Oscillators from nonlinear realizations
Kozyrev, N.; Krivonos, S.
2018-02-01
We construct the systems of the harmonic and Pais-Uhlenbeck oscillators, which are invariant with respect to arbitrary noncompact Lie algebras. The equations of motion of these systems can be obtained with the help of the formalism of nonlinear realizations. We prove that it is always possible to choose time and the fields within this formalism in such a way that the equations of motion become linear and, therefore, reduce to ones of ordinary harmonic and Pais-Uhlenbeck oscillators. The first-order actions, that produce these equations, can also be provided. As particular examples of this construction, we discuss the so(2, 3) and G 2(2) algebras.
Non-linear realizations and bosonic branes
International Nuclear Information System (INIS)
West, P.
2001-01-01
In this very short note, following hep-th/0001216, we express the well known bosonic brane as a non-linear realization. The reader may also consult hep-th/9912226, 0001216 and 0005270 where the branes of M theory are constructed as a non-linear realisation. The automorphisms of the supersymmetry algebra play an essential role. (author)
Inverse Higgs effect in nonlinear realizations
International Nuclear Information System (INIS)
Ivanov, E.A.; Ogievetskij, V.I.
1975-01-01
In theories with nonlinearly realized symmetry it is possible in a number of cases to eliminate some initial Goldstone and gauge fields by means of putting appropriate Cartan forms equal to zero. This is called the inverse Higgs phenomenon. We give a general treatment of the inverse Higgs phenomenon for gauge and space-time symmetries and consider four instructive examples which are the elimination of unessential gauge fields in chiral symmetry and in non-linearly realized supersymmetry and also the elimination of unessential Goldstone fields in the spontaneously broken conformal and projective symmetries
Nonlinear realizations of W3 symmetry
International Nuclear Information System (INIS)
Ivanov, E.A.; Krivonos, S.O.
1991-01-01
We derive the Toda lattice realization of classical W 3 symmetry on two scalar fields in a purely geometric way, proceeding from a nonlinear realization of some associate higher-spin symmetry W 3 ∞ is derived. The Toda lattice equations are interpreted as the constraints singling out a two-dimensional fully geodesic subspace in the initial coset space of W 3 ∞ . This subspace is the quotient of SL(3,R) over its maximal parabolic subgroup. 20 refs
Nonlinear realization of general covariance group
International Nuclear Information System (INIS)
Hamamoto, Shinji
1979-01-01
The structure of the theory resulting from the nonlinear realization of general covariance group is analysed. We discuss the general form of free Lagrangian for Goldstone fields, and propose as a special choice one reasonable form which is shown to describe a gravitational theory with massless tensor graviton and massive vector tordion. (author)
Quantization of a nonlinearly realized supersymmetric theory
International Nuclear Information System (INIS)
Shima, K.
1977-01-01
The two-dimensional version of the Volkov-Akulov Lagrangian, where the supersymmetry is realized nonlinearly by means of a single Majorana spinor psi (x), is quantized. The equal-time anticommutators for the field are not c numbers but are functions of the field itself. By explicit calculation we shall show that the supersymmetry charges of the model form the supersymmetry algebra (the graded Lie algebra); therefore the Hamiltonian of the system P 0 is written as a bilinear sum of products of supersymmetry charges. We shall also show that the supersymmetry charges exactly generate a constant translation of psi (x) in the spinor space
Invariant renormalization method for nonlinear realizations of dynamical symmetries
International Nuclear Information System (INIS)
Kazakov, D.I.; Pervushin, V.N.; Pushkin, S.V.
1977-01-01
The structure of ultraviolet divergences is investigated for the field theoretical models with nonlinear realization of the arbitrary semisimple Lie group, with spontaneously broken symmetry of vacuum. An invariant formulation of the background field method of renormalization is proposed which gives the manifest invariant counterterms off mass shell. A simple algorithm for construction of counterterms is developed. It is based on invariants of the group of dynamical symmetry in terms of the Cartan forms. The results of one-loop and two-loop calculations are reported
Supertrace formulae for nonlinearly realized supersymmetry
Murli, Divyanshu; Yamada, Yusuke
2018-04-01
We derive the general supertrace formula for a system with N chiral superfields and one nilpotent chiral superfield in global and local supersymmetry. The nilpotent multiplet is realized by taking the scalar-decoupling limit of a chiral superfield breaking supersymmetry spontaneously. As we show, however, the modified formula is not simply related to the scalar-decoupling limit of the supertrace in linearly-realized supersymmetry. We also show that the supertrace formula reduces to that of a linearly realized supersymmetric theory with a decoupled sGoldstino if the Goldstino is the fermion in the nilpotent multiplet.
Some nonlinear space decomposition algorithms
Energy Technology Data Exchange (ETDEWEB)
Tai, Xue-Cheng; Espedal, M. [Univ. of Bergen (Norway)
1996-12-31
Convergence of a space decomposition method is proved for a general convex programming problem. The space decomposition refers to methods that decompose a space into sums of subspaces, which could be a domain decomposition or a multigrid method for partial differential equations. Two algorithms are proposed. Both can be used for linear as well as nonlinear elliptic problems and they reduce to the standard additive and multiplicative Schwarz methods for linear elliptic problems. Two {open_quotes}hybrid{close_quotes} algorithms are also presented. They converge faster than the additive one and have better parallelism than the multiplicative method. Numerical tests with a two level domain decomposition for linear, nonlinear and interface elliptic problems are presented for the proposed algorithms.
Field-theoretical investigations in nonlinear realizations of gauge symmetry
International Nuclear Information System (INIS)
Lee, Chenhan.
1989-01-01
A review of both linear realization and non-linear realization of gauge symmetries is given and the connection between the two recipes is carefully examined. The author then constructs both linear and non-linear realizations for of supersymmetric theories. The supermultiplets of the Goldstone modes contain Goldstone bosons, quasi-Goldstone bosons and quasi-Goldstone fermions. He makes an attempt to construct a specific model of a supersymmetric non-linear realization for the Nambu-Goldstone superfields and the quasi-Goldstone fermions are identified with the quarks and leptons. Further, he discusses a mechanism by which the components of the Nambu-Goldstone supermultiplets are given non-zero mass splittings by the coupling to a hidden sector. Next, he turns to anti-symmetric tensor gauge theories, which are shown to be classically equivalent to the non-linear models describing the complete symmetry breakdown. To study the quantum mechanical equivalence of these two models, he carries out the tensor gauge fixing and the quantization procedures for the anti-symmetric tensor theories and establish the global symmetry currents which connect the two models. He then builds the supersymmetric extensions of the anti-symmetric tensor gauge theories in both abelian and non-abelian versions. Such super-tensor gauge theories are shown, by using the superfield equations of motion, to be equivalent to the fully doubled supersymmetric non-linear models of complete symmetry breakdown
Non-linear realization of α0 -extended supersymmetry
International Nuclear Information System (INIS)
Nishino, Hitoshi
2000-01-01
As generalizations of the original Volkov-Akulov action in four-dimensions, actions are found for all space-time dimensions D invariant under N non-linear realized global supersymmetries. We also give other such actions invariant under the global non-linear supersymmetry. As an interesting consequence, we find a non-linear supersymmetric Born-Infeld action for a non-Abelian gauge group for arbitrary D and N , which coincides with the linearly supersymmetric Born-Infeld action in D=10 at the lowest order. For the gauge group U(N) for M(atrix)-theory, this model has N 2 -extended non-linear supersymmetries, so that its large N limit corresponds to the infinitely many (α 0 ) supersymmetries. We also perform a duality transformation from F μν into its Hodge dual N μ 1 ctdot μD-2 . We next point out that any Chern-Simons action for any (super)groups has the non-linear supersymmetry as a hidden symmetry. Subsequently, we present a superspace formulation for the component results. We further find that as long as superspace supergravity is consistent, this generalized Volkov-Akulov action can further accommodate such curved superspace backgrounds with local supersymmetry, as a super p -brane action with fermionic kappa-symmetry. We further elaborate these results to what we call 'simplified' (Supersymmetry) 2 -models, with both linear and non-linear representations of supersymmetries in superspace at the same time. Our result gives a proof that there is no restriction on D or N for global non-linear supersymmetry. We also see that the non-linear realization of supersymmetry in 'curved' space-time can be interpreted as 'non-perturbative' effect starting with the 'flat' space-time
Hofstadter butterflies in nonlinear Harper lattices, and their optical realizations
International Nuclear Information System (INIS)
Manela, Ofer; Segev, Mordechai; Christodoulides, Demetrios N; Kip, Detlef
2010-01-01
The ubiquitous Hofstadter butterfly describes a variety of systems characterized by incommensurable periodicities, ranging from Bloch electrons in magnetic fields and the quantum Hall effect to cold atoms in optical lattices and more. Here, we introduce nonlinearity into the underlying (Harper) model and study the nonlinear spectra and the corresponding extended eigenmodes of nonlinear quasiperiodic systems. We show that the spectra of the nonlinear eigenmodes form deformed versions of the Hofstadter butterfly and demonstrate that the modes can be classified into two families: nonlinear modes that are a 'continuation' of the linear modes of the system and new nonlinear modes that have no counterparts in the linear spectrum. Finally, we propose an optical realization of the linear and nonlinear Harper models in transversely modulated waveguide arrays, where these Hofstadter butterflies can be observed. This work is relevant to a variety of other branches of physics beyond optics, such as disorder-induced localization in ultracold bosonic gases, localization transition processes in disordered lattices, and more.
Hofstadter butterflies in nonlinear Harper lattices, and their optical realizations
Energy Technology Data Exchange (ETDEWEB)
Manela, Ofer; Segev, Mordechai [Department of Physics and Solid State Institute, Technion, Haifa 32000 (Israel); Christodoulides, Demetrios N [College of Optics/CREOL, University of Central Florida, FL 32816-2700 (United States); Kip, Detlef, E-mail: msegev@tx.technion.ac.i [Department of Electrical Engineering, Helmut Schmidt University, 22043 Hamburg (Germany)
2010-05-15
The ubiquitous Hofstadter butterfly describes a variety of systems characterized by incommensurable periodicities, ranging from Bloch electrons in magnetic fields and the quantum Hall effect to cold atoms in optical lattices and more. Here, we introduce nonlinearity into the underlying (Harper) model and study the nonlinear spectra and the corresponding extended eigenmodes of nonlinear quasiperiodic systems. We show that the spectra of the nonlinear eigenmodes form deformed versions of the Hofstadter butterfly and demonstrate that the modes can be classified into two families: nonlinear modes that are a 'continuation' of the linear modes of the system and new nonlinear modes that have no counterparts in the linear spectrum. Finally, we propose an optical realization of the linear and nonlinear Harper models in transversely modulated waveguide arrays, where these Hofstadter butterflies can be observed. This work is relevant to a variety of other branches of physics beyond optics, such as disorder-induced localization in ultracold bosonic gases, localization transition processes in disordered lattices, and more.
Superworld volume dynamics of super branes from nonlinear realizations
International Nuclear Information System (INIS)
Bellucci, S.; Ivanov, E.; Krivonos, S.
2000-01-01
Based on the concept of the partial breaking of global supersymmetry (PBGS), it has been derived the world volume superfield equations of motion for N=1, D=4 supermembrane, as well as for the space-time filling D2- and D3-branes, from nonlinear realizations of the corresponding supersymmetries. It has been argued that it is of no need to take care of the relevant automorphism groups when being interested in the dynamical equations. This essentially facilitates computations. As a by-product, it has been obtained a new polynomial representation for the d=3,4 Born-Infeld equations, with merely a cubic nonlinearity
Optimization and experimental realization of the quantum permutation algorithm
Yalçınkaya, I.; Gedik, Z.
2017-12-01
The quantum permutation algorithm provides computational speed-up over classical algorithms for determining the parity of a given cyclic permutation. For its n -qubit implementations, the number of required quantum gates scales quadratically with n due to the quantum Fourier transforms included. We show here for the n -qubit case that the algorithm can be simplified so that it requires only O (n ) quantum gates, which theoretically reduces the complexity of the implementation. To test our results experimentally, we utilize IBM's 5-qubit quantum processor to realize the algorithm by using the original and simplified recipes for the 2-qubit case. It turns out that the latter results in a significantly higher success probability which allows us to verify the algorithm more precisely than the previous experimental realizations. We also verify the algorithm for the first time for the 3-qubit case with a considerable success probability by taking the advantage of our simplified scheme.
Quantization of a non-linearly realized supersymmetric theory
International Nuclear Information System (INIS)
Shima, Kazunari
1976-01-01
The two-dimensional version of the Volkov-Akulov's Lagrngian, where the super-symmetry is realized non-linearly by means of a single Majorana spinor psi(x), is quantized. The equal time anti-commutators for the field are not c-numbers but functions of the field itself. By the explicite calculation we shall show that supersymmetry charges of the model form the supersymmetry algebra(the graded Lie algebra) and the supersymmetry charges exactly generate a constant translation of psi(x) in the spinor space. In this work we restrict our investigation to the two-dimensional space-time for the sake of simplicity. (auth.)
Nonlinear realization of supersymmetric AdS space isometries
International Nuclear Information System (INIS)
Clark, T. E.; Love, S. T.
2006-01-01
The isometries of AdS 5 space and supersymmetric AdS 5 xS 1 space are nonlinearly realized on four-dimensional Minkowski space. The resultant effective actions in terms of the Nambu-Goldstone modes are constructed. The dilatonic mode governing the motion of the Minkowski space probe brane into the covolume of supersymmetric AdS 5 space is found to be unstable and the bulk of the AdS 5 space is unable to sustain the brane. No such instability appears in the nonsupersymmetric case
Non-linear realizations and higher curvature supergravity
Energy Technology Data Exchange (ETDEWEB)
Farakos, F. [Dipartimento di Fisica e Astronomia ' ' Galileo Galilei' ' , Universita di Padova (Italy); INFN, Sezione di Padova (Italy); Ferrara, S. [Department of Theoretical Physics, Geneva (Switzerland); INFN - Laboratori Nazionali di Frascati, Frascati (Italy); Department of Physics and Astronomy, Mani L. Bhaumik Institute for Theoretical Physics, U.C.L.A., Los Angeles, CA (United States); Kehagias, A. [Physics Division, National Technical University of Athens (Greece); Luest, D. [Arnold Sommerfeld Center for Theoretical Physics, Muenchen (Germany); Max-Planck-Institut fuer Physik, Muenchen (Germany)
2017-12-15
We focus on non-linear realizations of local supersymmetry as obtained by using constrained superfields in supergravity. New constraints, beyond those of rigid supersymmetry, are obtained whenever curvature multiplets are affected as well as higher derivative interactions are introduced. In particular, a new constraint, which removes a very massive gravitino is introduced, and in the rigid limit it merely reduces to an explicit supersymmetry breaking. Higher curvature supergravities free of ghosts and instabilities are also obtained in this way. Finally, we consider direct coupling of the goldstino multiplet to the super Gauss-Bonnet multiplet and discuss the emergence of a new scalar degree of freedom. (copyright 2017 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)
Algorithms For Integrating Nonlinear Differential Equations
Freed, A. D.; Walker, K. P.
1994-01-01
Improved algorithms developed for use in numerical integration of systems of nonhomogenous, nonlinear, first-order, ordinary differential equations. In comparison with integration algorithms, these algorithms offer greater stability and accuracy. Several asymptotically correct, thereby enabling retention of stability and accuracy when large increments of independent variable used. Accuracies attainable demonstrated by applying them to systems of nonlinear, first-order, differential equations that arise in study of viscoplastic behavior, spread of acquired immune-deficiency syndrome (AIDS) virus and predator/prey populations.
Combined algorithms in nonlinear problems of magnetostatics
International Nuclear Information System (INIS)
Gregus, M.; Khoromskij, B.N.; Mazurkevich, G.E.; Zhidkov, E.P.
1988-01-01
To solve boundary problems of magnetostatics in unbounded two- and three-dimensional regions, we construct combined algorithms based on a combination of the method of boundary integral equations with the grid methods. We study the question of substantiation of the combined method of nonlinear magnetostatic problem without the preliminary discretization of equations and give some results on the convergence of iterative processes that arise in non-linear cases. We also discuss economical iterative processes and algorithms that solve boundary integral equations on certain surfaces. Finally, examples of numerical solutions of magnetostatic problems that arose when modelling the fields of electrophysical installations are given too. 14 refs.; 2 figs.; 1 tab
Non-linear realizations of supersymmetry with off-shell central charges
International Nuclear Information System (INIS)
Santos Filho, P.B.; Oliveira Rivelles, V. de.
1985-01-01
A new class of non-linear realizations of the extended supersymmetry algebra with central charges is presented. They were obtained by applying the technique of dimensional reduction by Legendre transformation to a non-linear realization without central charges in one higher dimension. As a result an off-shell central charge is obtained. The non-linear lagrangian is the same as is the case of vanishing central charge. On-shell the central charge vanishes so this non-linear realization differs from that without central charges only off-shell. It is worked in two dimensions and its extension to higher dimensions is discussed. (Author) [pt
Hardware realization of an SVM algorithm implemented in FPGAs
Wiśniewski, Remigiusz; Bazydło, Grzegorz; Szcześniak, Paweł
2017-08-01
The paper proposes a technique of hardware realization of a space vector modulation (SVM) of state function switching in matrix converter (MC), oriented on the implementation in a single field programmable gate array (FPGA). In MC the SVM method is based on the instantaneous space-vector representation of input currents and output voltages. The traditional computation algorithms usually involve digital signal processors (DSPs) which consumes the large number of power transistors (18 transistors and 18 independent PWM outputs) and "non-standard positions of control pulses" during the switching sequence. Recently, hardware implementations become popular since computed operations may be executed much faster and efficient due to nature of the digital devices (especially concurrency). In the paper, we propose a hardware algorithm of SVM computation. In opposite to the existing techniques, the presented solution applies COordinate Rotation DIgital Computer (CORDIC) method to solve the trigonometric operations. Furthermore, adequate arithmetic modules (that is, sub-devices) used for intermediate calculations, such as code converters or proper sectors selectors (for output voltages and input current) are presented in detail. The proposed technique has been implemented as a design described with the use of Verilog hardware description language. The preliminary results of logic implementation oriented on the Xilinx FPGA (particularly, low-cost device from Artix-7 family from Xilinx was used) are also presented.
Nonlinear model predictive control theory and algorithms
Grüne, Lars
2017-01-01
This book offers readers a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC schemes with and without stabilizing terminal constraints are detailed, and intuitive examples illustrate the performance of different NMPC variants. NMPC is interpreted as an approximation of infinite-horizon optimal control so that important properties like closed-loop stability, inverse optimality and suboptimality can be derived in a uniform manner. These results are complemented by discussions of feasibility and robustness. An introduction to nonlinear optimal control algorithms yields essential insights into how the nonlinear optimization routine—the core of any nonlinear model predictive controller—works. Accompanying software in MATLAB® and C++ (downloadable from extras.springer.com/), together with an explanatory appendix in the book itself, enables readers to perform computer experiments exploring the possibilities and limitations of NMPC. T...
Nonlinear realizations, the orbit method and Kohn's theorem
Andrzejewski, K.; Gonera, J.; Kosinski, P.
2012-01-01
The orbit method is used to describe the centre of mass motion of the system of particles with fixed charge to mass ratio moving in homogeneous magnetic field and confined by harmonic potential. The nonlinear action of symmetry group on phase space is identified and compared with the one obtained with the help of Eisenhart lift.
