Research on MPLPC Excited-Pulse Abstract Algorithm

2009 ◽  
Author(s):  
Ma Zhen ◽  
Cao Yanyan ◽  
Zhang Jinlan
Keyword(s):  
Abstract Algorithm

The Signorini perturbation scheme in an abstract setting

1991 ◽  
Vol 119 (3-4) ◽  
pp. 373-395 ◽  
Author(s):  
D. R. J. Chillingworth
Keyword(s):  
Logical Structure ◽  
Perturbation Scheme ◽  
Additional Symmetry ◽  
Symmetry Constraints ◽  
Bifurcation Problems ◽  
Relationship Of ◽  
The Relationship ◽  
Abstract Algorithm ◽  
Nonlinear Elastostatics ◽  
Abstract Formulation

SynopsisThe Signorini perturbation scheme is a series expansion algorithm that locates solution branches for a class of symmetry-breaking bifurcation problems in nonlinear elastostatics. The relationship of the formal steps in the algorithm to geometric aspects of the problem is brought out in work of J. E. Marsden and Y.-H. Wan, where an abstract formulation is also considered. In this paper, the abstract algorithm and its geometry are explored further: the logical structure is clarified, and it is shown how the scheme adapts to the presence of additional symmetry constraints.

scholarly journals Gene Sequence Assembly Algorithm Model Based on the DBG Strategy and Its Application

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Haihe Shi ◽  
Gang Wu
Keyword(s):  
Gene Sequence ◽  
Sequence Assembly ◽  
Feature Model ◽  
De Bruijn Graph ◽  
Specific Sequence ◽  
Component Library ◽  
Assembly Algorithm ◽  
Assembly Algorithms ◽  
Abstract Algorithm ◽  
Domain Level

With the continuous development of sequencing technology, the amount of bioinformatics data has increased geometrically, and the massive amount of bioinformatics data puts forward more stringent requirements for sequence assembly problems. The sequence assembly algorithm based on DBG (De Bruijn graph) strategy is a key algorithm in bioinformatics, which is widely used in the domain of gene sequence assembly. Current research on the domain of sequence assembly always focuses on optimization of specific steps to a specific algorithm and lack of research on domain-level high-abstract algorithm frameworks. To some extent, it leads to the redundancy of the sequence assembly algorithm, and some problems may be caused by the artificial selection algorithm. This paper analyzes the domain of DBGSA and establishes a feature model of this domain. Based on the production programming method, the DBGSA algorithm component is interactively designed. With the support of the PAR platform, the DBGSA algorithm component library is formally implemented, and furthermore, the DBGSA component library is used to assemble the specific algorithm. This research adds domain-level research to the domain of sequence assembly and implements the DBGSA component library, which can assemble specific sequence assembly algorithms, ensuring the efficiency of algorithm development and the reliability of assembly generation algorithms. At the same time, it also provides a valuable reference for solving problems in the domain of sequence assembly.

Principle-Based Engineering

2006 ◽  
pp. 221-244
Author(s):  
Susan Ella George
Keyword(s):  
Lambda Calculus ◽  
Turing Machines ◽  
Rule Based ◽  
Step Procedure ◽  
Intuitive Idea ◽  
Rule Based Approach ◽  
Abstract Algorithm

This chapter discusses a new conception of computation. The conception is one of constraints rather than rules. In contrast to the rule-based approach of Turing machines, Post systems and lambda calculus, the constraint-based approach “models” the constraints in operation in the system, and between the system and the environment. There are similarities with Putnam’s idea that “everything is computation” because (1) computation must be “situated” in a profound way, embedded in its environment, but, there is also (2) a move away from the intuitive idea of “algorithm” as a step-by-step procedure, modellling the behaviour of the system in its environment, requiring a mapping of the abstract “algorithm” states to the physical states of “reality.”

The formal language of recursion

1989 ◽  
Vol 54 (4) ◽  
pp. 1216-1252 ◽  
Author(s):  
Yiannis N. Moschovakis
Keyword(s):  
Formal Language ◽  
Iterative Algorithms ◽  
Theory Of Computation ◽  
Mathematical Properties ◽  
Essential Properties ◽  
Suitable Structure ◽  
Recursive Definitions ◽  
Abstract Algorithm ◽  
Computable Functions ◽  
Main Technical Tool

This is the first of a sequence of papers in which we will develop a foundation for the theory of computation based on a precise, mathematical notion of abstract algorithm. To understand the aim of this program, one should keep in mind clearly the distinction between an algorithm and the object (typically a function) computed by that algorithm. The theory of computable functions (on the integers and on abstract structures) is obviously relevant to this work, but we will focus on making rigorous and identifying the mathematical properties of the finer (intensional) notion of algorithm.It is characteristic of this approach that we take recursion to be a fundamental (primitive) process for constructing algorithms, not a derived notion which must be reduced to others—e.g. iteration or application and abstraction, as in the classical λ-calculus. We will model algorithms by recursors, the set-theoretic objects one would naturally choose to represent (syntactically described) recursive definitions. Explicit and iterative algorithms are modelled by (appropriately degenerate) recursors.The main technical tool we will use is the formal language of recursion, FLR, a language of terms with two kinds of semantics: on each suitable structure, the denotation of a term t of FLR is a function, while the intension of t is a recursor (i.e. an algorithm) which computes the denotation of t. FLR is meant to be intensionally complete, in the sense that every (intuitively understood) “algorithm” should “be” (faithfully modelled, in all its essential properties by) the intension of some term of FLR on a suitably chosen structure.

scholarly journals An Assessment of Algorithms for Deriving Failure Deterministic Finite Automata

2017 ◽  
Vol 29 (1) ◽  
Author(s):  
Madoda Nxumalo ◽  
Derrick G Kourie ◽  
Loek Cleophas ◽  
Bruce W Watson
Keyword(s):  
Lower Bounds ◽  
Test Data ◽  
Finite Length ◽  
Spanning Tree ◽  
Finite Automata ◽  
Regular Languages ◽  
Deterministic Finite Automata ◽  
Abstract Algorithm ◽  
Generating Algorithms

Failure deterministic finite automata (FDFAs) represent regular languages more compactly than deterministic finite automata (DFAs). Four algorithms that convert arbitrary DFAs to language-equivalent FDFAs are empirically investigated. Three are concrete variants of a previously published abstract algorithm, the DFA-Homomorphic Algorithm (DHA). The fourth builds a maximal spanning tree from the DFA to derive what it calls a delayed input DFA. A first suite of test data consists of DFAs that recognise randomised sets of finite length keywords. Since the classical Aho-Corasick algorithm builds an optimal FDFA from such a set (and only from such a set), it provides benchmark FDFAs against which the performance of the general algorithms can be compared. A second suite of test data consists of random DFAs generated by a specially designed algorithm that also builds language-equivalent FDFAs, some of which may have non-divergent cycles. These random FDFAs provide (not necessarily tight) lower bounds for assessing the effectiveness of the four general FDFA generating algorithms.

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