One, Two, Three and N Dimensional String Search Algorithms

TL;DR

This paper introduces sequence alignment algorithms for matching and comparing sequences across one to N dimensions using inner product schemes, expanding the applicability of such algorithms to multidimensional data.

Contribution

It presents new algorithms for N-dimensional sequence alignment, generalizing existing methods for 1D, 2D, and 3D sequences using inner product schemes.

Findings

Algorithms successfully align N-dimensional sequences.

Effective comparison of multidimensional sequences demonstrated.

Potential applications in multidimensional data analysis.

Abstract

In this research endeavor, some Sequence Alignment Algorithms are detailed that are useful for finding or comparing 1 dimensional (1-D), 2 dimensional (2-D), 3 dimensional (3-D) sequences in or against a parent or mother database which is 1 dimensional (1-D), 2 dimensional (2-D), 3 dimensional (3-D) sequence. Inner Product [1], [2] based schemes are used to lay down such algorithms. Also,in this research, a Sequence Alignment Algorithms is detailed that is useful for finding or comparing an N-Dimensional (N-D) sequence in or against a parent or mother database which N-Dimensional (N-D) sequence. Inner Product [1], [2] based schemes are used to lay down such an algorithm.