Nonlinear realizations and effective Lagrangian densities for nonlinear σ-models
International Nuclear Information System (INIS)
Hamilton-Charlton, Jason Dominic
2003-01-01
Nonlinear realizations of the groups SU(N), SO(m) and SO(t,s) are analysed, described by the coset spaces SU(N) / SU(N-1) x U(1), SO(m) / SO(m-1), SO(1,m-1) / SO(1,m-2) and SO(m) / SO(m-2 x SO(2). The analysis consists of determining the transformation properties of the Goldstone Bosons, constructing the most general possible Lagrangian for the realizations, and as a result identifying the coset space metric. We view the λ matrices of SU(N) as being the basis of an (N 2 - 1) dimensional real vector space, and from this we learn how to construct the basis of a Cartan Subspace associated with a vector. This results in a mathematical structure which allows us to find expressions for coset representative elements used in the analysis. This structure is not only relevant to SU(N) breaking models, but may also be used to find results in SO(m) and SO(1,m - 1) breaking models. (author)
Non-linear realization of the Virasoro-Kac-Moody algebra and the anomalies
International Nuclear Information System (INIS)
Aoyama, S.
1988-01-01
The non-linear realization of the Virasoro algebra x Kac-Moody algebra will be studied. We will calculate the Ricci tensor of the relevant Kaehler manifold to show a new vacuum structure for this coupled algebra. (orig.)
Realization of seven-qubit Deutsch-Jozsa algorithm on NMR quantum computer
International Nuclear Information System (INIS)
Wei Daxiu; Yang Xiaodong; Luo Jun; Sun Xianping; Zeng Xizhi; Liu Maili; Ding Shangwu
2002-01-01
Recent years, remarkable progresses in experimental realization of quantum information have been made, especially based on nuclear magnetic resonance (NMR) theory. In all quantum algorithms, Deutsch-Jozsa algorithm has been widely studied. It can be realized on NMR quantum computer and also can be simplified by using the Cirac's scheme. At first the principle of Deutsch-Jozsa quantum algorithm is analyzed, then the authors implement the seven-qubit Deutsch-Jozsa algorithm on NMR quantum computer
An efficient control algorithm for nonlinear systems
International Nuclear Information System (INIS)
Sinha, S.
1990-12-01
We suggest a scheme to step up the efficiency of a recently proposed adaptive control algorithm, which is remarkably effective for regulating nonlinear systems. The technique involves monitoring of the ''stiffness of control'' to get maximum gain while maintaining a predetermined accuracy. The success of the procedure is demonstrated for the case of the logistic map, where we show that the improvement in performance is often factors of tens, and for small control stiffness, even factors of hundreds. (author). 4 refs, 1 fig., 1 tab
Realization of Deutsch-like algorithm using ensemble computing
International Nuclear Information System (INIS)
Wei Daxiu; Luo Jun; Sun Xianping; Zeng Xizhi
2003-01-01
The Deutsch-like algorithm [Phys. Rev. A. 63 (2001) 034101] distinguishes between even and odd query functions using fewer function calls than its possible classical counterpart in a two-qubit system. But the similar method cannot be applied to a multi-qubit system. We propose a new approach for solving Deutsch-like problem using ensemble computing. The proposed algorithm needs an ancillary qubit and can be easily extended to multi-qubit system with one query. Our ensemble algorithm beginning with a easily-prepared initial state has three main steps. The classifications of the functions can be obtained directly from the spectra of the ancilla qubit. We also demonstrate the new algorithm in a four-qubit molecular system using nuclear magnetic resonance (NMR). One hydrogen and three carbons are selected as the four qubits, and one of carbons is ancilla qubit. We choice two unitary transformations, corresponding to two functions (one odd function and one even function), to validate the ensemble algorithm. The results show that our experiment is successfully and our ensemble algorithm for solving the Deutsch-like problem is virtual
On realization of nonlinear systems described by higher-order differential equations
van der Schaft, Arjan
1987-01-01
We consider systems of smooth nonlinear differential and algebraic equations in which some of the variables are distinguished as “external variables.” The realization problem is to replace the higher-order implicit differential equations by first-order explicit differential equations and the
Algorithms for adaptive nonlinear pattern recognition
Schmalz, Mark S.; Ritter, Gerhard X.; Hayden, Eric; Key, Gary
2011-09-01
In Bayesian pattern recognition research, static classifiers have featured prominently in the literature. A static classifier is essentially based on a static model of input statistics, thereby assuming input ergodicity that is not realistic in practice. Classical Bayesian approaches attempt to circumvent the limitations of static classifiers, which can include brittleness and narrow coverage, by training extensively on a data set that is assumed to cover more than the subtense of expected input. Such assumptions are not realistic for more complex pattern classification tasks, for example, object detection using pattern classification applied to the output of computer vision filters. In contrast, we have developed a two step process, that can render the majority of static classifiers adaptive, such that the tracking of input nonergodicities is supported. Firstly, we developed operations that dynamically insert (or resp. delete) training patterns into (resp. from) the classifier's pattern database, without requiring that the classifier's internal representation of its training database be completely recomputed. Secondly, we developed and applied a pattern replacement algorithm that uses the aforementioned pattern insertion/deletion operations. This algorithm is designed to optimize the pattern database for a given set of performance measures, thereby supporting closed-loop, performance-directed optimization. This paper presents theory and algorithmic approaches for the efficient computation of adaptive linear and nonlinear pattern recognition operators that use our pattern insertion/deletion technology - in particular, tabular nearest-neighbor encoding (TNE) and lattice associative memories (LAMs). Of particular interest is the classification of nonergodic datastreams that have noise corruption with time-varying statistics. The TNE and LAM based classifiers discussed herein have been successfully applied to the computation of object classification in hyperspectral
International Nuclear Information System (INIS)
Bina, B.; Guenaydin, M.
1997-01-01
We give a complete classification of the real forms of simple non-linear superconformal algebras (SCA) and quasi-superconformal algebras (QSCA) and present a unified realization of these algebras with simple symmetry groups. This classification is achieved by establishing a correspondence between simple non-linear QSCA's and SCA's and quaternionic and super-quaternionic symmetric spaces of simple Lie groups and Lie supergroups, respectively. The unified realization we present involves a dimension zero scalar field (dilaton), dimension-1 symmetry currents, and dimension-1/2 free bosons for QSCA's and dimension-1/2 free fermions for SCA's. The free bosons and fermions are associated with the quaternionic and super-quaternionic symmetric spaces of corresponding Lie groups and Lie supergroups, respectively. We conclude with a discussion of possible applications of our results. (orig.)
Motion Cueing Algorithm Development: Human-Centered Linear and Nonlinear Approaches
Houck, Jacob A. (Technical Monitor); Telban, Robert J.; Cardullo, Frank M.
2005-01-01
While the performance of flight simulator motion system hardware has advanced substantially, the development of the motion cueing algorithm, the software that transforms simulated aircraft dynamics into realizable motion commands, has not kept pace. Prior research identified viable features from two algorithms: the nonlinear "adaptive algorithm", and the "optimal algorithm" that incorporates human vestibular models. A novel approach to motion cueing, the "nonlinear algorithm" is introduced that combines features from both approaches. This algorithm is formulated by optimal control, and incorporates a new integrated perception model that includes both visual and vestibular sensation and the interaction between the stimuli. Using a time-varying control law, the matrix Riccati equation is updated in real time by a neurocomputing approach. Preliminary pilot testing resulted in the optimal algorithm incorporating a new otolith model, producing improved motion cues. The nonlinear algorithm vertical mode produced a motion cue with a time-varying washout, sustaining small cues for longer durations and washing out large cues more quickly compared to the optimal algorithm. The inclusion of the integrated perception model improved the responses to longitudinal and lateral cues. False cues observed with the NASA adaptive algorithm were absent. The neurocomputing approach was crucial in that the number of presentations of an input vector could be reduced to meet the real time requirement without degrading the quality of the motion cues.
New preconditioned conjugate gradient algorithms for nonlinear unconstrained optimization problems
International Nuclear Information System (INIS)
Al-Bayati, A.; Al-Asadi, N.
1997-01-01
This paper presents two new predilection conjugate gradient algorithms for nonlinear unconstrained optimization problems and examines their computational performance. Computational experience shows that the new proposed algorithms generally imp lone the efficiency of Nazareth's [13] preconditioned conjugate gradient algorithm. (authors). 16 refs., 1 tab
Directory of Open Access Journals (Sweden)
Viktoriia Boiko
2016-02-01
Full Text Available The paper specifies basic stages of developing and realizing the strategy of enhancing competitiveness of enterprises and represents an appropriate algorithm. The study analyzes the economic indexes and results of the activity of the agrarian enterprises in Kherson region and provides competitive strategies of efficient development of agrarian enterprises with different levels of competitiveness and specifies the ways of realizing them which will contribute to the optimal use of the available strategic potential
Algorithms for non-linear M-estimation
DEFF Research Database (Denmark)
Madsen, Kaj; Edlund, O; Ekblom, H
1997-01-01
In non-linear regression, the least squares method is most often used. Since this estimator is highly sensitive to outliers in the data, alternatives have became increasingly popular during the last decades. We present algorithms for non-linear M-estimation. A trust region approach is used, where...
Ghosh, A
1988-08-01
Lanczos and conjugate gradient algorithms are important in computational linear algebra. In this paper, a parallel pipelined realization of these algorithms on a ring of optical linear algebra processors is described. The flow of data is designed to minimize the idle times of the optical multiprocessor and the redundancy of computations. The effects of optical round-off errors on the solutions obtained by the optical Lanczos and conjugate gradient algorithms are analyzed, and it is shown that optical preconditioning can improve the accuracy of these algorithms substantially. Algorithms for optical preconditioning and results of numerical experiments on solving linear systems of equations arising from partial differential equations are discussed. Since the Lanczos algorithm is used mostly with sparse matrices, a folded storage scheme to represent sparse matrices on spatial light modulators is also described.
Nonlinear symmetry realizations and the generalized CP sup(n-1) model
International Nuclear Information System (INIS)
Santos, T.A.
1982-01-01
The genralized CP sup(n-1) model having U(p) as Gauge group in the two-dimension Euclidean space in the several existing formulations is presented. Such a model is described as a nonlinear symmetry realization which becames linear when restricted to a determined sub-groups treating therefore of fields which have values in the quocient space G/H. Classical instanton and meron solutions for this model are presented and the existence of a mechanism to generate a family of non auto-dual solutions with finite action, taking as starting point the instanton solutions, is demonstrated. (L.C.) [pt
Hardware realization of a fast neural network algorithm for real-time tracking in HEP experiments
International Nuclear Information System (INIS)
Leimgruber, F.R.; Pavlopoulos, P.; Steinacher, M.; Tauscher, L.; Vlachos, S.; Wendler, H.
1995-01-01
A fast pattern recognition system for HEP experiments, based on artificial neural network algorithms (ANN), has been realized with standard electronics. The multiplicity and location of tracks in an event are determined in less than 75 ns. Hardware modules of this first level trigger were extensively tested for performance and reliability with data from the CPLEAR experiment. (orig.)
Improved algorithm for solving nonlinear parabolized stability equations
Zhao, Lei; Zhang, Cun-bo; Liu, Jian-xin; Luo, Ji-sheng
2016-08-01
Due to its high computational efficiency and ability to consider nonparallel and nonlinear effects, nonlinear parabolized stability equations (NPSE) approach has been widely used to study the stability and transition mechanisms. However, it often diverges in hypersonic boundary layers when the amplitude of disturbance reaches a certain level. In this study, an improved algorithm for solving NPSE is developed. In this algorithm, the mean flow distortion is included into the linear operator instead of into the nonlinear forcing terms in NPSE. An under-relaxation factor for computing the nonlinear terms is introduced during the iteration process to guarantee the robustness of the algorithm. Two case studies, the nonlinear development of stationary crossflow vortices and the fundamental resonance of the second mode disturbance in hypersonic boundary layers, are presented to validate the proposed algorithm for NPSE. Results from direct numerical simulation (DNS) are regarded as the baseline for comparison. Good agreement can be found between the proposed algorithm and DNS, which indicates the great potential of the proposed method on studying the crossflow and streamwise instability in hypersonic boundary layers. Project supported by the National Natural Science Foundation of China (Grant Nos. 11332007 and 11402167).
Improved algorithm for solving nonlinear parabolized stability equations
International Nuclear Information System (INIS)
Zhao Lei; Zhang Cun-bo; Liu Jian-xin; Luo Ji-sheng
2016-01-01
Due to its high computational efficiency and ability to consider nonparallel and nonlinear effects, nonlinear parabolized stability equations (NPSE) approach has been widely used to study the stability and transition mechanisms. However, it often diverges in hypersonic boundary layers when the amplitude of disturbance reaches a certain level. In this study, an improved algorithm for solving NPSE is developed. In this algorithm, the mean flow distortion is included into the linear operator instead of into the nonlinear forcing terms in NPSE. An under-relaxation factor for computing the nonlinear terms is introduced during the iteration process to guarantee the robustness of the algorithm. Two case studies, the nonlinear development of stationary crossflow vortices and the fundamental resonance of the second mode disturbance in hypersonic boundary layers, are presented to validate the proposed algorithm for NPSE. Results from direct numerical simulation (DNS) are regarded as the baseline for comparison. Good agreement can be found between the proposed algorithm and DNS, which indicates the great potential of the proposed method on studying the crossflow and streamwise instability in hypersonic boundary layers. (paper)
On the Fock space realizations of nonlinear algebras describing the high spin fields in AdS spaces
International Nuclear Information System (INIS)
Burdik, C.; Navratil, O.; Pashnev, A.
2002-01-01
The method of construction of Fock space realizations of Lie algebras is generalized for nonlinear algebras. We consider as an example the nonlinear algebra of constraints which describe the totally symmetric fields with higher spins in the AdS space-time
Telban, Robert J.
While the performance of flight simulator motion system hardware has advanced substantially, the development of the motion cueing algorithm, the software that transforms simulated aircraft dynamics into realizable motion commands, has not kept pace. To address this, new human-centered motion cueing algorithms were developed. A revised "optimal algorithm" uses time-invariant filters developed by optimal control, incorporating human vestibular system models. The "nonlinear algorithm" is a novel approach that is also formulated by optimal control, but can also be updated in real time. It incorporates a new integrated visual-vestibular perception model that includes both visual and vestibular sensation and the interaction between the stimuli. A time-varying control law requires the matrix Riccati equation to be solved in real time by a neurocomputing approach. Preliminary pilot testing resulted in the optimal algorithm incorporating a new otolith model, producing improved motion cues. The nonlinear algorithm vertical mode produced a motion cue with a time-varying washout, sustaining small cues for longer durations and washing out large cues more quickly compared to the optimal algorithm. The inclusion of the integrated perception model improved the responses to longitudinal and lateral cues. False cues observed with the NASA adaptive algorithm were absent. As a result of unsatisfactory sensation, an augmented turbulence cue was added to the vertical mode for both the optimal and nonlinear algorithms. The relative effectiveness of the algorithms, in simulating aircraft maneuvers, was assessed with an eleven-subject piloted performance test conducted on the NASA Langley Visual Motion Simulator (VMS). Two methods, the quasi-objective NASA Task Load Index (TLX), and power spectral density analysis of pilot control, were used to assess pilot workload. TLX analysis reveals, in most cases, less workload and variation among pilots with the nonlinear algorithm. Control input
Modification of Brueschweiler quantum searching algorithm and realization by NMR experiment
International Nuclear Information System (INIS)
Yang Xiaodong; Wei Daxiu; Luo Jun; Miao Xijia
2002-01-01
In recent years, quantum computing research has made big progress, which exploit quantum mechanical laws, such as interference, superposition and parallelism, to perform computing tasks. The most inducing thing is that the quantum computing can provide large rise to the speedup in quantum algorithm. Quantum computing can solve some problems, which are impossible or difficult for the classical computing. The problem of searching for a specific item in an unsorted database can be solved with certain quantum algorithm, for example, Grover quantum algorithm and Brueschweiler quantum algorithm. The former gives a quadratic speedup, and the latter gives an exponential speedup comparing with the corresponding classical algorithm. In Brueschweiler quantum searching algorithm, the data qubit and the read-out qubit (the ancilla qubit) are different qubits. The authors have studied Brueschweiler algorithm and proposed a modified version, in which no ancilla qubit is needed to reach exponential speedup in the searching, the data and the read-out qubit are the same qubits. The modified Brueschweiler algorithm can be easier to design and realize. The authors also demonstrate the modified Brueschweiler algorithm in a 3-qubit molecular system by Nuclear Magnetic Resonance (NMR) experiment
Applications and algorithms for mixed integer nonlinear programming
International Nuclear Information System (INIS)
Leyffer, Sven; Munson, Todd; Linderoth, Jeff; Luedtke, James; Miller, Andrew
2009-01-01
The mathematical modeling of systems often requires the use of both nonlinear and discrete components. Discrete decision variables model dichotomies, discontinuities, and general logical relationships. Nonlinear functions are required to accurately represent physical properties such as pressure, stress, temperature, and equilibrium. Problems involving both discrete variables and nonlinear constraint functions are known as mixed-integer nonlinear programs (MINLPs) and are among the most challenging computational optimization problems faced by researchers and practitioners. In this paper, we describe relevant scientific applications that are naturally modeled as MINLPs, we provide an overview of available algorithms and software, and we describe ongoing methodological advances for solving MINLPs. These algorithmic advances are making increasingly larger instances of this important family of problems tractable.
A Linearized Relaxing Algorithm for the Specific Nonlinear Optimization Problem
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Mio Horai
2016-01-01
Full Text Available We propose a new method for the specific nonlinear and nonconvex global optimization problem by using a linear relaxation technique. To simplify the specific nonlinear and nonconvex optimization problem, we transform the problem to the lower linear relaxation form, and we solve the linear relaxation optimization problem by the Branch and Bound Algorithm. Under some reasonable assumptions, the global convergence of the algorithm is certified for the problem. Numerical results show that this method is more efficient than the previous methods.
Bayesian estimation of realized stochastic volatility model by Hybrid Monte Carlo algorithm
International Nuclear Information System (INIS)
Takaishi, Tetsuya
2014-01-01
The hybrid Monte Carlo algorithm (HMCA) is applied for Bayesian parameter estimation of the realized stochastic volatility (RSV) model. Using the 2nd order minimum norm integrator (2MNI) for the molecular dynamics (MD) simulation in the HMCA, we find that the 2MNI is more efficient than the conventional leapfrog integrator. We also find that the autocorrelation time of the volatility variables sampled by the HMCA is very short. Thus it is concluded that the HMCA with the 2MNI is an efficient algorithm for parameter estimations of the RSV model
Impulse position control algorithms for nonlinear systems
Energy Technology Data Exchange (ETDEWEB)
Sesekin, A. N., E-mail: sesekin@list.ru [Ural Federal University, 19 S. Mira, Ekaterinburg, 620002 (Russian Federation); Institute of Mathematics and Mechanics, Ural Division of Russian Academy of Sciences, 16 S. Kovalevskaya, Ekaterinburg, 620990 (Russian Federation); Nepp, A. N., E-mail: anepp@urfu.ru [Ural Federal University, 19 S. Mira, Ekaterinburg, 620002 (Russian Federation)
2015-11-30
The article is devoted to the formalization and description of impulse-sliding regime in nonlinear dynamical systems that arise in the application of impulse position controls of a special kind. The concept of trajectory impulse-sliding regime formalized as some limiting network element Euler polygons generated by a discrete approximation of the impulse position control This paper differs from the previously published papers in that it uses a definition of solutions of systems with impulse controls, it based on the closure of the set of smooth solutions in the space of functions of bounded variation. The need for the study of such regimes is the fact that they often arise when parry disturbances acting on technical or economic control system.
Impulse position control algorithms for nonlinear systems
Sesekin, A. N.; Nepp, A. N.
2015-11-01
The article is devoted to the formalization and description of impulse-sliding regime in nonlinear dynamical systems that arise in the application of impulse position controls of a special kind. The concept of trajectory impulse-sliding regime formalized as some limiting network element Euler polygons generated by a discrete approximation of the impulse position control This paper differs from the previously published papers in that it uses a definition of solutions of systems with impulse controls, it based on the closure of the set of smooth solutions in the space of functions of bounded variation. The need for the study of such regimes is the fact that they often arise when parry disturbances acting on technical or economic control system.
