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About 10,000 papers for “recursive algorithm”

COLLISION AVOIDANCE RECURSIVE ALGORITHM

Rob Res, K Prasanna Lakshmi, K Prasanna Lakshmi · 2014

This paper presents a technique for providing collision avoidance of arbitrary objects in a computer graphics system. The recursive algorithm implements the method of avoiding the collisions by taking an alternate path and therefore among the available alternate paths, the shortest one is chosen. Under the cluttered environment, maneuvering among the static and moving obstacles is the biggest hurdle which the robotic industry is facing. A small attempt is made to solve these issues.

Cited by 0

A Parallel/Recursive Algorithm

Gibbs, W. R. · arXiv (Cornell University) · 2003

An algorithm is discussed for converting a class of recursive processes to a parallel system. It is argued that this algorithm can be superior to certain methods currently found in the literature for an important subset of problems. The cases of homogeneous and non-homogenous two term recursion are treated. Applications to three problems (finding the eigenvalues of a tri-diagonal matrix, the solution of a radial wave equation and the solution of a tri-diagonal matrix) are discussed.

Cited by 0Open access

Recursive Hierarchical Clustering Algorithm

Pavani Y. De Silva, Chiran N. Fernando, Damith D. Wijethunge et al. · International Journal of Machine Learning and Computing · 2018

Ultimate objective of data mining is to extract information from large datasets, and to utilize the extracted information in decision making process. Clustering is the most generic approach of many unsupervised algorithms in data mining, which cluster data into samples so that objects with similar statistical properties cluster together. Hierarchical, partition, grid and spectral are such clustering algorithms coming under unsupervised approach. Many of these approaches produce clusters either according to a predefined value or according to its own algorithm or produces hierarchies letting the user to determine the preferred number of clusters. Selecting appropriate number of clusters for a given problem is a crucial factor that determine the success of the approach. This paper proposes a novel recursive hierarchical clustering algorithm which combine the core concepts of hierarchical clustering and decision tree fundamentals to find the optimal number of clusters that suits to the given problem autonomously.

Cited by 12Open access

Recursive Algorithm for LASSO

Yasuaki Kaneda, Yasuharu Irizuki · IEEJ Transactions on Electronics Information and Systems · 2016

In many fields including control systems society, sparse estimations are attracting the most attention. Especially, L1 regularized linear regression is applied to many applications because it is easy to deal with. However, in calculations using all measurement data at once, the more number of measurement becomes, the lager computational costs become. In this paper, we propose a recursive algorithm for the L1 regularized linear regression. In order to derive the proposed recursive algorithm, we introduce upper and lower bounds of a criterion of the L1 regularized linear regression. Moreover, we show that we can solve a minimization problem of the both bounds analytically and recursively, and we use the analytic solutions as an approximate solution of the L1 regularized linear regression. We demonstrate the effectiveness of the proposed method by numerical simulations, in which we use random systems to evaluate the proposed method.

Cited by 0

Fast recursive AMIPAP algorithm

Felix Albu · 2015

The approximate memory improved proportionate affine projection algorithm has been proposed for sparse system identification. This paper presents a fast recursive implementation of this algorithm. Three ideas used previously for other affine projection variants are used: auxiliary coefficients vectors, periodically update of the proportionate coefficients and recursive filtering of the error vector. Simulation results are made in order to show the performance of the algorithm for network echo cancellation example.

Cited by 1

An order recursive algorithm for synthesizing linear recursive filters

Yang Sun · International Conference on Acoustics, Speech, and Signal Processing · 2003

The author proposes an order recursive algorithm to compute efficiently the solution to the set of linear equations for finding the parameters of a recursive filter whose unit impulse response best approximates that of the prescribed ideal response. The algorithm requires only O(p/sup 2/) operations. The inherent structure of the coefficient matrix in the system of linear equations and the inversion procedure for a partitioned matrix are used in the algorithm. In a numerical example of a low-pass filter the system of linear equations is found to be ill-conditioned. A satisfactory solution can not be achieved using the usual software routines, even with double precision, for a moderate value of the order p. The proposed algorithm is shown to be more accurate and less sensitive to this ill-conditioned case.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Cited by 0

