimensional Matching Problem is defined as follows: . . . INPUT: Text array T[n x n] and pattern array P[m x m]. OUTPUT: All locations [i,j] in T where there is an occurrence of P, i.e. T[i+k+,j+l] = P[k+1,l+1] 0 ≤ k, l ≤ n-1. . . . A natural way of solving any generalized problem is by reducing it to a special case whose solution is known. It is therefore not surprising that most solutions to the two dimensional exact matching problem use exact string matching algorithms in one way or another. In this section, we present an algorithm for two dimensional matching which relies on reducing a matrix of characters into a one dimensional array. Let P' [1 . . .m] be a pattern which is derived from P by setting P' [i] = P[i,l]P[i,2]…P[i,m], that is, the ith character of P' is the ith row of P. Let Ti[l . . .n — m + 1], for 1 ≤ i ≤ n, be a set of arrays such that Ti[j] = T[i, j] T [ i , j + 1 ] • • • T[i, j + m-1]. Clearly, P occurs at T[i, j] iff P' occurs at Ti[j].

scholarly journals An efficient algorithm for the blocked pattern matching problem

2014 ◽  
Vol 31 (4) ◽  
pp. 532-538 ◽  
Author(s):  
Fei Deng ◽  
Lusheng Wang ◽  
Xiaowen Liu
Keyword(s):  
Pattern Matching ◽  
Efficient Algorithm ◽  
Matching Problem

scholarly journals Smart Templates for peak pattern matching with comprehensive two-dimensional liquid chromatography

2009 ◽  
Vol 1216 (16) ◽  
pp. 3458-3466 ◽  
Author(s):  
Stephen E. Reichenbach ◽  
Peter W. Carr ◽  
Dwight R. Stoll ◽  
Qingping Tao
Keyword(s):  
Liquid Chromatography ◽  
Pattern Matching ◽  
Two Dimensional ◽  
Peak Pattern

Efficient two-dimensional pattern matching in the presence of errors

1987 ◽  
Vol 43 (3) ◽  
pp. 169-184 ◽  
Author(s):  
Kamala Krithivasan ◽  
R. Sitalakshmi
Keyword(s):  
Pattern Matching ◽  
Two Dimensional

scholarly journals An Efficient Signal Reconstruction Algorithm for Stepped Frequency MIMO-SAR in the Spotlight and Sliding Spotlight Modes

2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
Jiajia Zhang ◽  
Guangcai Sun ◽  
Mengdao Xing ◽  
Zheng Bao ◽  
Fang Zhou
Keyword(s):  
Efficient Algorithm ◽  
Low Cost ◽  
Signal Reconstruction ◽  
Multiple Input Multiple Output ◽  
Reconstruction Algorithm ◽  
Synthetic Aperture ◽  
Two Dimensional ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Stepped Frequency

Multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) using stepped frequency (SF) waveforms enables a high two-dimensional (2D) resolution with wider imaging swath at relatively low cost. However, only the stripmap mode has been discussed for SF MIMO-SAR. This paper presents an efficient algorithm to reconstruct the signal of SF MIMO-SAR in the spotlight and sliding spotlight modes, which includes Doppler ambiguity resolving algorithm based on subaperture division and an improved frequency-domain bandwidth synthesis (FBS) method. Both simulated and constructed data are used to validate the effectiveness of the proposed algorithm.

scholarly journals Hyers-Ulam Stability of Lagrange’s Mean Value Points in Two Variables

Mathematics ◽  
2018 ◽  
Vol 6 (11) ◽  
pp. 216 ◽  
Author(s):  
Soon-Mo Jung ◽  
Ji-Hye Kim
Keyword(s):  
Efficient Algorithm ◽  
Mean Value ◽  
Two Dimensional ◽  
Ulam Stability

Using a theorem of Ulam and Hyers, we will prove the Hyers-Ulam stability of two-dimensional Lagrange’s mean value points ( η , ξ ) which satisfy the equation, f ( u , v ) − f ( p , q ) = ( u − p ) f x ( η , ξ ) + ( v − q ) f y ( η , ξ ) , where ( p , q ) and ( u , v ) are distinct points in the plane. Moreover, we introduce an efficient algorithm for applying our main result in practical use.

A new algorithm for the small-field astrometric point-pattern matching problem

2018 ◽  
Vol 72 (1) ◽  
pp. 55-70 ◽  
Author(s):  
Cláudio P. Santiago ◽  
Carlile Lavor ◽  
Sérgio Assunção Monteiro ◽  
Alberto Kroner-Martins
Keyword(s):  
Pattern Matching ◽  
Point Pattern ◽  
Small Field ◽  
Matching Problem ◽  
Point Pattern Matching
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