Realization of 3D evaluation algorithm in dose-guided radiotherapy
International Nuclear Information System (INIS)
Wang Yu; Li Gui; Wang Dong; Wu Yican; FDS Team
2012-01-01
3D evaluation algorithm instead of 2D evaluation method of clinical dose verification is highly needed for dose evaluation in Dose-guided Radiotherapy. 3D evaluation algorithm of three evaluation methods, including Dose Difference, Distance-To-Agreement and 7 Analysis, was realized by the tool of Visual C++ according to the formula. Two plans were designed to test the algorithm, plan 1 was radiation on equivalent water using square field for the verification of the algorithm's correctness; plan 2 was radiation on the emulation head phantom using conformal field for the verification of the algorithm's practicality. For plan 1, the dose difference, in the tolerance range has a pass rate of 100%, the Distance-To-Agreement and 7 analysis was of a pass rate of 100% in the tolerance range, and a pass rate of 99±1% at the boundary of range. For plan 2, the pass rate of algorithm were 88.35%, 100%, 95.07% for the three evaluation methods, respectively. It can be concluded that the 3D evaluation algorithm is feasible and could be used to evaluate 3D dose distributions in Dose-guided Radiotherapy. (authors)
Sparse Nonlinear Electromagnetic Imaging Accelerated With Projected Steepest Descent Algorithm
Desmal, Abdulla
2017-04-03
An efficient electromagnetic inversion scheme for imaging sparse 3-D domains is proposed. The scheme achieves its efficiency and accuracy by integrating two concepts. First, the nonlinear optimization problem is constrained using L₀ or L₁-norm of the solution as the penalty term to alleviate the ill-posedness of the inverse problem. The resulting Tikhonov minimization problem is solved using nonlinear Landweber iterations (NLW). Second, the efficiency of the NLW is significantly increased using a steepest descent algorithm. The algorithm uses a projection operator to enforce the sparsity constraint by thresholding the solution at every iteration. Thresholding level and iteration step are selected carefully to increase the efficiency without sacrificing the convergence of the algorithm. Numerical results demonstrate the efficiency and accuracy of the proposed imaging scheme in reconstructing sparse 3-D dielectric profiles.
Campoamor-Stursberg, R.
2018-03-01
A procedure for the construction of nonlinear realizations of Lie algebras in the context of Vessiot-Guldberg-Lie algebras of first-order systems of ordinary differential equations (ODEs) is proposed. The method is based on the reduction of invariants and projection of lowest-dimensional (irreducible) representations of Lie algebras. Applications to the description of parameterized first-order systems of ODEs related by contraction of Lie algebras are given. In particular, the kinematical Lie algebras in (2 + 1)- and (3 + 1)-dimensions are realized simultaneously as Vessiot-Guldberg-Lie algebras of parameterized nonlinear systems in R3 and R4, respectively.
Concise quantum associative memories with nonlinear search algorithm
International Nuclear Information System (INIS)
Tchapet Njafa, J.P.; Nana Engo, S.G.
2016-01-01
The model of Quantum Associative Memories (QAM) we propose here consists in simplifying and generalizing that of Rigui Zhou et al. [1] which uses the quantum matrix with the binary decision diagram put forth by David Rosenbaum [2] and the Abrams and Lloyd's nonlinear search algorithm [3]. Our model gives the possibility to retrieve one of the sought states in multi-values retrieving scheme when a measurement is done on the first register in O(c-r) time complexity. It is better than Grover's algorithm and its modified form which need O(√((2 n )/(m))) steps when they are used as the retrieval algorithm. n is the number of qubits of the first register and m the number of x values for which f(x) = 1. As the nonlinearity makes the system highly susceptible to the noise, an analysis of the influence of the single qubit noise channels on the Nonlinear Search Algorithm of our model of QAM shows a fidelity of about 0.7 whatever the number of qubits existing in the first register, thus demonstrating the robustness of our model. (copyright 2016 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)
Evolutionary algorithm based heuristic scheme for nonlinear heat transfer equations.
Ullah, Azmat; Malik, Suheel Abdullah; Alimgeer, Khurram Saleem
2018-01-01
In this paper, a hybrid heuristic scheme based on two different basis functions i.e. Log Sigmoid and Bernstein Polynomial with unknown parameters is used for solving the nonlinear heat transfer equations efficiently. The proposed technique transforms the given nonlinear ordinary differential equation into an equivalent global error minimization problem. Trial solution for the given nonlinear differential equation is formulated using a fitness function with unknown parameters. The proposed hybrid scheme of Genetic Algorithm (GA) with Interior Point Algorithm (IPA) is opted to solve the minimization problem and to achieve the optimal values of unknown parameters. The effectiveness of the proposed scheme is validated by solving nonlinear heat transfer equations. The results obtained by the proposed scheme are compared and found in sharp agreement with both the exact solution and solution obtained by Haar Wavelet-Quasilinearization technique which witnesses the effectiveness and viability of the suggested scheme. Moreover, the statistical analysis is also conducted for investigating the stability and reliability of the presented scheme.
Evolutionary algorithm based heuristic scheme for nonlinear heat transfer equations.
Directory of Open Access Journals (Sweden)
Azmat Ullah
Full Text Available In this paper, a hybrid heuristic scheme based on two different basis functions i.e. Log Sigmoid and Bernstein Polynomial with unknown parameters is used for solving the nonlinear heat transfer equations efficiently. The proposed technique transforms the given nonlinear ordinary differential equation into an equivalent global error minimization problem. Trial solution for the given nonlinear differential equation is formulated using a fitness function with unknown parameters. The proposed hybrid scheme of Genetic Algorithm (GA with Interior Point Algorithm (IPA is opted to solve the minimization problem and to achieve the optimal values of unknown parameters. The effectiveness of the proposed scheme is validated by solving nonlinear heat transfer equations. The results obtained by the proposed scheme are compared and found in sharp agreement with both the exact solution and solution obtained by Haar Wavelet-Quasilinearization technique which witnesses the effectiveness and viability of the suggested scheme. Moreover, the statistical analysis is also conducted for investigating the stability and reliability of the presented scheme.
Iterative Nonlinear Tikhonov Algorithm with Constraints for Electromagnetic Tomography
Xu, Feng; Deshpande, Manohar
2012-01-01
Low frequency electromagnetic tomography such as the capacitance tomography (ECT) has been proposed for monitoring and mass-gauging of gas-liquid two-phase system under microgravity condition in NASA's future long-term space missions. Due to the ill-posed inverse problem of ECT, images reconstructed using conventional linear algorithms often suffer from limitations such as low resolution and blurred edges. Hence, new efficient high resolution nonlinear imaging algorithms are needed for accurate two-phase imaging. The proposed Iterative Nonlinear Tikhonov Regularized Algorithm with Constraints (INTAC) is based on an efficient finite element method (FEM) forward model of quasi-static electromagnetic problem. It iteratively minimizes the discrepancy between FEM simulated and actual measured capacitances by adjusting the reconstructed image using the Tikhonov regularized method. More importantly, it enforces the known permittivity of two phases to the unknown pixels which exceed the reasonable range of permittivity in each iteration. This strategy does not only stabilize the converging process, but also produces sharper images. Simulations show that resolution improvement of over 2 times can be achieved by INTAC with respect to conventional approaches. Strategies to further improve spatial imaging resolution are suggested, as well as techniques to accelerate nonlinear forward model and thus increase the temporal resolution.
Experimental realization of a one-way quantum computer algorithm solving Simon's problem.
Tame, M S; Bell, B A; Di Franco, C; Wadsworth, W J; Rarity, J G
2014-11-14
We report an experimental demonstration of a one-way implementation of a quantum algorithm solving Simon's problem-a black-box period-finding problem that has an exponential gap between the classical and quantum runtime. Using an all-optical setup and modifying the bases of single-qubit measurements on a five-qubit cluster state, key representative functions of the logical two-qubit version's black box can be queried and solved. To the best of our knowledge, this work represents the first experimental realization of the quantum algorithm solving Simon's problem. The experimental results are in excellent agreement with the theoretical model, demonstrating the successful performance of the algorithm. With a view to scaling up to larger numbers of qubits, we analyze the resource requirements for an n-qubit version. This work helps highlight how one-way quantum computing provides a practical route to experimentally investigating the quantum-classical gap in the query complexity model.
Directory of Open Access Journals (Sweden)
ALEX RAJ S. M.
2017-09-01
Full Text Available Underwater images raise new challenges in the field of digital image processing technology in recent years because of its widespread applications. There are many tangled matters to be considered in processing of images collected from water medium due to the adverse effects imposed by the environment itself. Image segmentation is preferred as basal stage of many digital image processing techniques which distinguish multiple segments in an image and reveal the hidden crucial information required for a peculiar application. There are so many general purpose algorithms and techniques that have been developed for image segmentation. Discontinuity based segmentation are most promising approach for image segmentation, in which Canny Edge detection based segmentation is more preferred for its high level of noise immunity and ability to tackle underwater environment. Since dealing with real time underwater image segmentation algorithm, which is computationally complex enough, an efficient hardware implementation is to be considered. The FPGA based realization of the referred segmentation algorithm is presented in this paper.
SINS/CNS Nonlinear Integrated Navigation Algorithm for Hypersonic Vehicle
Directory of Open Access Journals (Sweden)
Yong-jun Yu
2015-01-01
Full Text Available Celestial Navigation System (CNS has characteristics of accurate orientation and strong autonomy and has been widely used in Hypersonic Vehicle. Since the CNS location and orientation mainly depend upon the inertial reference that contains errors caused by gyro drifts and other error factors, traditional Strap-down Inertial Navigation System (SINS/CNS positioning algorithm setting the position error between SINS and CNS as measurement is not effective. The model of altitude azimuth, platform error angles, and horizontal position is designed, and the SINS/CNS tightly integrated algorithm is designed, in which CNS altitude azimuth is set as measurement information. GPF (Gaussian particle filter is introduced to solve the problem of nonlinear filtering. The results of simulation show that the precision of SINS/CNS algorithm which reaches 130 m using three stars is improved effectively.
Bonus algorithm for large scale stochastic nonlinear programming problems
Diwekar, Urmila
2015-01-01
This book presents the details of the BONUS algorithm and its real world applications in areas like sensor placement in large scale drinking water networks, sensor placement in advanced power systems, water management in power systems, and capacity expansion of energy systems. A generalized method for stochastic nonlinear programming based on a sampling based approach for uncertainty analysis and statistical reweighting to obtain probability information is demonstrated in this book. Stochastic optimization problems are difficult to solve since they involve dealing with optimization and uncertainty loops. There are two fundamental approaches used to solve such problems. The first being the decomposition techniques and the second method identifies problem specific structures and transforms the problem into a deterministic nonlinear programming problem. These techniques have significant limitations on either the objective function type or the underlying distributions for the uncertain variables. Moreover, these ...
A Nonlinear GMRES Optimization Algorithm for Canonical Tensor Decomposition
De Sterck, Hans
2011-01-01
A new algorithm is presented for computing a canonical rank-R tensor approximation that has minimal distance to a given tensor in the Frobenius norm, where the canonical rank-R tensor consists of the sum of R rank-one components. Each iteration of the method consists of three steps. In the first step, a tentative new iterate is generated by a stand-alone one-step process, for which we use alternating least squares (ALS). In the second step, an accelerated iterate is generated by a nonlinear g...
Genetic algorithms applied to nonlinear and complex domains; TOPICAL
International Nuclear Information System (INIS)
Barash, D; Woodin, A E
1999-01-01
The dissertation, titled ''Genetic Algorithms Applied to Nonlinear and Complex Domains'', describes and then applies a new class of powerful search algorithms (GAS) to certain domains. GAS are capable of solving complex and nonlinear problems where many parameters interact to produce a ''final'' result such as the optimization of the laser pulse in the interaction of an atom with an intense laser field. GAS can very efficiently locate the global maximum by searching parameter space in problems which are unsuitable for a search using traditional methods. In particular, the dissertation contains new scientific findings in two areas. First, the dissertation examines the interaction of an ultra-intense short laser pulse with atoms. GAS are used to find the optimal frequency for stabilizing atoms in the ionization process. This leads to a new theoretical formulation, to explain what is happening during the ionization process and how the electron is responding to finite (real-life) laser pulse shapes. It is shown that the dynamics of the process can be very sensitive to the ramp of the pulse at high frequencies. The new theory which is formulated, also uses a novel concept (known as the (t,t') method) to numerically solve the time-dependent Schrodinger equation Second, the dissertation also examines the use of GAS in modeling decision making problems. It compares GAS with traditional techniques to solve a class of problems known as Markov Decision Processes. The conclusion of the dissertation should give a clear idea of where GAS are applicable, especially in the physical sciences, in problems which are nonlinear and complex, i.e. difficult to analyze by other means
Genetic algorithms applied to nonlinear and complex domains
International Nuclear Information System (INIS)
Barash, D; Woodin, A E
1999-01-01
The dissertation, titled ''Genetic Algorithms Applied to Nonlinear and Complex Domains'', describes and then applies a new class of powerful search algorithms (GAS) to certain domains. GAS are capable of solving complex and nonlinear problems where many parameters interact to produce a ''final'' result such as the optimization of the laser pulse in the interaction of an atom with an intense laser field. GAS can very efficiently locate the global maximum by searching parameter space in problems which are unsuitable for a search using traditional methods. In particular, the dissertation contains new scientific findings in two areas. First, the dissertation examines the interaction of an ultra-intense short laser pulse with atoms. GAS are used to find the optimal frequency for stabilizing atoms in the ionization process. This leads to a new theoretical formulation, to explain what is happening during the ionization process and how the electron is responding to finite (real-life) laser pulse shapes. It is shown that the dynamics of the process can be very sensitive to the ramp of the pulse at high frequencies. The new theory which is formulated, also uses a novel concept (known as the (t,t') method) to numerically solve the time-dependent Schrodinger equation Second, the dissertation also examines the use of GAS in modeling decision making problems. It compares GAS with traditional techniques to solve a class of problems known as Markov Decision Processes. The conclusion of the dissertation should give a clear idea of where GAS are applicable, especially in the physical sciences, in problems which are nonlinear and complex, i.e. difficult to analyze by other means
Data Reduction Algorithm Using Nonnegative Matrix Factorization with Nonlinear Constraints
Sembiring, Pasukat
2017-12-01
Processing ofdata with very large dimensions has been a hot topic in recent decades. Various techniques have been proposed in order to execute the desired information or structure. Non- Negative Matrix Factorization (NMF) based on non-negatives data has become one of the popular methods for shrinking dimensions. The main strength of this method is non-negative object, the object model by a combination of some basic non-negative parts, so as to provide a physical interpretation of the object construction. The NMF is a dimension reduction method thathasbeen used widely for numerous applications including computer vision,text mining, pattern recognitions,and bioinformatics. Mathematical formulation for NMF did not appear as a convex optimization problem and various types of algorithms have been proposed to solve the problem. The Framework of Alternative Nonnegative Least Square(ANLS) are the coordinates of the block formulation approaches that have been proven reliable theoretically and empirically efficient. This paper proposes a new algorithm to solve NMF problem based on the framework of ANLS.This algorithm inherits the convergenceproperty of the ANLS framework to nonlinear constraints NMF formulations.
An algorithm for nonlinear thermal analysis of fuel bearing pads
International Nuclear Information System (INIS)
Attia, M.H.; D'Silva, N.
1983-01-01
An algorithm has been developed for accurate prediction of the temperature field in a CANDU fuel bearing pad and the extent of the nucleate boiling in the crevice region. The methodology recognizes the nonlinear nature of the problem due to the fact that local boiling is both controlling and being controlled by the conditions of heat transfer at the boundaries. The finite difference model accounts for the volumetric effect of the thermal contact resistance at the bearing pad/pressure tube interface. It also allows the evaluation of the thermal barrier effect caused by applying an oxide film on the radiused surface of the bearing pad. Information pertaining to the distribution of the coefficient of heat transfer over water-cooled surfaces has been generated. Analysis of the results indicated the significance of considering the nonlinear behaviour of the system in determining its state of equilibrium. It also indicated that, depending on the thickness of the oxide layer and the position of the bearing pad along the core of the reactor, the nucleate boiling process can be prevented
International Nuclear Information System (INIS)
Wang Yanfang; Liu Li; Yan Yonglian; Shan Baoci; Tang Xiaowei
2007-01-01
A new algorithm of segmenting contour series of images is presented, which can achieve three dimension reconstruction with parametric recognition in Reverse Engineering based on X-ray CT. First, in order to get the nested relationship between contours, a method of a certain angle ray is used. Second, for realizing the contour location in one slice, another approach is presented to generate the contour tree by scanning the relevant vector only once. Last, a judge algorithm is put forward to accomplish the contour match between slices by adopting the qualitative and quantitative properties. The example shows that this algorithm can segment contour series of CT parts rapidly and precisely. (authors)
Non-linear realizations of superconformal and W-algebras as embeddings of strings
International Nuclear Information System (INIS)
Bellucci, S.
1998-01-01
We propose a simple method for constructing representations of (super)conformal and non-linear W-type algebras in terms of their subalgebras and corresponding Nambu-Goldstone fields. We apply it to N=2 and N=1 superconformal algebras and describe in this way various embeddings of strings and superstrings for which these algebras and their subalgebras define world-sheet symmetries. Besides reproducing the known examples, we present some new ones, in particular an embedding of the bosonic string with additional U(1) affine symmetry into N=2 superstring. We also apply our method to the non-linear W 3 (2) algebra and demonstrate that the linearization procedure worked out for it some time ago gets a natural interpretation as a kind of string embedding. All these embeddings include the critical ones as particular cases. (orig.)
Nonlinear realizations of superconformal and W algebras as embeddings of strings
International Nuclear Information System (INIS)
Bellucci, S.; Gribanov, V.; Ivanov, E.; Krivonos, S.; Pashnev, A.
1997-07-01
The authors propose a simple method for constructing representations of (super)conformal and nonlinear W -type algebras in terms of their subalgebras and corresponding Nambu-Goldstone fields. They apply it to N = 2 and N = 1 superconformal algebras and describe in this way various embeddings of strings and superstrings for which these algebras and their subalgebras define worked-sheet symmetries. Besides reproducing the known examples, they present some new ones, in particular an embedding of the bosonic string with additional U (1) affine symmetry into N = 2 superstring. They also apply their method to the nonlinear W 3 (2) algebra and demonstrate that the linearization procedure worked out for ti some time ago gets a natural interpretation as a kind of string embedding. All these embeddings include the critical ones as particular cases
Realization and optimization of AES algorithm on the TMS320DM6446 based on DaVinci technology
Jia, Wen-bin; Xiao, Fu-hai
2013-03-01
The application of AES algorithm in the digital cinema system avoids video data to be illegal theft or malicious tampering, and solves its security problems. At the same time, in order to meet the requirements of the real-time, scene and transparent encryption of high-speed data streams of audio and video in the information security field, through the in-depth analysis of AES algorithm principle, based on the hardware platform of TMS320DM6446, with the software framework structure of DaVinci, this paper proposes the specific realization methods of AES algorithm in digital video system and its optimization solutions. The test results show digital movies encrypted by AES128 can not play normally, which ensures the security of digital movies. Through the comparison of the performance of AES128 algorithm before optimization and after, the correctness and validity of improved algorithm is verified.
