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About 10,000 papers for “recursive algorithm”

An improved recursive algorithm for BLAST

Hufei Zhu, Zhongding Lei, F. Chin · 2006

In this paper, an improved recursive algorithm for BLAST is proposed. The speedups of the improved recursive algorithm over the original recursive algorithm in the number of multiplications and additions are 1.47 and 1.2 respectively. And the speedups of the improved recursive algorithm over the conventional V-BLAST in the number of multiplications and additions are 1.43M+2.93 and 1.43M+2.67, respectively, when the number of transmitting antennas is equal to the number of receiving antennas and is M.

Cited by 2

The CLEF semi-recursive generation algorithm

Rodrigo Reyès · 2000

We will discuss the semi-recursive algorithm for text generation, as defined for the GTAG formalism, and its implementation in the CLEF project. We will show how to use lexical choice constraints and properties of the LTAG grammar to minimize the backtracking of the semi-recursive algorithm.

Cited by 0Open access

A Contraction-Recursive Algorithm for Treewidth

Hisao Tamaki · arXiv (Cornell University) · 2023

Let tw(G) denote the treewidth of graph G. Given a graph G and a positive integer k such that tw(G) <= k + 1, we are to decide if tw(G) <= k. We give a certifying algorithm RTW ("R" for recursive) for this task: it returns one or more tree-decompositions of G of width <= k if the answer is YES and a minimal contraction H of G such that tw(H) > k otherwise. RTW uses a heuristic variant of Tamaki's PID algorithm for treewidth (ESA2017), which we call HPID. RTW, given G and k, interleaves the execution of HPID with recursive calls on G /e for edges e of G, where G / e denotes the graph obtained from G by contracting edge e. If we find that tw(G / e) > k, then we have tw(G) > k with the same certificate. If we find that tw(G / e) <= k, we "uncontract" the bags of the certifying tree-decompositions of G / e into bags of G and feed them to HPID to help progress. If the question is not resolved after the recursive calls are made for all edges, we finish HPID in an exhaustive mode. If it turns out that tw(G) > k, then G is a certificate for tw(G') > k for every G' of which G is a contraction, because we have found tw(G / e) <= k for every edge e of G. This final round of HPID guarantees the correctness of the algorithm, while its practical efficiency derives from our methods of "uncontracting" bags of tree-decompositions of G / e to useful bags of G, as well as of exploiting those bags in HPID. Experiments show that our algorithm drastically extends the scope of practically solvable instances. In particular, when applied to the 100 instances in the PACE 2017 bonus set, the number of instances solved by our implementation on a typical laptop, with the timeout of 100, 1000, and 10000 seconds per instance, are 72, 92, and 98 respectively, while these numbers are 11, 38, and 68 for Tamaki's PID solver and 65, 82, and 85 for his new solver (SEA 2022).

Cited by 0Open access

INVERSION ALGORITHM FOR RECURSIVE NONLINEAR SYSTEMS

Ü Kotta · Proceedings of the Estonian Academy of Sciences Physics Mathematics · 1998

The right invertibility problem is studied for a class of recursive nonlinear systems (RNSs), i.e., for systems, modelled by recursive nonlinear input-output equations involving only a finite:number of input values and a finite number of output values.The concept of rank, which plays the key role in the study of right invertibility for discrete-time nonlinear systems in state space form, is extended to the RNS.It is shown that the inversion algorithm provides the means to compute the rank of the system.Necessary and sufficient conditions for local right invertibility in terms of the rank of the system are proposed.

Cited by 1Open access

Recursive Least Complex Signa Signum Algorithm

Shinrichi Koike · 2018

In this paper, we first review Complex Signo Signum Algorithm (CSSA, and then combine the CSSA with a recursive least estimate of the inverse covariance matrix of the regressor, proposing Recursive Least Complex Signa Signum Algorithm (RLCSSA. Two types of impulse noise are considered: one is found in observation noise at the filter output and another at the filter input. Statistical analysis of the RLCSSA is developed for calculating theoretical convergence behavior. Through experiments with typical examples, we demonstrate effectiveness of the proposed algorithm in accelerating the convergence speed, while preserving the robustness of the CSSA against both types of impulse noise. The calculated theoretical convergence curves are generally in good agreement with the simulated ones that shows the validity and accuracy of the analysis.

Cited by 0

New recursive algorithm for matrix inversion

Jianshu Cao, Xuegang Wang · Journal of Systems Engineering and Electronics · 2008

To reduce the computational complexity of matrix inversion, which is the majority of processing in many practical applications, two numerically efficient recursive algorithms (called algorithms I and II, respectively) are presented. Algorithm I is used to calculate the inverse of such a matrix, whose leading principal minors are all nonzero. Algorithm II, whereby, the inverse of an arbitrary nonsingular matrix can be evaluated is derived via improving the algorithm I. The implementation, for algorithm II or I, involves matrix-vector multiplications and vector outer products. These operations are computationally fast and highly parallelizable. MATLAB simulations show that both recursive algorithms are valid.