Recursive Kernel MPE Loss Algorithm

Wentao Ma, Jinzhe Qiu · 2019

Kernel mean p-power error (KMPE) as a robust learning loss has been successfully employed to design robust PCA and ELM. This paper proposes a novel recursive adaptive filtering algorithm via the KMPE loss to identify linear system parameters under non-Gaussian noise cases. To derive the recursive KMPE algorithm, a KMPE loss with a forgetting factor is given first, and then the gradient method is employed to derive a recursive form of the weight estimation with a gain matrix for the system. Numerical simulation results demonstrate that the proposed algorithm with a suitable p value can obtain higher steady-state accuracy and faster convergence rate compared with some other existing algorithms.

Cited by 1

Recursive least-squares algorithm revisited

Jean–Jacques Fuchs · 1981

A modified form of the recursive least-squares algorithm is proposed. It is shown that this algorithm possesses interesting properties that are valid without any restriction on experimental conditions, or stability assumptions. It is thus especially well suited for adaptive control schemes.

Cited by 5

RGS: Recursive Gradient Scanning Algorithm

Shuo Yang, Fei Yi · 2024

Provides a recursive gradient scanning algorithm for discretizing continuous variables in Logistic and Cox regression models. This algorithm is especially effective in identifying optimal cut-points for variables with U-shaped relationships to 'lnOR' (the natural logarithm of the odds ratio) or 'lnHR' (the natural logarithm of the hazard ratio), thereby enhancing model fit, interpretability, and predictive power. By iteratively scanning and calculating gradient changes, the method accurately pinpoints critical cut-points within nonlinear relationships, transforming continuous variables into categorical ones. This approach improves risk classification and regression analysis performance, increasing interpretability and practical relevance in clinical and risk management settings.

Cited by 0

RECURSIVE STRUCTURALIZATION IN ALGORITHM CYBERNETICS

Bush Jones · Kybernetes · 1978

An approach to the cybernetic design of a wide class of algorithms is presented. The approach allows the implicit elimination of symbolic forms for an algorithm, while the search for a symbolic form can be dynamically restricted to a narrow space of symbolic forms. The immediate practical use of the design concept is demonstrated.

Cited by 3

Pel-recursive motion estimation algorithm

H. Gharavi, Hamid‐Reza Reza‐Alikhani · Electronics Letters · 2001

A new pel-recursive motion estimation algorithm for video coding applications is presented. The derivation of the algorithm is based on recursive least-squares estimation that minimises the mean-square prediction error. A comparison with the modified steepest-descent gradient estimation technique algorithm shows significant improvement in terms of mean-square prediction error performance.

Cited by 7

A Recursive Pattern Recognition Algorithm

Puerto Cuadros, Eduard Gilberto, Aguilar Castro, Jose Lisandro · Repositorio Universidad Francisco de Paula Santander · 2017

"This work presents a pattern recognition algorithm based on the systematic functioning of the human neocortex, in processes of pattern recognition. The algorithm exploits the idea of recursivity, based on the neocortical hierarchy and the decomposition/integration in the recognition process. The proposed algorithm is tested to analyze its capabilities of pattern recognition."

Cited by 0

A Fast Recursive Algorithm For

Constructing Matrices With, Abstract. Theweyl-horntheoremcharacterizesarelationshipbetweenthe Moodyt. Chu · 2008

The Weyl-Horn theorem characterizes a relationship between the eigenvalues and the singular values of an arbitrary matrix. Based on that characterization, a fast recursive algorithm is developed to construct numerically a matrix with prescribed eigenvalues and singular values. Beside being theoretically interesting, the technique could be employed to create test matrices with desired spectral features. Numerical experiment shows this algorithm is quite efficient and robust.

Cited by 0

Recursive moving window DFT algorithm

J.L. Aravena · IEEE Transactions on Computers · 1990

A recursive algorithm is presented for computing the discrete Fourier transform (DFT). The algorithm is developed for a moving-window-type processing. The computational structure is fully concurrent and allows a vectorized updating of the DFT. The total time required for the updating could be as low as that of only one multiplication and two additions, regardless of the number of points. A possible structure for executing the computations is developed, and possible enhancements are analyzed.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Cited by 28