A Design of a Hybrid Non-Linear Control Algorithm
Directory of Open Access Journals (Sweden)
Farinaz Behrooz
2017-11-01
Full Text Available One of the high energy consuming devices in the buildings is the air-conditioning system. Designing a proper controller to consider the thermal comfort and simultaneously control the energy usage of the device will impact on the system energy efficiency and its performance. The aim of this study was to design a Multiple-Input and Multiple-Output (MIMO, non-linear, and intelligent controller on direct expansion air-conditioning system The control algorithm uses the Fuzzy Cognitive Map method as a main controller and the Generalized Predictive Control method is used for assigning the initial weights of the main controller. The results of the proposed controller shows that the controller was successfully designed and works in set point tracking and under disturbance rejection tests. The obtained results of the Generalized Predictive Control-Fuzzy Cognitive Map controller are compared with the previous MIMO Linear Quadratic Gaussian control design on the same direct expansion air-conditioning system under the same conditions. The comparative results indicate energy savings would be achieved with the proposed controller with long-term usage. Energy efficiency and thermal comfort conditions are achieved by the proposed controller.
Supersymmetric models for quarks and leptons with nonlinearly realized E8 symmetry
International Nuclear Information System (INIS)
Ong, C.L.
1985-01-01
We propose three supersymmetric nonlinear sigma models with global symmetry E 8 . The models can accommodate three left-handed families of quarks and leptons without incurring the Adler-Bell-Jackiw anomaly with respect to either the standard SU(3) x SU(2) x U(1) gauge group, or the SU(5), or SO(10) grand unifying gauge group. They also predict unambiguously a right-handed, fourth family of quarks and leptons. In order to explore the structure of the models, we develop a differential-form formulation of the Kahler manifolds, resulting in general expressions for the curvature tensors and other geometrical objects in terms of the structure constants of the algebra, and the squashing parameters. These results, in turn, facilitate a general method for determining the Lagrangian to quartic order, and so the structure of the inherent four-fermion interactions of the models. We observe that the Kahlerian condition dω = 0 on the fundamental two-form ω greatly reduces the number of the independent squashing parameters. We also point out two plausible mechanisms for symmetry breaking, involving gravity
Domí nguez, Luis F.; Pistikopoulos, Efstratios N.
2012-01-01
An algorithm for the solution of convex multiparametric mixed-integer nonlinear programming problems arising in process engineering problems under uncertainty is introduced. The proposed algorithm iterates between a multiparametric nonlinear
A cellular automata based FPGA realization of a new metaheuristic bat-inspired algorithm
Progias, Pavlos; Amanatiadis, Angelos A.; Spataro, William; Trunfio, Giuseppe A.; Sirakoulis, Georgios Ch.
2016-10-01
Optimization algorithms are often inspired by processes occuring in nature, such as animal behavioral patterns. The main concern with implementing such algorithms in software is the large amounts of processing power they require. In contrast to software code, that can only perform calculations in a serial manner, an implementation in hardware, exploiting the inherent parallelism of single-purpose processors, can prove to be much more efficient both in speed and energy consumption. Furthermore, the use of Cellular Automata (CA) in such an implementation would be efficient both as a model for natural processes, as well as a computational paradigm implemented well on hardware. In this paper, we propose a VHDL implementation of a metaheuristic algorithm inspired by the echolocation behavior of bats. More specifically, the CA model is inspired by the metaheuristic algorithm proposed earlier in the literature, which could be considered at least as efficient than other existing optimization algorithms. The function of the FPGA implementation of our algorithm is explained in full detail and results of our simulations are also demonstrated.
International Nuclear Information System (INIS)
Dhenaut, Christophe
1995-01-01
Conception of new organic materials for nonlinear optics is generally driven by a molecular engineering approach. The usual technique for determining the quadratic hyper polarizability of designed molecules is the electric field induced second harmonic (EFISH) experiment. However this technique is limited to neutral molecules with a permanent dipole moment. We have realized an harmonic light scattering (HLS) experiment which allow the measurement of any kind of molecules, polar or non polar, neutral or ionic. Using this technique we have been able to demonstrate experimentally the validity of the octupole concept (molecules without dipole moment) which has been proposed recently. We have studied molecules corresponding to various octupolar geometries. Nonlinearities are found to be comparable to those of the best dipolar compounds. We have also investigated other molecular families with different symmetry such as polyenes, sub-phthalocyanines and phthalocyanines by EFISH and HLS techniques. We have confronted results obtained by the two experiments. It appears that these results are not easy to compare, the tensorial components accessible by each experiment being different. The two experiments seems complementary. HLS experiments allow the observation of a quadratic hyper polarizability for centrosymmetric molecules. This surprising observation could be explained by the contribution of a vibration al part to the hyper polarizability measured by HLS (but not present in EFISH). Interpretation of this dynamic process is still in progress. (author) [fr
Directory of Open Access Journals (Sweden)
A. K. CHOWDHURY
2016-02-01
Full Text Available In this paper an evolutionary technique for synthesizing Multi-Valued Logic (MVL functions using Neural Network Deployment Algorithm (NNDA is presented. The algorithm is combined with back-propagation learning capability and neural MVL operators. This research article is done to observe the anomalistic characteristics of MVL neural operators and their role in synthesis. The advantages of NNDA-MVL algorithm is demonstrated with realization of synthesized many valued functions with lesser MVL operators. The characteristic feature set consists of MVL gate count, network link count, network propagation delay and accuracy achieved in training. In brief, this paper depicts an effort of reduced network size for synthesized MVL functions. Trained MVL operators improve the basic architecture by reducing MIN gate and interlink connection by 52.94% and 23.38% respectively.
International Nuclear Information System (INIS)
Huang, Xiaobiao; Safranek, James
2014-01-01
Nonlinear dynamics optimization is carried out for a low emittance upgrade lattice of SPEAR3 in order to improve its dynamic aperture and Touschek lifetime. Two multi-objective optimization algorithms, a genetic algorithm and a particle swarm algorithm, are used for this study. The performance of the two algorithms are compared. The result shows that the particle swarm algorithm converges significantly faster to similar or better solutions than the genetic algorithm and it does not require seeding of good solutions in the initial population. These advantages of the particle swarm algorithm may make it more suitable for many accelerator optimization applications
Energy Technology Data Exchange (ETDEWEB)
Huang, Xiaobiao, E-mail: xiahuang@slac.stanford.edu; Safranek, James
2014-09-01
Nonlinear dynamics optimization is carried out for a low emittance upgrade lattice of SPEAR3 in order to improve its dynamic aperture and Touschek lifetime. Two multi-objective optimization algorithms, a genetic algorithm and a particle swarm algorithm, are used for this study. The performance of the two algorithms are compared. The result shows that the particle swarm algorithm converges significantly faster to similar or better solutions than the genetic algorithm and it does not require seeding of good solutions in the initial population. These advantages of the particle swarm algorithm may make it more suitable for many accelerator optimization applications.
A Model Predictive Algorithm for Active Control of Nonlinear Noise Processes
Directory of Open Access Journals (Sweden)
Qi-Zhi Zhang
2005-01-01
Full Text Available In this paper, an improved nonlinear Active Noise Control (ANC system is achieved by introducing an appropriate secondary source. For ANC system to be successfully implemented, the nonlinearity of the primary path and time delay of the secondary path must be overcome. A nonlinear Model Predictive Control (MPC strategy is introduced to deal with the time delay in the secondary path and the nonlinearity in the primary path of the ANC system. An overall online modeling technique is utilized for online secondary path and primary path estimation. The secondary path is estimated using an adaptive FIR filter, and the primary path is estimated using a Neural Network (NN. The two models are connected in parallel with the two paths. In this system, the mutual disturbances between the operation of the nonlinear ANC controller and modeling of the secondary can be greatly reduced. The coefficients of the adaptive FIR filter and weight vector of NN are adjusted online. Computer simulations are carried out to compare the proposed nonlinear MPC method with the nonlinear Filter-x Least Mean Square (FXLMS algorithm. The results showed that the convergence speed of the proposed nonlinear MPC algorithm is faster than that of nonlinear FXLMS algorithm. For testing the robust performance of the proposed nonlinear ANC system, the sudden changes in the secondary path and primary path of the ANC system are considered. Results indicated that the proposed nonlinear ANC system can rapidly track the sudden changes in the acoustic paths of the nonlinear ANC system, and ensure the adaptive algorithm stable when the nonlinear ANC system is time variable.
International Nuclear Information System (INIS)
Baginyan, S.A.; Govorun, N.N.; Tkhang, T.L.; Shigaev, V.N.
1982-01-01
Software development minimum guidance system for measuring pictures of bubble chamber on the base of a scanner (HPD) and special hardware processor (SHP) is described. The algorithm of selective filter is proposed. The local software structure and functional specifications of its major parts are described. Some examples of processing picture from HBC-1 (JINR) are also presented
Experimental realization of Shor's quantum factoring algorithm using nuclear magnetic resonance.
Vandersypen, L M; Steffen, M; Breyta, G; Yannoni, C S; Sherwood, M H; Chuang, I L
The number of steps any classical computer requires in order to find the prime factors of an l-digit integer N increases exponentially with l, at least using algorithms known at present. Factoring large integers is therefore conjectured to be intractable classically, an observation underlying the security of widely used cryptographic codes. Quantum computers, however, could factor integers in only polynomial time, using Shor's quantum factoring algorithm. Although important for the study of quantum computers, experimental demonstration of this algorithm has proved elusive. Here we report an implementation of the simplest instance of Shor's algorithm: factorization of N = 15 (whose prime factors are 3 and 5). We use seven spin-1/2 nuclei in a molecule as quantum bits, which can be manipulated with room temperature liquid-state nuclear magnetic resonance techniques. This method of using nuclei to store quantum information is in principle scalable to systems containing many quantum bits, but such scalability is not implied by the present work. The significance of our work lies in the demonstration of experimental and theoretical techniques for precise control and modelling of complex quantum computers. In particular, we present a simple, parameter-free but predictive model of decoherence effects in our system.
Sparse Nonlinear Electromagnetic Imaging Accelerated With Projected Steepest Descent Algorithm
Desmal, Abdulla; Bagci, Hakan
2017-01-01
steepest descent algorithm. The algorithm uses a projection operator to enforce the sparsity constraint by thresholding the solution at every iteration. Thresholding level and iteration step are selected carefully to increase the efficiency without
Realization of a neural algorithm by means of front-propagation in a thyristor-based hybrid system
Niedernostheide, F J; Freyd, O; Bode, M; Gorbatyuk, A V
2003-01-01
Propagating fronts are generic structures in a bistable diffusion-driven system and can be used to realize neural algorithms, as e.g., the Kohonen or the neural-gas algorithm. We present an analog-digital hybrid system based on a thyristor-like structure with several gate terminals. This structure represents the continuous part in which a propagating front, separating a region of high current density from a region of low current density, is used to control the learning process of the neural algorithm. With a system containing five neurons and five gates in a quasi one-dimensional arrangement it is demonstrated that an efficient parallel operating learning process can be realized by using the winner-take-all principle and the front propagation, i.e. exploiting the intrinsic dynamics of the semiconductor device. Finally, numerical and analytical investigations of the dependency of the front velocity and its width on the load current have been performed since these are essential parameters for improving the netw...
Realization of a neural algorithm by means of front-propagation in a thyristor-based hybrid system
International Nuclear Information System (INIS)
Niedernostheide, F.-J.; Schulze, H.-J.; Freyd, O.; Bode, M.; Gorbatyuk, A.V.
2003-01-01
Propagating fronts are generic structures in a bistable diffusion-driven system and can be used to realize neural algorithms, as e.g., the Kohonen or the neural-gas algorithm. We present an analog-digital hybrid system based on a thyristor-like structure with several gate terminals. This structure represents the continuous part in which a propagating front, separating a region of high current density from a region of low current density, is used to control the learning process of the neural algorithm. With a system containing five neurons and five gates in a quasi one-dimensional arrangement it is demonstrated that an efficient parallel operating learning process can be realized by using the winner-take-all principle and the front propagation, i.e. exploiting the intrinsic dynamics of the semiconductor device. Finally, numerical and analytical investigations of the dependency of the front velocity and its width on the load current have been performed since these are essential parameters for improving the network performance
Research and Realization of the HJ-1C Real-time Software Frame Synchronization Algorithm
Hou Yang-shuan; Shi Tao; Hu Yu-xin
2014-01-01
Conventional software frame synchronization methods are inefficient in processing huge continuous data without synchronization words. To improve the processing speed, a real-time synchronization algorithm is proposed based on reverse searching. Satellite data are grouped and searched in the reverse direction to avoid searching for synchronization words in huge continuous invalid data; thus, the frame synchronization speed is improved enormously. The fastest processing speed is up to 15445.9 M...
Research and Realization of the HJ-1C Real-time Software Frame Synchronization Algorithm
Directory of Open Access Journals (Sweden)
Hou Yang-shuan
2014-06-01
Full Text Available Conventional software frame synchronization methods are inefficient in processing huge continuous data without synchronization words. To improve the processing speed, a real-time synchronization algorithm is proposed based on reverse searching. Satellite data are grouped and searched in the reverse direction to avoid searching for synchronization words in huge continuous invalid data; thus, the frame synchronization speed is improved enormously. The fastest processing speed is up to 15445.9 Mbps when HJ-1C data are tested. This method is presently applied to the HJ-1C quick-look system in remote sensing satellite ground stations.
International Nuclear Information System (INIS)
Mesgarani, H; Parmour, P; Aghazadeh, N
2010-01-01
In this paper, we apply Aitken extrapolation and epsilon algorithm as acceleration technique for the solution of a weakly singular nonlinear Volterra integral equation of the second kind. In this paper, based on Tao and Yong (2006 J. Math. Anal. Appl. 324 225-37.) the integral equation is solved by Navot's quadrature formula. Also, Tao and Yong (2006) for the first time applied Richardson extrapolation to accelerating convergence for the weakly singular nonlinear Volterra integral equations of the second kind. To our knowledge, this paper may be the first attempt to apply Aitken extrapolation and epsilon algorithm for the weakly singular nonlinear Volterra integral equations of the second kind.
The Reach-and-Evolve Algorithm for Reachability Analysis of Nonlinear Dynamical Systems
P.J. Collins (Pieter); A. Goldsztejn
2008-01-01
htmlabstractThis paper introduces a new algorithm dedicated to the rigorous reachability analysis of nonlinear dynamical systems. The algorithm is initially presented in the context of discrete time dynamical systems, and then extended to continuous time dynamical systems driven by ODEs. In
Comparative efficiencies of three parallel algorithms for nonlinear ...
Indian Academy of Sciences (India)
R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22
This algorithm is better suited for large size problems on coarse ... and reliable time integration algorithms for solving the second-order dynamic equilibrium equations that arise due ... Programming models required to take advantage of the parallel and distributed ..... In addition, MPI added the concept of a 'virtual topology'.
Parallel processors and nonlinear structural dynamics algorithms and software
Belytschko, Ted
1989-01-01
A nonlinear structural dynamics finite element program was developed to run on a shared memory multiprocessor with pipeline processors. The program, WHAMS, was used as a framework for this work. The program employs explicit time integration and has the capability to handle both the nonlinear material behavior and large displacement response of 3-D structures. The elasto-plastic material model uses an isotropic strain hardening law which is input as a piecewise linear function. Geometric nonlinearities are handled by a corotational formulation in which a coordinate system is embedded at the integration point of each element. Currently, the program has an element library consisting of a beam element based on Euler-Bernoulli theory and trianglar and quadrilateral plate element based on Mindlin theory.
NONLINEAR FILTER METHOD OF GPS DYNAMIC POSITIONING BASED ON BANCROFT ALGORITHM
Institute of Scientific and Technical Information of China (English)
ZHANGQin; TAOBen-zao; ZHAOChao-ying; WANGLi
2005-01-01
Because of the ignored items after linearization, the extended Kalman filter (EKF) becomes a form of suboptimal gradient descent algorithm. The emanative tendency exists in GPS solution when the filter equations are ill-posed. The deviation in the estimation cannot be avoided. Furthermore, the true solution may be lost in pseudorange positioning because the linearized pseudorange equations are partial solutions. To solve the above problems in GPS dynamic positioning by using EKF, a closed-form Kalman filter method called the two-stage algorithm is presented for the nonlinear algebraic solution of GPS dynamic positioning based on the global nonlinear least squares closed algorithm--Bancroft numerical algorithm of American. The method separates the spatial parts from temporal parts during processing the GPS filter problems, and solves the nonlinear GPS dynamic positioning, thus getting stable and reliable dynamic positioning solutions.
Indian Academy of Sciences (India)
to as 'divide-and-conquer'. Although there has been a large effort in realizing efficient algorithms, there are not many universally accepted algorithm design paradigms. In this article, we illustrate algorithm design techniques such as balancing, greedy strategy, dynamic programming strategy, and backtracking or traversal of ...
PRESS-based EFOR algorithm for the dynamic parametrical modeling of nonlinear MDOF systems
Liu, Haopeng; Zhu, Yunpeng; Luo, Zhong; Han, Qingkai
2017-09-01
In response to the identification problem concerning multi-degree of freedom (MDOF) nonlinear systems, this study presents the extended forward orthogonal regression (EFOR) based on predicted residual sums of squares (PRESS) to construct a nonlinear dynamic parametrical model. The proposed parametrical model is based on the non-linear autoregressive with exogenous inputs (NARX) model and aims to explicitly reveal the physical design parameters of the system. The PRESS-based EFOR algorithm is proposed to identify such a model for MDOF systems. By using the algorithm, we built a common-structured model based on the fundamental concept of evaluating its generalization capability through cross-validation. The resulting model aims to prevent over-fitting with poor generalization performance caused by the average error reduction ratio (AERR)-based EFOR algorithm. Then, a functional relationship is established between the coefficients of the terms and the design parameters of the unified model. Moreover, a 5-DOF nonlinear system is taken as a case to illustrate the modeling of the proposed algorithm. Finally, a dynamic parametrical model of a cantilever beam is constructed from experimental data. Results indicate that the dynamic parametrical model of nonlinear systems, which depends on the PRESS-based EFOR, can accurately predict the output response, thus providing a theoretical basis for the optimal design of modeling methods for MDOF nonlinear systems.
A quasi-Newton algorithm for large-scale nonlinear equations
Directory of Open Access Journals (Sweden)
Linghua Huang
2017-02-01
Full Text Available Abstract In this paper, the algorithm for large-scale nonlinear equations is designed by the following steps: (i a conjugate gradient (CG algorithm is designed as a sub-algorithm to obtain the initial points of the main algorithm, where the sub-algorithm’s initial point does not have any restrictions; (ii a quasi-Newton algorithm with the initial points given by sub-algorithm is defined as main algorithm, where a new nonmonotone line search technique is presented to get the step length α k $\\alpha_{k}$ . The given nonmonotone line search technique can avoid computing the Jacobian matrix. The global convergence and the 1 + q $1+q$ -order convergent rate of the main algorithm are established under suitable conditions. Numerical results show that the proposed method is competitive with a similar method for large-scale problems.
Controller Parameter Optimization for Nonlinear Systems Using Enhanced Bacteria Foraging Algorithm
Directory of Open Access Journals (Sweden)
V. Rajinikanth
2012-01-01
Full Text Available An enhanced bacteria foraging optimization (EBFO algorithm-based Proportional + integral + derivative (PID controller tuning is proposed for a class of nonlinear process models. The EBFO algorithm is a modified form of standard BFO algorithm. A multiobjective performance index is considered to guide the EBFO algorithm for discovering the best possible value of controller parameters. The efficiency of the proposed scheme has been validated through a comparative study with classical BFO, adaptive BFO, PSO, and GA based controller tuning methods proposed in the literature. The proposed algorithm is tested in real time on a nonlinear spherical tank system. The real-time results show that, EBFO tuned PID controller gives a smooth response for setpoint tracking performance.
Directory of Open Access Journals (Sweden)
Sergii Voloshynov
2016-12-01
Full Text Available The article examines the development of visual learning theory, states functions of accuracy and peculiarities of visual technique realization in modern studying process, it defines the concept of “Visual learning environment” and didactic role of interactive and multimedia visualization processes. Author examines the problem of determination of cognitive visualization potential in algorithmic training of students through information and communication technologies of educational environment. This article specifies functions of visual aids use and implementation features of the specified principle in modern educational process and proves the didactic role of interactive multimedia visualization process that stimulates cognitive activity of student and activates perceptive mechanism of teaching information. It analyzes problem of cognitive visualization potential capacity signification while training future marine personnel using informational communicative educational environment.