Cited by 12

Discussion on Writing of Recursive Algorithm

Jinping Song · International Journal of Hybrid Information Technology · 2013

Writing a program with the recursive method is a simple and effective way of program design, making the logic of the program concise and clear. This paper will focus on the analytical program, writing method of the recursive algorithm, as well as the optimization of recursive program. Formula method or mathematical induction can be applied for writing of the recursive algorithm more simply. Meanwhile, either of them could provide the method of tail recursive to deal with the problem lies in recursive algorithm that massive time and space of the system are occupied.

Cited by 2Open access

A nonlinear adaptive estimation recursive algorithm

D.G. Lainiotis · IEEE Transactions on Automatic Control · 1968

A nonlinear, adaptive and recursive algorithm is derived for estimating an unknown probability density given a sequence of independent samples from the unknown density. An expansion of the unknown density in terms of a known and finite set of orthogonal functions is utilized and a Bayesian recursive learning procedure is derived for learning the coefficients of the expansion. The algorithm eliminates the need for quantization of the unknown parameter space. Adaptive estimators of population moments are also derived as known linear combinations of the recursively obtained expansion coefficients.

Cited by 7

A new convergent recursive identification algorithm

T.C. Hsia · 1983

Presented in this paper is a least-squares based recursive algorithm for system parameter identification free of the usual positive-real conditions required by many similar recursive algorithms. The algorithm is globally asymptotic convergent and robust. Simulation studies have also demonstrated that the new algorithm has a faster converging rate than similar algorithms. Comparison results with the RELS and Landau's algorithms are presented.

Cited by 0

The Recursive Segment 3D Reconstruction Algorithm

Matej Meško, Emil Kršák, Patrik Hrkút · 2013

In this paper, we propose an improved algorithm for 3D scene reconstruction from images obtained from two or more cameras. The principal objective of the proposed algorithm is to reduce number of feature points used for 3D scene reconstruction by using a triangle mesh and recursive sub-mesh definition. This kind of optimization can reduce computational complexity and the algorithm thereafter might be applied in various real-time applications. Another benefit of the solution is reducing the need of computing power, hence a less powerful and more energy efficient computers can be placed e.g. in vehicles. At the beginning of this paper we introduce several issues of 3D reconstruction algorithms, the middle part is focused on the description of the proposed algorithm and in the conclusion we outline a few potential algorithm applications.

Cited by 2

Extended recursive maximum-likelihood identification algorithm

J.P. Norton · Proceedings of the Institution of Electrical Engineers · 1979

An extension of the well known recursive maximum-likelihood or extended least-squares identification algorithm to improve its rate of convergence is presented. The extension is to include explicitly in the model giving rise to the algorithm the errors in the noise-generating sequence normally ignored. The extended algorithm is related to the original, much as an extended Kalman filter is related to an ordinary Kalman filter. The paper compares the algorithm with a similar, but differently motiviated, one, recently described by Ljung. The performance of the algorithm and its optimisation are discussed with reference to computational results from Monte Carlo tests.

Cited by 1

V.: Parallel Recursive Algorithm for FCA

Petr Krajca, Jan Outrata, Vilem Vychodil · 2008

Abstract. This paper presents a parallel algorithm for computing formal concepts. Presented is a sequential version upon which we build the parallel one. We describe the algorithm, its implementation, scalability, and provide an initial experimental evaluation of its efficiency. The algorithm is fast, memory efficient, and can be optimized so that all critical operations are reduced to low-level bit-array operations. One of the key features of the algorithm is that it avoids synchronization which has positive impacts on its speed and implementation. 1

Cited by 0

Fast stochastic and recursive search algorithm

M. Rosvall, C. T. Bergstrom · 2009

Any greedy (fast but inaccurate) or Monte Carlo-based (accurate but slow) approach can be used to minimize the map equation. But since on the order of 1000 networks must be clustered for each significance clustering and high accuracy always is desirable, we have developed a new method that provides a good balance between the two extremes. As a reference, the new algorithm is in practice as fast as the previous high-speed algorithms (the greedy search presented in the supporting appendix of ref. (1)), which were based on the method introduced in ref. (2) and refined in ref. (3). Yet it is also more accurate than our previous high-accuracy algorithm (a simulated annealing approach) presented in the same supporting appendix. The core of the algorithm follows closely the method

Cited by 0