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About 10,000 papers for “recursive method”

Method for manual recursive mapping.docx

HARA, TOMIJIRO, Takatsuka, Yumiko, Shiwa, Yuh et al. · Figshare · 2021

We report a draft genome sequence of the <i>Comamonas testosteroni</i> strain YAZ2, a polychlorinated biphenyl (PCB) degrader, isolated from a PCB-unpolluted environment. The assembled genome contains a single 5.4-Mb chromosome and an 87-kb plasmid. The <i>bph</i> gene cluster involved in PCB degradation was found on the chromosome. This method was used in the sequence assembly of YAZ2.

Cited by 0Open access

Modelling method of recursive entity

Amal Rifai, Rochdi Messoussi · British Journal of Educational Technology · 2010

Abstract With the development of the Information and Communication Technologies, great masses of information are published in the Web. In order to reuse, to share and to organise them in distance formation and e‐learning frameworks, several research projects have been achieved and various standards and modelling languages developed. In our previous article, the limits of theses languages were examined and a new method named the recursive entity modelling method (REMM) was established to overcome these limits. But, when it was revised, some limitations were discovered. So, in this paper, an improved version of the REMM will be proposed, and the diagram of classes for a scenario modelled by this version will be established. In addition, both the learning scenario package and the generic XML schema permitting to implement these scenarios will be conceived.

Cited by 1

Method for manual recursive mapping.docx

HARA, TOMIJIRO, Takatsuka, Yumiko, Shiwa, Yuh et al. · Figshare · 2021

We report a draft genome sequence of the <i>Comamonas testosteroni</i> strain YAZ2, a polychlorinated biphenyl (PCB) degrader, isolated from a PCB-unpolluted environment. The assembled genome contains a single 5.4-Mb chromosome and an 87-kb plasmid. The <i>bph</i> gene cluster involved in PCB degradation was found on the chromosome. This method was used in the sequence assembly of YAZ2.

Cited by 0Open access

Recursive method for modelling metallic boundariesusing TLM method

Remus Cacoveanu, P. Saguet, Silviu Ciochină et al. · Electronics Letters · 1995

The use of a dispersive reflection coefficient concept in the TLM-method to model conductor boundaries is described. An efficient implementation of this approach, based on the recursive proprieties of convolution with exponentials, is presented. The reflection of plane waves on a lossy conductor wall is modelled over a wide frequency range, and the TLM simulations are compared to the theoretical results.

Cited by 1

Recursive Integral Method with Cayley Transformation

Ruihao Huang, Jiguang Sun, Chao Yang · arXiv (Cornell University) · 2017

Recently, a non-classical eigenvalue solver, called RIM, was proposed to compute (all) eigenvalues in a region on the complex plane. Without solving any eigenvalue problem, it tests if a region contains eigenvalues using an approximate spectral projection. Regions that contain eigenvalues are subdivided and tested recursively until eigenvalues are isolated with a specified precision. This makes RIM an eigensolver distinct from all existing methods. Furthermore, it requires no a priori spectral information. In this paper, we propose an improved version of {\bf RIM} for non-Hermitian eigenvalue problems. Using Cayley transformation and Arnoldi's method, the computation cost is reduced significantly. Effectiveness and efficiency of the new method are demonstrated by numerical examples and compared with 'eigs' in Matlab.

Cited by 7Open access

The overdetermined recursive instrumental variable method

B. Friedlander · IEEE Transactions on Automatic Control · 1984

A recursive instrumental variable algorithm is derived for the overdetermined case in which the number of instruments is greater than the number of estimated parameters. In some applications, the algorithm provides improved parameter estimation accuracy, compared to the standard recursive instrumental variable method. The performance of the algorithm is illustrated by simulation results.

Cited by 89

An Adaptive Recursive Volatility Prediction Method

Nicklas Werge, Olivier Wintenberger · HAL (Le Centre pour la Communication Scientifique Directe) · 2020

The Quasi-Maximum Likelihood (QML) procedure is widely used for statistical inference due to its robustness against overdisper-sion. However, while there are extensive references on non-recursive QML estimation, recursive QML estimation has attracted little attention until recently. In this paper, we investigate the convergence properties of the QML procedure in a general conditionally heteroscedastic time series model, extending the classical offline optimization routines to recursive approximation. We propose an adaptive recursive estimation routine for GARCH models using the technique of Variance Targeting Estimation (VTE) to alleviate the convergence difficulties encountered in the usual QML estimation. Finally, empirical results demonstrate a favorable trade-off between the ability to adapt to time-varying estimates and stability of the estimation routine.

Cited by 0Open access

THE RECURSIVE LAGRANGIAN METHOD: DISCRETE TIME

CHRISTOPHER SLEET, SEVIN YELTEKIN · 2010

Marcet and Marimon (1999) propose a recursive Lagrangian-based method for solving dynamic incentive problems. We show that this method is applicable to a large class of concave contracting problems that encompass many in the literature. This class includes problems with (potentially persistent) private information, non-commitment, differential private and societal discounting and potentially unbounded returns. The dynamic programming problems associated with the method are non-standard in several respects: their state spaces may be unknown and their constraint correspondences are not continuous or compact-valued. We propose resolutions for these difficulties.

Cited by 0

Recursive mean-separate histogram equalisation method.