Nonlinear Algorithms for Channel Equalization and Map Symbol Detection.
Giridhar, K.
The transfer of information through a communication medium invariably results in various kinds of distortion to the transmitted signal. In this dissertation, a feed -forward neural network-based equalizer, and a family of maximum a posteriori (MAP) symbol detectors are proposed for signal recovery in the presence of intersymbol interference (ISI) and additive white Gaussian noise. The proposed neural network-based equalizer employs a novel bit-mapping strategy to handle multilevel data signals in an equivalent bipolar representation. It uses a training procedure to learn the channel characteristics, and at the end of training, the multilevel symbols are recovered from the corresponding inverse bit-mapping. When the channel characteristics are unknown and no training sequences are available, blind estimation of the channel (or its inverse) and simultaneous data recovery is required. Convergence properties of several existing Bussgang-type blind equalization algorithms are studied through computer simulations, and a unique gain independent approach is used to obtain a fair comparison of their rates of convergence. Although simple to implement, the slow convergence of these Bussgang-type blind equalizers make them unsuitable for many high data-rate applications. Rapidly converging blind algorithms based on the principle of MAP symbol-by -symbol detection are proposed, which adaptively estimate the channel impulse response (CIR) and simultaneously decode the received data sequence. Assuming a linear and Gaussian measurement model, the near-optimal blind MAP symbol detector (MAPSD) consists of a parallel bank of conditional Kalman channel estimators, where the conditioning is done on each possible data subsequence that can convolve with the CIR. This algorithm is also extended to the recovery of convolutionally encoded waveforms in the presence of ISI. Since the complexity of the MAPSD algorithm increases exponentially with the length of the assumed CIR, a suboptimal
Directory of Open Access Journals (Sweden)
S. I. Samsudin
2014-01-01
Full Text Available The wastewater treatment plant (WWTP is highly known with the nonlinearity of the control parameters, thus it is difficult to be controlled. In this paper, the enhancement of nonlinear PI controller (ENon-PI to compensate the nonlinearity of the activated sludge WWTP is proposed. The ENon-PI controller is designed by cascading a sector-bounded nonlinear gain to linear PI controller. The rate variation of the nonlinear gain kn is automatically updated based on adaptive interaction algorithm. Initiative to simplify the ENon-PI control structure by adapting kn has been proved by significant improvement under various dynamic influents. More than 30% of integral square error and 14% of integral absolute error are reduced compared to benchmark PI for DO control and nitrate in nitrogen removal control. Better average effluent qualities, less number of effluent violations, and lower aeration energy consumption resulted.
Directory of Open Access Journals (Sweden)
Hui Huang
2017-01-01
Full Text Available According to the pros and cons of contourlet transform and multimodality medical imaging, here we propose a novel image fusion algorithm that combines nonlinear approximation of contourlet transform with image regional features. The most important coefficient bands of the contourlet sparse matrix are retained by nonlinear approximation. Low-frequency and high-frequency regional features are also elaborated to fuse medical images. The results strongly suggested that the proposed algorithm could improve the visual effects of medical image fusion and image quality, image denoising, and enhancement.
Algorithms of estimation for nonlinear systems a differential and algebraic viewpoint
Martínez-Guerra, Rafael
2017-01-01
This book acquaints readers with recent developments in dynamical systems theory and its applications, with a strong focus on the control and estimation of nonlinear systems. Several algorithms are proposed and worked out for a set of model systems, in particular so-called input-affine or bilinear systems, which can serve to approximate a wide class of nonlinear control systems. These can either take the form of state space models or be represented by an input-output equation. The approach taken here further highlights the role of modern mathematical and conceptual tools, including differential algebraic theory, observer design for nonlinear systems and generalized canonical forms.
Generalized Nonlinear Chirp Scaling Algorithm for High-Resolution Highly Squint SAR Imaging.
Yi, Tianzhu; He, Zhihua; He, Feng; Dong, Zhen; Wu, Manqing
2017-11-07
This paper presents a modified approach for high-resolution, highly squint synthetic aperture radar (SAR) data processing. Several nonlinear chirp scaling (NLCS) algorithms have been proposed to solve the azimuth variance of the frequency modulation rates that are caused by the linear range walk correction (LRWC). However, the azimuth depth of focusing (ADOF) is not handled well by these algorithms. The generalized nonlinear chirp scaling (GNLCS) algorithm that is proposed in this paper uses the method of series reverse (MSR) to improve the ADOF and focusing precision. It also introduces a high order processing kernel to avoid the range block processing. Simulation results show that the GNLCS algorithm can enlarge the ADOF and focusing precision for high-resolution highly squint SAR data.
Generalized Nonlinear Chirp Scaling Algorithm for High-Resolution Highly Squint SAR Imaging
Directory of Open Access Journals (Sweden)
Tianzhu Yi
2017-11-01
Full Text Available This paper presents a modified approach for high-resolution, highly squint synthetic aperture radar (SAR data processing. Several nonlinear chirp scaling (NLCS algorithms have been proposed to solve the azimuth variance of the frequency modulation rates that are caused by the linear range walk correction (LRWC. However, the azimuth depth of focusing (ADOF is not handled well by these algorithms. The generalized nonlinear chirp scaling (GNLCS algorithm that is proposed in this paper uses the method of series reverse (MSR to improve the ADOF and focusing precision. It also introduces a high order processing kernel to avoid the range block processing. Simulation results show that the GNLCS algorithm can enlarge the ADOF and focusing precision for high-resolution highly squint SAR data.
MOHAMMED, M. A. SI; BOUSSADIA, H.; BELLAR, A.; ADNANE, A.
2017-01-01
This paper presents a brief synthesis and useful performance analysis of different attitude filtering algorithms (attitude determination algorithms, attitude estimation algorithms, and nonlinear observers) applied to Low Earth Orbit Satellite in terms of accuracy, convergence time, amount of memory, and computation time. This latter is calculated in two ways, using a personal computer and also using On-board computer 750 (OBC 750) that is being used in many SSTL Earth observation missions. The use of this comparative study could be an aided design tool to the designer to choose from an attitude determination or attitude estimation or attitude observer algorithms. The simulation results clearly indicate that the nonlinear Observer is the more logical choice.
Institute of Scientific and Technical Information of China (English)
WANG; Shunjin; ZHANG; Hua
2006-01-01
The problem of preserving fidelity in numerical computation of nonlinear ordinary differential equations is studied in terms of preserving local differential structure and approximating global integration structure of the dynamical system.The ordinary differential equations are lifted to the corresponding partial differential equations in the framework of algebraic dynamics,and a new algorithm-algebraic dynamics algorithm is proposed based on the exact analytical solutions of the ordinary differential equations by the algebraic dynamics method.In the new algorithm,the time evolution of the ordinary differential system is described locally by the time translation operator and globally by the time evolution operator.The exact analytical piece-like solution of the ordinary differential equations is expressd in terms of Taylor series with a local convergent radius,and its finite order truncation leads to the new numerical algorithm with a controllable precision better than Runge Kutta Algorithm and Symplectic Geometric Algorithm.
Madyastha, Raghavendra K.; Aazhang, Behnaam; Henson, Troy F.; Huxhold, Wendy L.
1992-01-01
This paper addresses the issue of applying a globally convergent optimization algorithm to the training of multilayer perceptrons, a class of Artificial Neural Networks. The multilayer perceptrons are trained towards the solution of two highly nonlinear problems: (1) signal detection in a multi-user communication network, and (2) solving the inverse kinematics for a robotic manipulator. The research is motivated by the fact that a multilayer perceptron is theoretically capable of approximating any nonlinear function to within a specified accuracy. The algorithm that has been employed in this study combines the merits of two well known optimization algorithms, the Conjugate Gradients and the Trust Regions Algorithms. The performance is compared to a widely used algorithm, the Backpropagation Algorithm, that is basically a gradient-based algorithm, and hence, slow in converging. The performances of the two algorithms are compared with the convergence rate. Furthermore, in the case of the signal detection problem, performances are also benchmarked by the decision boundaries drawn as well as the probability of error obtained in either case.
Directory of Open Access Journals (Sweden)
Agarwal RaviP
2009-01-01
Full Text Available We glance at recent advances to the general theory of maximal (set-valued monotone mappings and their role demonstrated to examine the convex programming and closely related field of nonlinear variational inequalities. We focus mostly on applications of the super-relaxed ( -proximal point algorithm to the context of solving a class of nonlinear variational inclusion problems, based on the notion of maximal ( -monotonicity. Investigations highlighted in this communication are greatly influenced by the celebrated work of Rockafellar (1976, while others have played a significant part as well in generalizing the proximal point algorithm considered by Rockafellar (1976 to the case of the relaxed proximal point algorithm by Eckstein and Bertsekas (1992. Even for the linear convergence analysis for the overrelaxed (or super-relaxed ( -proximal point algorithm, the fundamental model for Rockafellar's case does the job. Furthermore, we attempt to explore possibilities of generalizing the Yosida regularization/approximation in light of maximal ( -monotonicity, and then applying to first-order evolution equations/inclusions.
Flaw characterization through nonlinear ultrasonics and wavelet cross-correlation algorithms
Bunget, Gheorghe; Yee, Andrew; Stewart, Dylan; Rogers, James; Henley, Stanley; Bugg, Chris; Cline, John; Webster, Matthew; Farinholt, Kevin; Friedersdorf, Fritz
2018-04-01
Ultrasonic measurements have become increasingly important non-destructive techniques to characterize flaws found within various in-service industrial components. The prediction of remaining useful life based on fracture analysis depends on the accurate estimation of flaw size and orientation. However, amplitude-based ultrasonic measurements are not able to estimate the plastic zones that exist ahead of crack tips. Estimating the size of the plastic zone is an advantage since some flaws may propagate faster than others. This paper presents a wavelet cross-correlation (WCC) algorithm that was applied to nonlinear analysis of ultrasonically guided waves (GW). By using this algorithm, harmonics present in the waveforms were extracted and nonlinearity parameters were used to indicate both the tip of the cracks and size of the plastic zone. B-scans performed with the quadratic nonlinearities were sensitive to micro-damage specific to plastic zones.
International Nuclear Information System (INIS)
Haug, E.; Rouvray, A.L. de; Nguyen, Q.S.
1977-01-01
This study proposes a general nonlinear algorithm stability criterion; it introduces a nonlinear algorithm, easily implemented in existing incremental/iterative codes, and it applies the new scheme beneficially to problems of linear elastic dynamic snap buckling. Based on the concept of energy conservation, the paper outlines an algorithm which degenerates into the trapezoidal rule, if applied to linear systems. The new algorithm conserves energy in systems having elastic potentials up to the fourth order in the displacements. This is true in the important case of nonlinear total Lagrange formulations where linear elastic material properties are substituted. The scheme is easily implemented in existing incremental-iterative codes with provisions for stiffness reformation and containing the basic Newmark scheme. Numerical analyses of dynamic stability can be dramatically sensitive to amplitude errors, because damping algorithms may mask, and overestimating schemes may numerically trigger, the physical instability. The newly proposed scheme has been applied with larger time steps and less cost to the dynamic snap buckling of simple one and multi degree-of-freedom structures for various initial conditions
Fsheikh, Ahmed H.
2013-01-01
A nonlinear orthogonal matching pursuit (NOMP) for sparse calibration of reservoir models is presented. Sparse calibration is a challenging problem as the unknowns are both the non-zero components of the solution and their associated weights. NOMP is a greedy algorithm that discovers at each iteration the most correlated components of the basis functions with the residual. The discovered basis (aka support) is augmented across the nonlinear iterations. Once the basis functions are selected from the dictionary, the solution is obtained by applying Tikhonov regularization. The proposed algorithm relies on approximate gradient estimation using an iterative stochastic ensemble method (ISEM). ISEM utilizes an ensemble of directional derivatives to efficiently approximate gradients. In the current study, the search space is parameterized using an overcomplete dictionary of basis functions built using the K-SVD algorithm.
A chaos-based evolutionary algorithm for general nonlinear programming problems
International Nuclear Information System (INIS)
El-Shorbagy, M.A.; Mousa, A.A.; Nasr, S.M.
2016-01-01
In this paper we present a chaos-based evolutionary algorithm (EA) for solving nonlinear programming problems named chaotic genetic algorithm (CGA). CGA integrates genetic algorithm (GA) and chaotic local search (CLS) strategy to accelerate the optimum seeking operation and to speed the convergence to the global solution. The integration of global search represented in genetic algorithm and CLS procedures should offer the advantages of both optimization methods while offsetting their disadvantages. By this way, it is intended to enhance the global convergence and to prevent to stick on a local solution. The inherent characteristics of chaos can enhance optimization algorithms by enabling it to escape from local solutions and increase the convergence to reach to the global solution. Twelve chaotic maps have been analyzed in the proposed approach. The simulation results using the set of CEC’2005 show that the application of chaotic mapping may be an effective strategy to improve the performances of EAs.
Kazemi, Mahdi; Arefi, Mohammad Mehdi
2017-03-01
In this paper, an online identification algorithm is presented for nonlinear systems in the presence of output colored noise. The proposed method is based on extended recursive least squares (ERLS) algorithm, where the identified system is in polynomial Wiener form. To this end, an unknown intermediate signal is estimated by using an inner iterative algorithm. The iterative recursive algorithm adaptively modifies the vector of parameters of the presented Wiener model when the system parameters vary. In addition, to increase the robustness of the proposed method against variations, a robust RLS algorithm is applied to the model. Simulation results are provided to show the effectiveness of the proposed approach. Results confirm that the proposed method has fast convergence rate with robust characteristics, which increases the efficiency of the proposed model and identification approach. For instance, the FIT criterion will be achieved 92% in CSTR process where about 400 data is used. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Ronghui Zhang
2017-05-01
Full Text Available Focusing on safety, comfort and with an overall aim of the comprehensive improvement of a vision-based intelligent vehicle, a novel Advanced Emergency Braking System (AEBS is proposed based on Nonlinear Model Predictive Algorithm. Considering the nonlinearities of vehicle dynamics, a vision-based longitudinal vehicle dynamics model is established. On account of the nonlinear coupling characteristics of the driver, surroundings, and vehicle itself, a hierarchical control structure is proposed to decouple and coordinate the system. To avoid or reduce the collision risk between the intelligent vehicle and collision objects, a coordinated cost function of tracking safety, comfort, and fuel economy is formulated. Based on the terminal constraints of stable tracking, a multi-objective optimization controller is proposed using the theory of non-linear model predictive control. To quickly and precisely track control target in a finite time, an electronic brake controller for AEBS is designed based on the Nonsingular Fast Terminal Sliding Mode (NFTSM control theory. To validate the performance and advantages of the proposed algorithm, simulations are implemented. According to the simulation results, the proposed algorithm has better integrated performance in reducing the collision risk and improving the driving comfort and fuel economy of the smart car compared with the existing single AEBS.
An efficient algorithm for some highly nonlinear fractional PDEs in mathematical physics.
Directory of Open Access Journals (Sweden)
Jamshad Ahmad
Full Text Available In this paper, a fractional complex transform (FCT is used to convert the given fractional partial differential equations (FPDEs into corresponding partial differential equations (PDEs and subsequently Reduced Differential Transform Method (RDTM is applied on the transformed system of linear and nonlinear time-fractional PDEs. The results so obtained are re-stated by making use of inverse transformation which yields it in terms of original variables. It is observed that the proposed algorithm is highly efficient and appropriate for fractional PDEs and hence can be extended to other complex problems of diversified nonlinear nature.
A frequency bin-wise nonlinear masking algorithm in convolutive mixtures for speech segregation.
Chi, Tai-Shih; Huang, Ching-Wen; Chou, Wen-Sheng
2012-05-01
A frequency bin-wise nonlinear masking algorithm is proposed in the spectrogram domain for speech segregation in convolutive mixtures. The contributive weight from each speech source to a time-frequency unit of the mixture spectrogram is estimated by a nonlinear function based on location cues. For each sound source, a non-binary mask is formed from the estimated weights and is multiplied to the mixture spectrogram to extract the sound. Head-related transfer functions (HRTFs) are used to simulate convolutive sound mixtures perceived by listeners. Simulation results show our proposed method outperforms convolutive independent component analysis and degenerate unmixing and estimation technique methods in almost all test conditions.
A nonlinear filtering algorithm for denoising HR(S)TEM micrographs
International Nuclear Information System (INIS)
Du, Hongchu
2015-01-01
Noise reduction of micrographs is often an essential task in high resolution (scanning) transmission electron microscopy (HR(S)TEM) either for a higher visual quality or for a more accurate quantification. Since HR(S)TEM studies are often aimed at resolving periodic atomistic columns and their non-periodic deviation at defects, it is important to develop a noise reduction algorithm that can simultaneously handle both periodic and non-periodic features properly. In this work, a nonlinear filtering algorithm is developed based on widely used techniques of low-pass filter and Wiener filter, which can efficiently reduce noise without noticeable artifacts even in HR(S)TEM micrographs with contrast of variation of background and defects. The developed nonlinear filtering algorithm is particularly suitable for quantitative electron microscopy, and is also of great interest for beam sensitive samples, in situ analyses, and atomic resolution EFTEM. - Highlights: • A nonlinear filtering algorithm for denoising HR(S)TEM images is developed. • It can simultaneously handle both periodic and non-periodic features properly. • It is particularly suitable for quantitative electron microscopy. • It is of great interest for beam sensitive samples, in situ analyses, and atomic resolution EFTEM
Killing scalar of non-linear σ-model on G/H realizing the classical exchange algebra
International Nuclear Information System (INIS)
Aoyama, Shogo
2014-01-01
The Poisson brackets for non-linear σ-models on G/H are set up on the light-like plane. A quantity which transforms irreducibly by the Killing vectors, called Killing scalar, is constructed in an arbitrary representation of G. It is shown to satisfy the classical exchange algebra
Directory of Open Access Journals (Sweden)
Koh Kim Jie
2017-01-01
Full Text Available Quadratic damping nonlinearity is challenging for displacement based structural dynamics problem as the problem is nonlinear in time derivative of the primitive variable. For such nonlinearity, the formulation of tangent stiffness matrix is not lucid in the literature. Consequently, ambiguity related to kinematics update arises when implementing the time integration-iterative algorithm. In present work, an Euler-Bernoulli beam vibration problem with quadratic damping nonlinearity is addressed as the main source of quadratic damping nonlinearity arises from drag force estimation, which is generally valid only for slender structures. Employing Newton-Raphson formulation, tangent stiffness components associated with quadratic damping nonlinearity requires velocity input for evaluation purpose. For this reason, two mathematically equivalent algorithm structures with different kinematics arrangement are tested. Both algorithm structures result in the same accuracy and convergence characteristic of solution.
Embedded algorithms within an FPGA-based system to process nonlinear time series data
Jones, Jonathan D.; Pei, Jin-Song; Tull, Monte P.
2008-03-01
This paper presents some preliminary results of an ongoing project. A pattern classification algorithm is being developed and embedded into a Field-Programmable Gate Array (FPGA) and microprocessor-based data processing core in this project. The goal is to enable and optimize the functionality of onboard data processing of nonlinear, nonstationary data for smart wireless sensing in structural health monitoring. Compared with traditional microprocessor-based systems, fast growing FPGA technology offers a more powerful, efficient, and flexible hardware platform including on-site (field-programmable) reconfiguration capability of hardware. An existing nonlinear identification algorithm is used as the baseline in this study. The implementation within a hardware-based system is presented in this paper, detailing the design requirements, validation, tradeoffs, optimization, and challenges in embedding this algorithm. An off-the-shelf high-level abstraction tool along with the Matlab/Simulink environment is utilized to program the FPGA, rather than coding the hardware description language (HDL) manually. The implementation is validated by comparing the simulation results with those from Matlab. In particular, the Hilbert Transform is embedded into the FPGA hardware and applied to the baseline algorithm as the centerpiece in processing nonlinear time histories and extracting instantaneous features of nonstationary dynamic data. The selection of proper numerical methods for the hardware execution of the selected identification algorithm and consideration of the fixed-point representation are elaborated. Other challenges include the issues of the timing in the hardware execution cycle of the design, resource consumption, approximation accuracy, and user flexibility of input data types limited by the simplicity of this preliminary design. Future work includes making an FPGA and microprocessor operate together to embed a further developed algorithm that yields better
A Numerical Algorithm for Solving a Four-Point Nonlinear Fractional Integro-Differential Equations
Directory of Open Access Journals (Sweden)
Er Gao
2012-01-01
Full Text Available We provide a new algorithm for a four-point nonlocal boundary value problem of nonlinear integro-differential equations of fractional order q∈(1,2] based on reproducing kernel space method. According to our work, the analytical solution of the equations is represented in the reproducing kernel space which we construct and so the n-term approximation. At the same time, the n-term approximation is proved to converge to the analytical solution. An illustrative example is also presented, which shows that the new algorithm is efficient and accurate.
Directory of Open Access Journals (Sweden)
H. Vazquez-Leal
2014-01-01
Full Text Available We present a homotopy continuation method (HCM for finding multiple operating points of nonlinear circuits composed of devices modelled by using piecewise linear (PWL representations. We propose an adaptation of the modified spheres path tracking algorithm to trace the homotopy trajectories of PWL circuits. In order to assess the benefits of this proposal, four nonlinear circuits composed of piecewise linear modelled devices are analysed to determine their multiple operating points. The results show that HCM can find multiple solutions within a single homotopy trajectory. Furthermore, we take advantage of the fact that homotopy trajectories are PWL curves meant to replace the multidimensional interpolation and fine tuning stages of the path tracking algorithm with a simple and highly accurate procedure based on the parametric straight line equation.
Energy Technology Data Exchange (ETDEWEB)
Carey, G.F.; Young, D.M.
1993-12-31
The program outlined here is directed to research on methods, algorithms, and software for distributed parallel supercomputers. Of particular interest are finite element methods and finite difference methods together with sparse iterative solution schemes for scientific and engineering computations of very large-scale systems. Both linear and nonlinear problems will be investigated. In the nonlinear case, applications with bifurcation to multiple solutions will be considered using continuation strategies. The parallelizable numerical methods of particular interest are a family of partitioning schemes embracing domain decomposition, element-by-element strategies, and multi-level techniques. The methods will be further developed incorporating parallel iterative solution algorithms with associated preconditioners in parallel computer software. The schemes will be implemented on distributed memory parallel architectures such as the CRAY MPP, Intel Paragon, the NCUBE3, and the Connection Machine. We will also consider other new architectures such as the Kendall-Square (KSQ) and proposed machines such as the TERA. The applications will focus on large-scale three-dimensional nonlinear flow and reservoir problems with strong convective transport contributions. These are legitimate grand challenge class computational fluid dynamics (CFD) problems of significant practical interest to DOE. The methods developed and algorithms will, however, be of wider interest.
An integer optimization algorithm for robust identification of non-linear gene regulatory networks
Directory of Open Access Journals (Sweden)
Chemmangattuvalappil Nishanth
2012-09-01
Full Text Available Abstract Background Reverse engineering gene networks and identifying regulatory interactions are integral to understanding cellular decision making processes. Advancement in high throughput experimental techniques has initiated innovative data driven analysis of gene regulatory networks. However, inherent noise associated with biological systems requires numerous experimental replicates for reliable conclusions. Furthermore, evidence of robust algorithms directly exploiting basic biological traits are few. Such algorithms are expected to be efficient in their performance and robust in their prediction. Results We have developed a network identification algorithm to accurately infer both the topology and strength of regulatory interactions from time series gene expression data in the presence of significant experimental noise and non-linear behavior. In this novel formulism, we have addressed data variability in biological systems by integrating network identification with the bootstrap resampling technique, hence predicting robust interactions from limited experimental replicates subjected to noise. Furthermore, we have incorporated non-linearity in gene dynamics using the S-system formulation. The basic network identification formulation exploits the trait of sparsity of biological interactions. Towards that, the identification algorithm is formulated as an integer-programming problem by introducing binary variables for each network component. The objective function is targeted to minimize the network connections subjected to the constraint of maximal agreement between the experimental and predicted gene dynamics. The developed algorithm is validated using both in silico and experimental data-sets. These studies show that the algorithm can accurately predict the topology and connection strength of the in silico networks, as quantified by high precision and recall, and small discrepancy between the actual and predicted kinetic parameters
Xu, Shaoping; Zeng, Xiaoxia; Jiang, Yinnan; Tang, Yiling
2018-01-01
We proposed a noniterative principal component analysis (PCA)-based noise level estimation (NLE) algorithm that addresses the problem of estimating the noise level with a two-step scheme. First, we randomly extracted a number of raw patches from a given noisy image and took the smallest eigenvalue of the covariance matrix of the raw patches as the preliminary estimation of the noise level. Next, the final estimation was directly obtained with a nonlinear mapping (rectification) function that was trained on some representative noisy images corrupted with different known noise levels. Compared with the state-of-art NLE algorithms, the experiment results show that the proposed NLE algorithm can reliably infer the noise level and has robust performance over a wide range of image contents and noise levels, showing a good compromise between speed and accuracy in general.
Bouchard, M
2001-01-01
In recent years, a few articles describing the use of neural networks for nonlinear active control of sound and vibration were published. Using a control structure with two multilayer feedforward neural networks (one as a nonlinear controller and one as a nonlinear plant model), steepest descent algorithms based on two distinct gradient approaches were introduced for the training of the controller network. The two gradient approaches were sometimes called the filtered-x approach and the adjoint approach. Some recursive-least-squares algorithms were also introduced, using the adjoint approach. In this paper, an heuristic procedure is introduced for the development of recursive-least-squares algorithms based on the filtered-x and the adjoint gradient approaches. This leads to the development of new recursive-least-squares algorithms for the training of the controller neural network in the two networks structure. These new algorithms produce a better convergence performance than previously published algorithms. Differences in the performance of algorithms using the filtered-x and the adjoint gradient approaches are discussed in the paper. The computational load of the algorithms discussed in the paper is evaluated for multichannel systems of nonlinear active control. Simulation results are presented to compare the convergence performance of the algorithms, showing the convergence gain provided by the new algorithms.
National Aeronautics and Space Administration — SSCI proposes to develop and test a framework referred to as the ADVANCE (Algorithm Design and Validation for Adaptive Nonlinear Control Enhancement), within which...
International Nuclear Information System (INIS)
Piltan, Mehdi; Shiri, Hiva; Ghaderi, S.F.
2012-01-01
Highlights: ► Investigating different fitness functions for evolutionary algorithms in energy forecasting. ► Energy forecasting of Iranian metal industry by value added, energy prices, investment and employees. ► Using real-coded instead of binary-coded genetic algorithm decreases energy forecasting error. - Abstract: Developing energy-forecasting models is known as one of the most important steps in long-term planning. In order to achieve sustainable energy supply toward economic development and social welfare, it is required to apply precise forecasting model. Applying artificial intelligent models for estimation complex economic and social functions is growing up considerably in many researches recently. In this paper, energy consumption in industrial sector as one of the critical sectors in the consumption of energy has been investigated. Two linear and three nonlinear functions have been used in order to forecast and analyze energy in the Iranian metal industry, Particle Swarm Optimization (PSO) and Genetic Algorithms (GAs) are applied to attain parameters of the models. The Real-Coded Genetic Algorithm (RCGA) has been developed based on real numbers, which is introduced as a new approach in the field of energy forecasting. In the proposed model, electricity consumption has been considered as a function of different variables such as electricity tariff, manufacturing value added, prevailing fuel prices, the number of employees, the investment in equipment and consumption in the previous years. Mean Square Error (MSE), Root Mean Square Error (RMSE), Mean Absolute Deviation (MAD) and Mean Absolute Percent Error (MAPE) are the four functions which have been used as the fitness function in the evolutionary algorithms. The results show that the logarithmic nonlinear model using PSO algorithm with 1.91 error percentage has the best answer. Furthermore, the prediction of electricity consumption in industrial sector of Turkey and also Turkish industrial sector
A unified framework of descent algorithms for nonlinear programs and variational inequalities
International Nuclear Information System (INIS)
Patriksson, M.
1993-01-01
We present a framework of algorithms for the solution of continuous optimization and variational inequality problems. In the general algorithm, a search direction finding auxiliary problems is obtained by replacing the original cost function with an approximating monotone cost function. The proposed framework encompasses algorithm classes presented earlier by Cohen, Dafermos, Migdalas, and Tseng, and includes numerous descent and successive approximation type methods, such as Newton methods, Jacobi and Gauss-Siedel type decomposition methods for problems defined over Cartesian product sets, and proximal point methods, among others. The auxiliary problem of the general algorithm also induces equivalent optimization reformulation and descent methods for asymmetric variational inequalities. We study the convergence properties of the general algorithm when applied to unconstrained optimization, nondifferentiable optimization, constrained differentiable optimization, and variational inequalities; the emphasis of the convergence analyses is placed on basic convergence results, convergence using different line search strategies and truncated subproblem solutions, and convergence rate results. This analysis offer a unification of known results; moreover, it provides strengthenings of convergence results for many existing algorithms, and indicates possible improvements of their realizations. 482 refs
Memetic Algorithms to Solve a Global Nonlinear Optimization Problem. A Review
Directory of Open Access Journals (Sweden)
M. K. Sakharov
2015-01-01
Full Text Available In recent decades, evolutionary algorithms have proven themselves as the powerful optimization techniques of search engine. Their popularity is due to the fact that they are easy to implement and can be used in all areas, since they are based on the idea of universal evolution. For example, in the problems of a large number of local optima, the traditional optimization methods, usually, fail in finding the global optimum. To solve such problems using a variety of stochastic methods, in particular, the so-called population-based algorithms, which are a kind of evolutionary methods. The main disadvantage of this class of methods is their slow convergence to the exact solution in the neighborhood of the global optimum, as these methods incapable to use the local information about the landscape of the function. This often limits their use in largescale real-world problems where the computation time is a critical factor.One of the promising directions in the field of modern evolutionary computation are memetic algorithms, which can be regarded as a combination of population search of the global optimum and local procedures for verifying solutions, which gives a synergistic effect. In the context of memetic algorithms, the meme is an implementation of the local optimization method to refine solution in the search.The concept of memetic algorithms provides ample opportunities for the development of various modifications of these algorithms, which can vary the frequency of the local search, the conditions of its end, and so on. The practically significant memetic algorithm modifications involve the simultaneous use of different memes. Such algorithms are called multi-memetic.The paper gives statement of the global problem of nonlinear unconstrained optimization, describes the most promising areas of AI modifications, including hybridization and metaoptimization. The main content of the work is the classification and review of existing varieties of
Nonlinear Filtering with IMM Algorithm for Ultra-Tight GPS/INS Integration
Directory of Open Access Journals (Sweden)
Dah-Jing Jwo
2013-05-01
Full Text Available Abstract This paper conducts a performance evaluation for the ultra-tight integration of a Global positioning system (GPS and an inertial navigation system (INS, using nonlinear filtering approaches with an interacting multiple model (IMM algorithm. An ultra-tight GPS/INS architecture involves the integration of in-phase and quadrature components from the correlator of a GPS receiver with INS data. An unscented Kalman filter (UKF, which employs a set of sigma points by deterministic sampling, avoids the error caused by linearization as in an extended Kalman filter (EKF. Based on the filter structural adaptation for describing various dynamic behaviours, the IMM nonlinear filtering provides an alternative for designing the adaptive filter in the ultra-tight GPS/INS integration. The use of IMM enables tuning of an appropriate value for the process of noise covariance so as to maintain good estimation accuracy and tracking capability. Two examples are provided to illustrate the effectiveness of the design and demonstrate the effective improvement in navigation estimation accuracy. A performance comparison among various filtering methods for ultra-tight integration of GPS and INS is also presented. The IMM based nonlinear filtering approach demonstrates the effectiveness of the algorithm for improved positioning performance.
Matveyev, A. Z.; Pasmanik, G. A.
1993-05-01
An associative memory using only optical elements has been realized experimentally. The key element of the arrangement is a stimulated-Brillouin-scattering (SBS) selector consisting of a short SBS medium at the focus of a lens. The qualitative advantage of the selector over an SBS mirror is demonstrated experimentally. The response time of the arrangement is ~ 10-8 s and is determined by the duration of the SBS. Estimates show that the SBS selector is capable in practice of distinguishing a signal against background noise when the initial distortion level of the object beam is 10-3. Reliable operation of the SBS selector has been demonstrated for radiative and energy loads reaching 2 GW/cm2 and 2 J, respectively.
Institute of Scientific and Technical Information of China (English)
2008-01-01
Using functional derivative technique in quantum field theory, the algebraic dy-namics approach for solution of ordinary differential evolution equations was gen-eralized to treat partial differential evolution equations. The partial differential evo-lution equations were lifted to the corresponding functional partial differential equations in functional space by introducing the time translation operator. The functional partial differential evolution equations were solved by algebraic dynam-ics. The algebraic dynamics solutions are analytical in Taylor series in terms of both initial functions and time. Based on the exact analytical solutions, a new nu-merical algorithm—algebraic dynamics algorithm was proposed for partial differ-ential evolution equations. The difficulty of and the way out for the algorithm were discussed. The application of the approach to and computer numerical experi-ments on the nonlinear Burgers equation and meteorological advection equation indicate that the algebraic dynamics approach and algebraic dynamics algorithm are effective to the solution of nonlinear partial differential evolution equations both analytically and numerically.
A conservative Fourier pseudospectral algorithm for a coupled nonlinear Schrödinger system
International Nuclear Information System (INIS)
Cai Jia-Xiang; Wang Yu-Shun
2013-01-01
We derive a new method for a coupled nonlinear Schrödinger system by using the square of first-order Fourier spectral differentiation matrix D 1 instead of traditional second-order Fourier spectral differentiation matrix D 2 to approximate the second derivative. We prove the proposed method preserves the charge and energy conservation laws exactly. In numerical tests, we display the accuracy of numerical solution and the role of the nonlinear coupling parameter in cases of soliton collisions. Numerical experiments also exhibit the excellent performance of the method in preserving the charge and energy conservation laws. These numerical results verify that the proposed method is both a charge-preserving and an energy-preserving algorithm
International Nuclear Information System (INIS)
Hinterbichler, Kurt; Joyce, Austin; Khoury, Justin
2012-01-01
The pseudo-conformal scenario is an alternative to inflation in which the early universe is described by an approximate conformal field theory on flat, Minkowski space. Some fields acquire a time-dependent expectation value, which breaks the flat space so(4,2) conformal algebra to its so(4,1) de Sitter subalgebra. As a result, weight-0 fields acquire a scale invariant spectrum of perturbations. The scenario is very general, and its essential features are determined by the symmetry breaking pattern, irrespective of the details of the underlying microphysics. In this paper, we apply the well-known coset technique to derive the most general effective lagrangian describing the Goldstone field and matter fields, consistent with the assumed symmetries. The resulting action captures the low energy dynamics of any pseudo-conformal realization, including the U(1)-invariant quartic model and the Galilean Genesis scenario. We also derive this lagrangian using an alternative method of curvature invariants, consisting of writing down geometric scalars in terms of the conformal mode. Using this general effective action, we compute the two-point function for the Goldstone and a fiducial weight-0 field, as well as some sample three-point functions involving these fields
A Numerical Algorithm for Solving a Four-Point Nonlinear Fractional Integro-Differential Equations
Gao, Er; Song, Songhe; Zhang, Xinjian
2012-01-01
We provide a new algorithm for a four-point nonlocal boundary value problem of nonlinear integro-differential equations of fractional order q∈(1,2] based on reproducing kernel space method. According to our work, the analytical solution of the equations is represented in the reproducing kernel space which we construct and so the n-term approximation. At the same time, the n-term approximation is proved to converge to the analytical solution. An illustrative example is also presented, which sh...
The genetic algorithm for the nonlinear programming of water pollution control system
Energy Technology Data Exchange (ETDEWEB)
Wei, J.; Zhang, J. [China University of Geosciences (China)
1999-08-01
In the programming of water pollution control system the combined method of optimization with simulation is used generally. It is not only laborious in calculation, but also the global optimum of the obtained solution is guaranteed difficult. In this paper, the genetic algorithm (GA) used in the nonlinear programming of water pollution control system is given, by which the preferred conception for the programming of waste water system is found in once-through operation. It is more succinct than the conventional method and the global optimum of the obtained solution could be ensured. 6 refs., 4 figs., 3 tabs.
Numerical nonlinear complex geometrical optics algorithm for the 3D Calderón problem
DEFF Research Database (Denmark)
Delbary, Fabrice; Knudsen, Kim
2014-01-01
to the generalized Laplace equation. The 3D problem was solved in theory in late 1980s using complex geometrical optics solutions and a scattering transform. Several approximations to the reconstruction method have been suggested and implemented numerically in the literature, but here, for the first time, a complete...... computer implementation of the full nonlinear algorithm is given. First a boundary integral equation is solved by a Nystrom method for the traces of the complex geometrical optics solutions, second the scattering transform is computed and inverted using fast Fourier transform, and finally a boundary value...
A Nonmonotone Line Search Filter Algorithm for the System of Nonlinear Equations
Directory of Open Access Journals (Sweden)
Zhong Jin
2012-01-01
Full Text Available We present a new iterative method based on the line search filter method with the nonmonotone strategy to solve the system of nonlinear equations. The equations are divided into two groups; some equations are treated as constraints and the others act as the objective function, and the two groups are just updated at the iterations where it is needed indeed. We employ the nonmonotone idea to the sufficient reduction conditions and filter technique which leads to a flexibility and acceptance behavior comparable to monotone methods. The new algorithm is shown to be globally convergent and numerical experiments demonstrate its effectiveness.
Directory of Open Access Journals (Sweden)
Y. W. Sun
2013-08-01
Full Text Available In this paper, we present an optimized analysis algorithm for non-dispersive infrared (NDIR to in situ monitor stack emissions. The proposed algorithm simultaneously compensates for nonlinear absorption and cross interference among different gases. We present a mathematical derivation for the measurement error caused by variations in interference coefficients when nonlinear absorption occurs. The proposed algorithm is derived from a classical one and uses interference functions to quantify cross interference. The interference functions vary proportionally with the nonlinear absorption. Thus, interference coefficients among different gases can be modeled by the interference functions whether gases are characterized by linear or nonlinear absorption. In this study, the simultaneous analysis of two components (CO2 and CO serves as an example for the validation of the proposed algorithm. The interference functions in this case can be obtained by least-squares fitting with third-order polynomials. Experiments show that the results of cross interference correction are improved significantly by utilizing the fitted interference functions when nonlinear absorptions occur. The dynamic measurement ranges of CO2 and CO are improved by about a factor of 1.8 and 3.5, respectively. A commercial analyzer with high accuracy was used to validate the CO and CO2 measurements derived from the NDIR analyzer prototype in which the new algorithm was embedded. The comparison of the two analyzers show that the prototype works well both within the linear and nonlinear ranges.
Model-independent nonlinear control algorithm with application to a liquid bridge experiment
International Nuclear Information System (INIS)
Petrov, V.; Haaning, A.; Muehlner, K.A.; Van Hook, S.J.; Swinney, H.L.