Abdul Rahman Ramli, Soong Der Chen · Universiti Putra Malaysia Institutional Repository (Universiti Putra Malaysia) · 2004

The present invention relates to recursive mean-separate histogram method to enhance the contrast of an image and to recursively mean separate the input image so that the output image mean brightness will coverage to the input image mean. The process is that an input image is divided into a predetermine number of sub-image and then calculate the cumulative density. Next, the sub-image is histogram equalised independently. This invention provide a scalable brightness preservation, and more importantly the method is very useful in consumer electronic products.

Cited by 0

Recursive method for Power-Flow solution

Véliz, Marcos Tostado, Kamel, Salah, , Francisco · Zenodo (CERN European Organization for Nuclear Research) · 2020

This is a power flow solver based on recursive formulas, ready to be used in Matpower software. The required functions for calculating the Jacobian matrix and the mismatches function are also provided (both functions required the state vector 'x' as input).

Cited by 0Open access

Formalizing a Recursive Epistemic Meta-Method

Mitchell D. McPhetridge · PhilPapers (PhilPapers Foundation)

We present a formal meta-methodology that underlies a series of works by M. D. McPhetridge (e.g. Φ-Method, Recursive Epistemic Modeling, Critical Self Critique). This methodology provides a unified approach to recursive systems – systems that generate themselves through recursion – by making their governing principles explicit. Rather than positing a fixed essence or external designer, these systems begin with a self-referential loop that produces identity and order as emergent attractors . In this meta-method, identity, intelligence, and even physical laws are treated not as static properties but as processes or stable patterns arising from iterative continuation . The approach is cross-domain, applying equally to cognitive “selves,” machine-learning systems, and cosmological models. It formalizes how a system continues itself, how it remains coherent across scales, and how it stays stable under perturbations . By abstracting these features into a portable framework, the method functions as an “engineering-and-critique scaffold” – a set of formal constraints and operations that can be instantiated in any domain to model self-generating behavior. This paper explicates the recursive methodological architecture in a formal manner. We first define the scope of systems addressed and enumerate the core primitives of the method – the minimal concepts and operators that recur across all implementations. We then describe the architectural decomposition strategy: how complex self-referential systems are broken into constrained operators and failure modes, leading to emergent attractors. A general procedure for applying the method to various domains (from modeling one’s “self” to designing AI or describing cosmology) is provided. We include suggestions for empirical validation – metrics and tests to ensure a given recursive model indeed exhibits the intended stability and convergence. Crucially, we articulate the second-order and third-order epistemic safeguards built into the method: design features and methodological norms that prevent the framework from devolving into unfalsifiable metaphysics or collapsing important distinctions. Finally, we situate this meta-method in the lineage of prior theoretical moves (Gödel’s self-reference, Ashby’s cybernetics, Maturana’s autopoiesis, Hofstadter’s loops, etc.), clarifying what is inherited and what is redefined. Scope of Systems and Assumptions The meta-method formalized here targets a broad class of systems that can be termed recursive identity attractors . These are systems in which persistent identity or order is not pre-given but emerges as a fixed-point attractor of a recursive process. In other words, the system “continues itself” over time by repeatedly applying an internal generative operation until a stable pattern (an identity) arises . Formally, if $\iota$ denotes the identity state (e.g. the notion of “self”), then $\iota$ is defined by a recursive equation $\iota = \Phi(\iota)$ – a self-consistency condition stating that identity is whatever state reproduces itself under the system’s update operator $\Phi$. This perspective treats identity not as a static substance or stored object, but as an attractor in state-space: a pattern toward which the system’s state converges through iteration . The systems of interest must also satisfy additional demands that go beyond mere recurrence. They often must maintain coherence across scales and resist disruptive drift in the face of noise or changing conditions . For example, a cognitive self might exhibit consistent identity both in minute-to-minute thoughts and across a lifetime (multi-scale coherence), and it must remain stable under perturbations (recovering from shocks or noise in the environment). Similarly, a complex artificial system or an organism must continue its core patterns (homeostasis or goal-directed behavior) even as external conditions vary. We refer to systems that achieve persistence by countering entropy or disorder as entropy-stabilized systems. In these systems, some form of “selection” or convergence pressure is at work to prevent runaway divergence or chaos . Rather than allowing arbitrary recursive growth (which could lead to explosive instability or collapse), the system must funnel its dynamics toward low-instability configurations (e.g. minimizing an energy or error functional). Finally, the meta-method is applicable to what we can call epistemic engines – systems or frameworks that model and learn about other systems (including themselves) through recursion. This includes an observer recursively improving a model of a black-box process , or a reflective reasoning process that bootstraps better understanding via self-application. In such cases, the “system” in question is a process of inquiry or cognition that must generate reliable knowledge of an opaque target. The Recursive Epistemic Modeling framework (REM) exemplifies this: it provides a way to iteratively construct and update a worldview or internal model of some phenomenon when the internal workings of that phenomenon are not directly observable . Across these diverse contexts – selfhood, AI, cognition, cosmology, organizations – the essential assumption is that the system can be understood as autonomously continuing itself (zero-origin recursion) and that doing so in a sustained, robust way requires certain fundamental constraints. We now turn to those core primitives and constraints.

Cited by 0