1998-01-01
We present a control method for high-dimensional nonlinear dynamical systems that can target remote unstable states without a priori knowledge of the underlying dynamical equations. The algorithm constructs a high-dimensional look-up table based on the system's responses to a sequence of random perturbations. The method is demonstrated by stabilizing unstable flow of a liquid bridge surface-tension-driven convection experiment that models the float zone refining process. Control of the dynamics is achieved by heating or cooling two thermoelectric Peltier devices placed in the vicinity of the liquid bridge surface. The algorithm routines along with several example programs written in the MATLAB language can be found at ftp://ftp.mathworks.com/pub/contrib/v5/control/nlcontrol. copyright 1998 The American Physical Society
An algorithm for robust non-linear analysis of radioimmunoassays and other bioassays
International Nuclear Information System (INIS)
Normolle, D.P.
1993-01-01
The four-parameter logistic function is an appropriate model for many types of bioassays that have continuous response variables, such as radioimmunoassays. By modelling the variance of replicates in an assay, one can modify the usual parameter estimation techniques (for example, Gauss-Newton or Marquardt-Levenberg) to produce parameter estimates for the standard curve that are robust against outlying observations. This article describes the computation of robust (M-) estimates for the parameters of the four-parameter logistic function. It describes techniques for modelling the variance structure of the replicates, modifications to the usual iterative algorithms for parameter estimation in non-linear models, and a formula for inverse confidence intervals. To demonstrate the algorithm, the article presents examples where the robustly estimated four-parameter logistic model is compared with the logit-log and four-parameter logistic models with least-squares estimates. (author)
Pal, Partha S; Kar, R; Mandal, D; Ghoshal, S P
2015-11-01
This paper presents an efficient approach to identify different stable and practically useful Hammerstein models as well as unstable nonlinear process along with its stable closed loop counterpart with the help of an evolutionary algorithm as Colliding Bodies Optimization (CBO) optimization algorithm. The performance measures of the CBO based optimization approach such as precision, accuracy are justified with the minimum output mean square value (MSE) which signifies that the amount of bias and variance in the output domain are also the least. It is also observed that the optimization of output MSE in the presence of outliers has resulted in a very close estimation of the output parameters consistently, which also justifies the effective general applicability of the CBO algorithm towards the system identification problem and also establishes the practical usefulness of the applied approach. Optimum values of the MSEs, computational times and statistical information of the MSEs are all found to be the superior as compared with those of the other existing similar types of stochastic algorithms based approaches reported in different recent literature, which establish the robustness and efficiency of the applied CBO based identification scheme. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Multilayer perceptron for robust nonlinear interval regression analysis using genetic algorithms.
Hu, Yi-Chung
2014-01-01
On the basis of fuzzy regression, computational models in intelligence such as neural networks have the capability to be applied to nonlinear interval regression analysis for dealing with uncertain and imprecise data. When training data are not contaminated by outliers, computational models perform well by including almost all given training data in the data interval. Nevertheless, since training data are often corrupted by outliers, robust learning algorithms employed to resist outliers for interval regression analysis have been an interesting area of research. Several approaches involving computational intelligence are effective for resisting outliers, but the required parameters for these approaches are related to whether the collected data contain outliers or not. Since it seems difficult to prespecify the degree of contamination beforehand, this paper uses multilayer perceptron to construct the robust nonlinear interval regression model using the genetic algorithm. Outliers beyond or beneath the data interval will impose slight effect on the determination of data interval. Simulation results demonstrate that the proposed method performs well for contaminated datasets.
Xia, Youshen; Kamel, Mohamed S
2007-06-01
Identification of a general nonlinear noisy system viewed as an estimation of a predictor function is studied in this article. A measurement fusion method for the predictor function estimate is proposed. In the proposed scheme, observed data are first fused by using an optimal fusion technique, and then the optimal fused data are incorporated in a nonlinear function estimator based on a robust least squares support vector machine (LS-SVM). A cooperative learning algorithm is proposed to implement the proposed measurement fusion method. Compared with related identification methods, the proposed method can minimize both the approximation error and the noise error. The performance analysis shows that the proposed optimal measurement fusion function estimate has a smaller mean square error than the LS-SVM function estimate. Moreover, the proposed cooperative learning algorithm can converge globally to the optimal measurement fusion function estimate. Finally, the proposed measurement fusion method is applied to ARMA signal and spatial temporal signal modeling. Experimental results show that the proposed measurement fusion method can provide a more accurate model.
Nonlinear inversion of potential-field data using a hybrid-encoding genetic algorithm
Chen, C.; Xia, J.; Liu, J.; Feng, G.
2006-01-01
Using a genetic algorithm to solve an inverse problem of complex nonlinear geophysical equations is advantageous because it does not require computer gradients of models or "good" initial models. The multi-point search of a genetic algorithm makes it easier to find the globally optimal solution while avoiding falling into a local extremum. As is the case in other optimization approaches, the search efficiency for a genetic algorithm is vital in finding desired solutions successfully in a multi-dimensional model space. A binary-encoding genetic algorithm is hardly ever used to resolve an optimization problem such as a simple geophysical inversion with only three unknowns. The encoding mechanism, genetic operators, and population size of the genetic algorithm greatly affect search processes in the evolution. It is clear that improved operators and proper population size promote the convergence. Nevertheless, not all genetic operations perform perfectly while searching under either a uniform binary or a decimal encoding system. With the binary encoding mechanism, the crossover scheme may produce more new individuals than with the decimal encoding. On the other hand, the mutation scheme in a decimal encoding system will create new genes larger in scope than those in the binary encoding. This paper discusses approaches of exploiting the search potential of genetic operations in the two encoding systems and presents an approach with a hybrid-encoding mechanism, multi-point crossover, and dynamic population size for geophysical inversion. We present a method that is based on the routine in which the mutation operation is conducted in the decimal code and multi-point crossover operation in the binary code. The mix-encoding algorithm is called the hybrid-encoding genetic algorithm (HEGA). HEGA provides better genes with a higher probability by a mutation operator and improves genetic algorithms in resolving complicated geophysical inverse problems. Another significant
International Nuclear Information System (INIS)
Ban, Ya.; Kotov, V.M.; Kharcharufkova, K.
1987-01-01
Algorithms for track signal filtration from bubble and streamer spark chambers read by CCD matrix with elements of 256x288 dimensions are described. The microprogrammed RISC processor is used for preliminary processing and filtration of data obtained. It makes possible to recognize and filter track elements in the zone of 0.25 mm 2 square during 0.17-0.20 s, that maintains it in real time operation
Directory of Open Access Journals (Sweden)
Felix Fritzen
2018-02-01
Full Text Available A novel algorithmic discussion of the methodological and numerical differences of competing parametric model reduction techniques for nonlinear problems is presented. First, the Galerkin reduced basis (RB formulation is presented, which fails at providing significant gains with respect to the computational efficiency for nonlinear problems. Renowned methods for the reduction of the computing time of nonlinear reduced order models are the Hyper-Reduction and the (Discrete Empirical Interpolation Method (EIM, DEIM. An algorithmic description and a methodological comparison of both methods are provided. The accuracy of the predictions of the hyper-reduced model and the (DEIM in comparison to the Galerkin RB is investigated. All three approaches are applied to a simple uncertainty quantification of a planar nonlinear thermal conduction problem. The results are compared to computationally intense finite element simulations.
Nonlinear Rayleigh wave inversion based on the shuffled frog-leaping algorithm
Sun, Cheng-Yu; Wang, Yan-Yan; Wu, Dun-Shi; Qin, Xiao-Jun
2017-12-01
At present, near-surface shear wave velocities are mainly calculated through Rayleigh wave dispersion-curve inversions in engineering surface investigations, but the required calculations pose a highly nonlinear global optimization problem. In order to alleviate the risk of falling into a local optimal solution, this paper introduces a new global optimization method, the shuffle frog-leaping algorithm (SFLA), into the Rayleigh wave dispersion-curve inversion process. SFLA is a swarm-intelligence-based algorithm that simulates a group of frogs searching for food. It uses a few parameters, achieves rapid convergence, and is capability of effective global searching. In order to test the reliability and calculation performance of SFLA, noise-free and noisy synthetic datasets were inverted. We conducted a comparative analysis with other established algorithms using the noise-free dataset, and then tested the ability of SFLA to cope with data noise. Finally, we inverted a real-world example to examine the applicability of SFLA. Results from both synthetic and field data demonstrated the effectiveness of SFLA in the interpretation of Rayleigh wave dispersion curves. We found that SFLA is superior to the established methods in terms of both reliability and computational efficiency, so it offers great potential to improve our ability to solve geophysical inversion problems.
Shi, Junwei; Liu, Fei; Zhang, Guanglei; Luo, Jianwen; Bai, Jing
2014-04-01
Owing to the high degree of scattering of light through tissues, the ill-posedness of fluorescence molecular tomography (FMT) inverse problem causes relatively low spatial resolution in the reconstruction results. Unlike L2 regularization, L1 regularization can preserve the details and reduce the noise effectively. Reconstruction is obtained through a restarted L1 regularization-based nonlinear conjugate gradient (re-L1-NCG) algorithm, which has been proven to be able to increase the computational speed with low memory consumption. The algorithm consists of inner and outer iterations. In the inner iteration, L1-NCG is used to obtain the L1-regularized results. In the outer iteration, the restarted strategy is used to increase the convergence speed of L1-NCG. To demonstrate the performance of re-L1-NCG in terms of spatial resolution, simulation and physical phantom studies with fluorescent targets located with different edge-to-edge distances were carried out. The reconstruction results show that the re-L1-NCG algorithm has the ability to resolve targets with an edge-to-edge distance of 0.1 cm at a depth of 1.5 cm, which is a significant improvement for FMT.
International Nuclear Information System (INIS)
Pang Chaoyang; Hu Benqiong
2008-01-01
The discrete Fourier transform (DFT) is the base of modern signal processing. 1-dimensional fast Fourier transform (ID FFT) and 2D FFT have time complexity O (N log N) and O (N 2 log N) respectively. Since 1965, there has been no more essential breakthrough for the design of fast DFT algorithm. DFT has two properties. One property is that DFT is energy conservation transform. The other property is that many DFT coefficients are close to zero. The basic idea of this paper is that the generalized Grover's iteration can perform the computation of DFT which acts on the entangled states to search the big DFT coefficients until these big coefficients contain nearly all energy. One-dimensional quantum DFT (ID QDFT) and two-dimensional quantum DFT (2D QDFT) are presented in this paper. The quantum algorithm for convolution estimation is also presented in this paper. Compared with FFT, ID and 2D QDFT have time complexity O(√N) and O (N) respectively. QDFT and quantum convolution demonstrate that quantum computation to process classical signal is possible. (general)
International Nuclear Information System (INIS)
Karpov, V.A.; Rybnikov, A.F.
1983-01-01
An algorithm for solving the problems associated with fast nuclear reactor computer-aided design is suggested. Formulation of the discrete optimization problem dealing with chosing of the first loading arrangement, determination of the control element functional purpose and the order of their rearrangement during reactor operation as well as the choice of operations for core reloading is given. An algorithm for computerized solutions of the mentioned optimization problem based on variational methods relized in the form of the DESIGN program complex written in FORTRAN for the BEhSM-6 computer is proposed. A fast-response program for solving the diffusion equations of two-dimensional reactor permitting to obtain the optimization problem solution at reasonable period of time is developed to conduct necessary neutron-physical calculations for the reactor in hexagonal geometry. The DESIGN program can be included into a computer-aided design system for automation of the procedure of determining the fast power reactor core arrangement. Application of the DESIGN program permits to avoid the routine calculations on substantiation of neutron-physical and thermal-hydraulic characteristics of the reactor core that releases operators from essential waste of time and increases efficiency of their work
A nonlinear relaxation/quasi-Newton algorithm for the compressible Navier-Stokes equations
Edwards, Jack R.; Mcrae, D. S.
1992-01-01
A highly efficient implicit method for the computation of steady, two-dimensional compressible Navier-Stokes flowfields is presented. The discretization of the governing equations is hybrid in nature, with flux-vector splitting utilized in the streamwise direction and central differences with flux-limited artificial dissipation used for the transverse fluxes. Line Jacobi relaxation is used to provide a suitable initial guess for a new nonlinear iteration strategy based on line Gauss-Seidel sweeps. The applicability of quasi-Newton methods as convergence accelerators for this and other line relaxation algorithms is discussed, and efficient implementations of such techniques are presented. Convergence histories and comparisons with experimental data are presented for supersonic flow over a flat plate and for several high-speed compression corner interactions. Results indicate a marked improvement in computational efficiency over more conventional upwind relaxation strategies, particularly for flowfields containing large pockets of streamwise subsonic flow.
An inertia-free filter line-search algorithm for large-scale nonlinear programming
Energy Technology Data Exchange (ETDEWEB)
Chiang, Nai-Yuan; Zavala, Victor M.
2016-02-15
We present a filter line-search algorithm that does not require inertia information of the linear system. This feature enables the use of a wide range of linear algebra strategies and libraries, which is essential to tackle large-scale problems on modern computing architectures. The proposed approach performs curvature tests along the search step to detect negative curvature and to trigger convexification. We prove that the approach is globally convergent and we implement the approach within a parallel interior-point framework to solve large-scale and highly nonlinear problems. Our numerical tests demonstrate that the inertia-free approach is as efficient as inertia detection via symmetric indefinite factorizations. We also demonstrate that the inertia-free approach can lead to reductions in solution time because it reduces the amount of convexification needed.
Identification of time-varying nonlinear systems using differential evolution algorithm
DEFF Research Database (Denmark)
Perisic, Nevena; Green, Peter L; Worden, Keith
2013-01-01
(DE) algorithm for the identification of time-varying systems. DE is an evolutionary optimisation method developed to perform direct search in a continuous space without requiring any derivative estimation. DE is modified so that the objective function changes with time to account for the continuing......, thus identification of time-varying systems with nonlinearities can be a very challenging task. In order to avoid conventional least squares and gradient identification methods which require uni-modal and double differentiable objective functions, this work proposes a modified differential evolution...... inclusion of new data within an error metric. This paper presents results of identification of a time-varying SDOF system with Coulomb friction using simulated noise-free and noisy data for the case of time-varying friction coefficient, stiffness and damping. The obtained results are promising and the focus...
Energy Technology Data Exchange (ETDEWEB)
Heasler, Patrick G.; Posse, Christian; Hylden, Jeff L.; Anderson, Kevin K.
2007-06-13
This paper presents a nonlinear Bayesian regression algorithm for the purpose of detecting and estimating gas plume content from hyper-spectral data. Remote sensing data, by its very nature, is collected under less controlled conditions than laboratory data. As a result, the physics-based model that is used to describe the relationship between the observed remotesensing spectra, and the terrestrial (or atmospheric) parameters that we desire to estimate, is typically littered with many unknown "nuisance" parameters (parameters that we are not interested in estimating, but also appear in the model). Bayesian methods are well-suited for this context as they automatically incorporate the uncertainties associated with all nuisance parameters into the error estimates of the parameters of interest. The nonlinear Bayesian regression methodology is illustrated on realistic simulated data from a three-layer model for longwave infrared (LWIR) measurements from a passive instrument. This shows that this approach should permit more accurate estimation as well as a more reasonable description of estimate uncertainty.
DEFF Research Database (Denmark)
Ghoreishi, Newsha; Sørensen, Jan Corfixen; Jørgensen, Bo Nørregaard
2015-01-01
Non-trivial real world decision-making processes usually involve multiple parties having potentially conflicting interests over a set of issues. State-of-the-art multi-objective evolutionary algorithms (MOEA) are well known to solve this class of complex real-world problems. In this paper, we...... compare the performance of state-of-the-art multi-objective evolutionary algorithms to solve a non-linear multi-objective multi-issue optimisation problem found in Greenhouse climate control. The chosen algorithms in the study includes NSGAII, eNSGAII, eMOEA, PAES, PESAII and SPEAII. The performance...... of all aforementioned algorithms is assessed and compared using performance indicators to evaluate proximity, diversity and consistency. Our insights to this comparative study enhanced our understanding of MOEAs performance in order to solve a non-linear complex climate control problem. The empirical...
Mizutani, Eiji; Demmel, James W
2003-01-01
This paper briefly introduces our numerical linear algebra approaches for solving structured nonlinear least squares problems arising from 'multiple-output' neural-network (NN) models. Our algorithms feature trust-region regularization, and exploit sparsity of either the 'block-angular' residual Jacobian matrix or the 'block-arrow' Gauss-Newton Hessian (or Fisher information matrix in statistical sense) depending on problem scale so as to render a large class of NN-learning algorithms 'efficient' in both memory and operation costs. Using a relatively large real-world nonlinear regression application, we shall explain algorithmic strengths and weaknesses, analyzing simulation results obtained by both direct and iterative trust-region algorithms with two distinct NN models: 'multilayer perceptrons' (MLP) and 'complementary mixtures of MLP-experts' (or neuro-fuzzy modular networks).
An evolutionary firefly algorithm for the estimation of nonlinear biological model parameters.
Directory of Open Access Journals (Sweden)
Afnizanfaizal Abdullah
Full Text Available The development of accurate computational models of biological processes is fundamental to computational systems biology. These models are usually represented by mathematical expressions that rely heavily on the system parameters. The measurement of these parameters is often difficult. Therefore, they are commonly estimated by fitting the predicted model to the experimental data using optimization methods. The complexity and nonlinearity of the biological processes pose a significant challenge, however, to the development of accurate and fast optimization methods. We introduce a new hybrid optimization method incorporating the Firefly Algorithm and the evolutionary operation of the Differential Evolution method. The proposed method improves solutions by neighbourhood search using evolutionary procedures. Testing our method on models for the arginine catabolism and the negative feedback loop of the p53 signalling pathway, we found that it estimated the parameters with high accuracy and within a reasonable computation time compared to well-known approaches, including Particle Swarm Optimization, Nelder-Mead, and Firefly Algorithm. We have also verified the reliability of the parameters estimated by the method using an a posteriori practical identifiability test.
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Chenlu Miao
2016-01-01
Full Text Available Many leader-follower relationships exist in product family design engineering problems. We use bilevel programming (BLP to reflect the leader-follower relationship and describe such problems. Product family design problems have unique characteristics; thus, mixed integer nonlinear BLP (MINLBLP, which has both continuous and discrete variables and multiple independent lower-level problems, is widely used in product family optimization. However, BLP is difficult in theory and is an NP-hard problem. Consequently, using traditional methods to solve such problems is difficult. Genetic algorithms (GAs have great value in solving BLP problems, and many studies have designed GAs to solve BLP problems; however, such GAs are typically designed for special cases that do not involve MINLBLP with one or multiple followers. Therefore, we propose a bilevel GA to solve these particular MINLBLP problems, which are widely used in product family problems. We give numerical examples to demonstrate the effectiveness of the proposed algorithm. In addition, a reducer family case study is examined to demonstrate practical applications of the proposed BLGA.
An evolutionary firefly algorithm for the estimation of nonlinear biological model parameters.
Abdullah, Afnizanfaizal; Deris, Safaai; Anwar, Sohail; Arjunan, Satya N V
2013-01-01
The development of accurate computational models of biological processes is fundamental to computational systems biology. These models are usually represented by mathematical expressions that rely heavily on the system parameters. The measurement of these parameters is often difficult. Therefore, they are commonly estimated by fitting the predicted model to the experimental data using optimization methods. The complexity and nonlinearity of the biological processes pose a significant challenge, however, to the development of accurate and fast optimization methods. We introduce a new hybrid optimization method incorporating the Firefly Algorithm and the evolutionary operation of the Differential Evolution method. The proposed method improves solutions by neighbourhood search using evolutionary procedures. Testing our method on models for the arginine catabolism and the negative feedback loop of the p53 signalling pathway, we found that it estimated the parameters with high accuracy and within a reasonable computation time compared to well-known approaches, including Particle Swarm Optimization, Nelder-Mead, and Firefly Algorithm. We have also verified the reliability of the parameters estimated by the method using an a posteriori practical identifiability test.
Elsheikh, A. H.
2013-12-01
Calibration of subsurface flow models is an essential step for managing ground water aquifers, designing of contaminant remediation plans, and maximizing recovery from hydrocarbon reservoirs. We investigate an efficient sampling algorithm known as nested sampling (NS), which can simultaneously sample the posterior distribution for uncertainty quantification, and estimate the Bayesian evidence for model selection. Model selection statistics, such as the Bayesian evidence, are needed to choose or assign different weights to different models of different levels of complexities. In this work, we report the first successful application of nested sampling for calibration of several nonlinear subsurface flow problems. The estimated Bayesian evidence by the NS algorithm is used to weight different parameterizations of the subsurface flow models (prior model selection). The results of the numerical evaluation implicitly enforced Occam\\'s razor where simpler models with fewer number of parameters are favored over complex models. The proper level of model complexity was automatically determined based on the information content of the calibration data and the data mismatch of the calibrated model.
Domínguez, Luis F.
2012-06-25
An algorithm for the solution of convex multiparametric mixed-integer nonlinear programming problems arising in process engineering problems under uncertainty is introduced. The proposed algorithm iterates between a multiparametric nonlinear programming subproblem and a mixed-integer nonlinear programming subproblem to provide a series of parametric upper and lower bounds. The primal subproblem is formulated by fixing the integer variables and solved through a series of multiparametric quadratic programming (mp-QP) problems based on quadratic approximations of the objective function, while the deterministic master subproblem is formulated so as to provide feasible integer solutions for the next primal subproblem. To reduce the computational effort when infeasibilities are encountered at the vertices of the critical regions (CRs) generated by the primal subproblem, a simplicial approximation approach is used to obtain CRs that are feasible at each of their vertices. The algorithm terminates when there does not exist an integer solution that is better than the one previously used by the primal problem. Through a series of examples, the proposed algorithm is compared with a multiparametric mixed-integer outer approximation (mp-MIOA) algorithm to demonstrate its computational advantages. © 2012 American Institute of Chemical Engineers (AIChE).
Directory of Open Access Journals (Sweden)
Zongyan Li
2016-01-01
Full Text Available This paper describes an improved global harmony search (IGHS algorithm for identifying the nonlinear discrete-time systems based on second-order Volterra model. The IGHS is an improved version of the novel global harmony search (NGHS algorithm, and it makes two significant improvements on the NGHS. First, the genetic mutation operation is modified by combining normal distribution and Cauchy distribution, which enables the IGHS to fully explore and exploit the solution space. Second, an opposition-based learning (OBL is introduced and modified to improve the quality of harmony vectors. The IGHS algorithm is implemented on two numerical examples, and they are nonlinear discrete-time rational system and the real heat exchanger, respectively. The results of the IGHS are compared with those of the other three methods, and it has been verified to be more effective than the other three methods on solving the above two problems with different input signals and system memory sizes.
Realization of parking task based on affine system modeling
International Nuclear Information System (INIS)
Kim, Young Woo; Narikiyo, Tatsuo
2007-01-01
This paper presents a motion control system of an unmanned vehicle, where parallel parking task is realized based on a self-organizing affine system modeling and a quadratic programming based robust controller. Because of non-linearity of the vehicle system and complexity of the task to realize, control objective is not always realized with a single algorithm or control mode. This paper presents a hybrid model for parallel parking task in which seven modes for describing sub-tasks constitute an entire model
International Nuclear Information System (INIS)
Fujiwara, Shingo; Hasegawa, Shuichi
2005-01-01
It is well known that, in order to build the universal quantum circuit, one only needs one-qubit rotation gate and two-qubit controlled-NOT gate and until now quantum networks have been built from these gates. However, the minimum components of quantum networks in real experiments are not these quantum gates, so we develop a general method for realizing the conditional phase-shift gate in multiqubit ion-trap quantum computation which has the scalability to N qubits (N≥3). The duration of the laser manipulations for the proposed conditional phase-shift gate is almost the same as that for the controlled-NOT gate in ion-trap quantum computation. Moreover, we simulate Grover's algorithm taking into consideration the real laser fluctuations and analyze the effect of decoherence on the practical search
Arteaga, Santiago Egido
1998-12-01
linearization strategies considered and whose computational cost is negligible. The algebraic properties of these systems depend on both the discretization and nonlinear method used. We study in detail the positive definiteness and skewsymmetry of the advection submatrices (essentially, convection-diffusion problems). We propose a discretization based on a new trilinear form for Newton's method. We solve the linear systems using three Krylov subspace methods, GMRES, QMR and TFQMR, and compare the advantages of each. Our emphasis is on parallel algorithms, and so we consider preconditioners suitable for parallel computers such as line variants of the Jacobi and Gauss- Seidel methods, alternating direction implicit methods, and Chebyshev and least squares polynomial preconditioners. These work well for moderate viscosities (moderate Reynolds number). For small viscosities we show that effective parallel solution of the advection subproblem is a critical factor to improve performance. Implementation details on a CM-5 are presented.
Calibration of Mine Ventilation Network Models Using the Non-Linear Optimization Algorithm
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Guang Xu
2017-12-01
Full Text Available Effective ventilation planning is vital to underground mining. To ensure stable operation of the ventilation system and to avoid airflow disorder, mine ventilation network (MVN models have been widely used in simulating and optimizing the mine ventilation system. However, one of the challenges for MVN model simulation is that the simulated airflow distribution results do not match the measured data. To solve this problem, a simple and effective calibration method is proposed based on the non-linear optimization algorithm. The calibrated model not only makes simulated airflow distribution results in accordance with the on-site measured data, but also controls the errors of other parameters within a minimum range. The proposed method was then applied to calibrate an MVN model in a real case, which is built based on ventilation survey results and Ventsim software. Finally, airflow simulation experiments are carried out respectively using data before and after calibration, whose results were compared and analyzed. This showed that the simulated airflows in the calibrated model agreed much better to the ventilation survey data, which verifies the effectiveness of calibrating method.
Ojo, A. O.; Xie, Jun; Olorunfemi, M. O.
2018-01-01
To reduce ambiguity related to nonlinearities in the resistivity model-data relationships, an efficient direct-search scheme employing the Neighbourhood Algorithm (NA) was implemented to solve the 1-D resistivity problem. In addition to finding a range of best-fit models which are more likely to be global minimums, this method investigates the entire multi-dimensional model space and provides additional information about the posterior model covariance matrix, marginal probability density function and an ensemble of acceptable models. This provides new insights into how well the model parameters are constrained and make assessing trade-offs between them possible, thus avoiding some common interpretation pitfalls. The efficacy of the newly developed program is tested by inverting both synthetic (noisy and noise-free) data and field data from other authors employing different inversion methods so as to provide a good base for comparative performance. In all cases, the inverted model parameters were in good agreement with the true and recovered model parameters from other methods and remarkably correlate with the available borehole litho-log and known geology for the field dataset. The NA method has proven to be useful whilst a good starting model is not available and the reduced number of unknowns in the 1-D resistivity inverse problem makes it an attractive alternative to the linearized methods. Hence, it is concluded that the newly developed program offers an excellent complementary tool for the global inversion of the layered resistivity structure.
Prediction of Flood Warning in Taiwan Using Nonlinear SVM with Simulated Annealing Algorithm
Lee, C.
2013-12-01
The issue of the floods is important in Taiwan. It is because the narrow and high topography of the island make lots of rivers steep in Taiwan. The tropical depression likes typhoon always causes rivers to flood. Prediction of river flow under the extreme rainfall circumstances is important for government to announce the warning of flood. Every time typhoon passed through Taiwan, there were always floods along some rivers. The warning is classified to three levels according to the warning water levels in Taiwan. The propose of this study is to predict the level of floods warning from the information of precipitation, rainfall duration and slope of riverbed. To classify the level of floods warning by the above-mentioned information and modeling the problems, a machine learning model, nonlinear Support vector machine (SVM), is formulated to classify the level of floods warning. In addition, simulated annealing (SA), a probabilistic heuristic algorithm, is used to determine the optimal parameter of the SVM model. A case study of flooding-trend rivers of different gradients in Taiwan is conducted. The contribution of this SVM model with simulated annealing is capable of making efficient announcement for flood warning and keeping the danger of flood from residents along the rivers.
Directory of Open Access Journals (Sweden)
Qiang Zhang
2017-09-01
Full Text Available Course keeping is hard to implement under the condition of the propeller stopping or reversing at slow speed for berthing due to the ship's dynamic motion becoming highly nonlinear. To solve this problem, a practical Maneuvering Modeling Group (MMG ship mathematic model with propeller reversing transverse forces and low speed correction is first discussed to be applied for the right-handed single-screw ship. Secondly, a novel PID-based nonlinear feedback algorithm driven by bipolar sigmoid function is proposed. The PID parameters are determined by a closed-loop gain shaping algorithm directly, while the closed-loop gain shaping theory was employed for effects analysis of this algorithm. Finally, simulation experiments were carried out on an LPG ship. It is shown that the energy consumption and the smoothness performance of the nonlinear feedback control are reduced by 4.2% and 14.6% with satisfactory control effects; the proposed algorithm has the advantages of robustness, energy saving and safety in berthing practice.
Wang, Xiaogang; Chen, Wen; Chen, Xudong
2014-09-22
We present a novel image hiding method based on phase retrieval algorithm under the framework of nonlinear double random phase encoding in fractional Fourier domain. Two phase-only masks (POMs) are efficiently determined by using the phase retrieval algorithm, in which two cascaded phase-truncated fractional Fourier transforms (FrFTs) are involved. No undesired information disclosure, post-processing of the POMs or digital inverse computation appears in our proposed method. In order to achieve the reduction in key transmission, a modified image hiding method based on the modified phase retrieval algorithm and logistic map is further proposed in this paper, in which the fractional orders and the parameters with respect to the logistic map are regarded as encryption keys. Numerical results have demonstrated the feasibility and effectiveness of the proposed algorithms.
Dreano, Denis
2017-04-05
Specification and tuning of errors from dynamical models are important issues in data assimilation. In this work, we propose an iterative expectation-maximisation (EM) algorithm to estimate the model error covariances using classical extended and ensemble versions of the Kalman smoother. We show that, for additive model errors, the estimate of the error covariance converges. We also investigate other forms of model error, such as parametric or multiplicative errors. We show that additive Gaussian model error is able to compensate for non additive sources of error in the algorithms we propose. We also demonstrate the limitations of the extended version of the algorithm and recommend the use of the more robust and flexible ensemble version. This article is a proof of concept of the methodology with the Lorenz-63 attractor. We developed an open-source Python library to enable future users to apply the algorithm to their own nonlinear dynamical models.
Tchapet Njafa, J-P; Nana Engo, S G
2018-01-01
This paper presents the QAMDiagnos, a model of Quantum Associative Memory (QAM) that can be a helpful tool for medical staff without experience or laboratory facilities, for the diagnosis of four tropical diseases (malaria, typhoid fever, yellow fever and dengue) which have several similar signs and symptoms. The memory can distinguish a single infection from a polyinfection. Our model is a combination of the improved versions of the original linear quantum retrieving algorithm proposed by Ventura and the non-linear quantum search algorithm of Abrams and Lloyd. From the given simulation results, it appears that the efficiency of recognition is good when particular signs and symptoms of a disease are inserted given that the linear algorithm is the main algorithm. The non-linear algorithm helps confirm or correct the diagnosis or give some advice to the medical staff for the treatment. So, our QAMDiagnos that has a friendly graphical user interface for desktop and smart-phone is a sensitive and a low-cost diagnostic tool that enables rapid and accurate diagnosis of four tropical diseases. Copyright © 2017 Elsevier Ltd. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Liu, Yunlong; Wang, Aiping; Guo, Lei; Wang, Hong
2017-07-09
This paper presents an error-entropy minimization tracking control algorithm for a class of dynamic stochastic system. The system is represented by a set of time-varying discrete nonlinear equations with non-Gaussian stochastic input, where the statistical properties of stochastic input are unknown. By using Parzen windowing with Gaussian kernel to estimate the probability densities of errors, recursive algorithms are then proposed to design the controller such that the tracking error can be minimized. The performance of the error-entropy minimization criterion is compared with the mean-square-error minimization in the simulation results.
Murli, Almerico; High Performance Algorithms and Software for Nonlinear Optics
2003-01-01
This volume contains the edited texts of the lectures presented at the Workshop on High Performance Algorithms and Software for Nonlinear Optimization held in Erice, Sicily, at the "G. Stampacchia" School of Mathematics of the "E. Majorana" Centre for Scientific Culture, June 30 - July 8, 2001. In the first year of the new century, the aim of the Workshop was to assess the past and to discuss the future of Nonlinear Optimization, and to highlight recent achieve ments and promising research trends in this field. An emphasis was requested on algorithmic and high performance software developments and on new computational experiences, as well as on theoretical advances. We believe that such goal was basically achieved. The Workshop was attended by 71 people from 22 countries. Although not all topics were covered, the presentations gave indeed a wide overview of the field, from different and complementary stand points. Besides the lectures, several formal and informal discussions took place. We wish ...
Ilyas, Muhammad; Hong, Beomjin; Cho, Kuk; Baeg, Seung-Ho; Park, Sangdeok
2016-01-01
This paper provides algorithms to fuse relative and absolute microelectromechanical systems (MEMS) navigation sensors, suitable for micro planetary rovers, to provide a more accurate estimation of navigation information, specifically, attitude and position. Planetary rovers have extremely slow speed (~1 cm/s) and lack conventional navigation sensors/systems, hence the general methods of terrestrial navigation may not be applicable to these applications. While relative attitude and position can be tracked in a way similar to those for ground robots, absolute navigation information is hard to achieve on a remote celestial body, like Moon or Mars, in contrast to terrestrial applications. In this study, two absolute attitude estimation algorithms were developed and compared for accuracy and robustness. The estimated absolute attitude was fused with the relative attitude sensors in a framework of nonlinear filters. The nonlinear Extended Kalman filter (EKF) and Unscented Kalman filter (UKF) were compared in pursuit of better accuracy and reliability in this nonlinear estimation problem, using only on-board low cost MEMS sensors. Experimental results confirmed the viability of the proposed algorithms and the sensor suite, for low cost and low weight micro planetary rovers. It is demonstrated that integrating the relative and absolute navigation MEMS sensors reduces the navigation errors to the desired level. PMID:27223293
National Research Council Canada - National Science Library
Homaifar, Abdollah; Esterline, Albert; Kimiaghalam, Bahram
2005-01-01
The Hybrid Projected Gradient-Evolutionary Search Algorithm (HPGES) algorithm uses a specially designed evolutionary-based global search strategy to efficiently create candidate solutions in the solution space...
International Nuclear Information System (INIS)
Tiilikainen, J; Tilli, J-M; Bosund, V; Mattila, M; Hakkarainen, T; Airaksinen, V-M; Lipsanen, H
2007-01-01
Two novel genetic algorithms implementing principal component analysis and an adaptive nonlinear fitness-space-structure technique are presented and compared with conventional algorithms in x-ray reflectivity analysis. Principal component analysis based on Hessian or interparameter covariance matrices is used to rotate a coordinate frame. The nonlinear adaptation applies nonlinear estimates to reshape the probability distribution of the trial parameters. The simulated x-ray reflectivity of a realistic model of a periodic nanolaminate structure was used as a test case for the fitting algorithms. The novel methods had significantly faster convergence and less stagnation than conventional non-adaptive genetic algorithms. The covariance approach needs no additional curve calculations compared with conventional methods, and it had better convergence properties than the computationally expensive Hessian approach. These new algorithms can also be applied to other fitting problems where tight interparameter dependence is present
Directory of Open Access Journals (Sweden)
Akemi Gálvez
2013-01-01
Full Text Available Fitting spline curves to data points is a very important issue in many applied fields. It is also challenging, because these curves typically depend on many continuous variables in a highly interrelated nonlinear way. In general, it is not possible to compute these parameters analytically, so the problem is formulated as a continuous nonlinear optimization problem, for which traditional optimization techniques usually fail. This paper presents a new bioinspired method to tackle this issue. In this method, optimization is performed through a combination of two techniques. Firstly, we apply the indirect approach to the knots, in which they are not initially the subject of optimization but precomputed with a coarse approximation scheme. Secondly, a powerful bioinspired metaheuristic technique, the firefly algorithm, is applied to optimization of data parameterization; then, the knot vector is refined by using De Boor’s method, thus yielding a better approximation to the optimal knot vector. This scheme converts the original nonlinear continuous optimization problem into a convex optimization problem, solved by singular value decomposition. Our method is applied to some illustrative real-world examples from the CAD/CAM field. Our experimental results show that the proposed scheme can solve the original continuous nonlinear optimization problem very efficiently.
Comparative Study of FDTD-Adopted Numerical Algorithms for Kerr Nonlinearities
DEFF Research Database (Denmark)
Maksymov, Ivan S.; Sukhorukov, Andrey A.; Lavrinenko, Andrei
2011-01-01
Accurate finite-difference time-domain (FDTD) modeling of optical pulse propagation in nonlinear media usually implies the use of auxiliary differential equation (ADE) techniques. The updating of electric field in full-vectorial 3-D ADE FDTD modeling of the optical Kerr effect and two-photon abso...... approaches. Such schemes can significantly reduce the CPU time for nonlinear computations, especially in 3-D models....
Zhang, Wei; Bao, Zhangmin; Jiang, Shan; He, Jingjing
2016-06-17
In the aerospace and aviation sectors, the damage tolerance concept has been applied widely so that the modeling analysis of fatigue crack growth has become more and more significant. Since the process of crack propagation is highly nonlinear and determined by many factors, such as applied stress, plastic zone in the crack tip, length of the crack, etc. , it is difficult to build up a general and flexible explicit function to accurately quantify this complicated relationship. Fortunately, the artificial neural network (ANN) is considered a powerful tool for establishing the nonlinear multivariate projection which shows potential in handling the fatigue crack problem. In this paper, a novel fatigue crack calculation algorithm based on a radial basis function (RBF)-ANN is proposed to study this relationship from the experimental data. In addition, a parameter called the equivalent stress intensity factor is also employed as training data to account for loading interaction effects. The testing data is then placed under constant amplitude loading with different stress ratios or overloads used for model validation. Moreover, the Forman and Wheeler equations are also adopted to compare with our proposed algorithm. The current investigation shows that the ANN-based approach can deliver a better agreement with the experimental data than the other two models, which supports that the RBF-ANN has nontrivial advantages in handling the fatigue crack growth problem. Furthermore, it implies that the proposed algorithm is possibly a sophisticated and promising method to compute fatigue crack growth in terms of loading interaction effects.
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Chung-Ta Li
2014-01-01
Full Text Available We propose a species-based hybrid of the electromagnetism-like mechanism (EM and back-propagation algorithms (SEMBP for an interval type-2 fuzzy neural system with asymmetric membership functions (AIT2FNS design. The interval type-2 asymmetric fuzzy membership functions (IT2 AFMFs and the TSK-type consequent part are adopted to implement the network structure in AIT2FNS. In addition, the type reduction procedure is integrated into an adaptive network structure to reduce computational complexity. Hence, the AIT2FNS can enhance the approximation accuracy effectively by using less fuzzy rules. The AIT2FNS is trained by the SEMBP algorithm, which contains the steps of uniform initialization, species determination, local search, total force calculation, movement, and evaluation. It combines the advantages of EM and back-propagation (BP algorithms to attain a faster convergence and a lower computational complexity. The proposed SEMBP algorithm adopts the uniform method (which evenly scatters solution agents over the feasible solution region and the species technique to improve the algorithm’s ability to find the global optimum. Finally, two illustrative examples of nonlinear systems control are presented to demonstrate the performance and the effectiveness of the proposed AIT2FNS with the SEMBP algorithm.
Bandyopadhyay, Saptarshi
guidance algorithms using results from numerical simulations and closed-loop hardware experiments on multiple quadrotors. In the second part of this dissertation, we present two novel discrete-time algorithms for distributed estimation, which track a single target using a network of heterogeneous sensing agents. The Distributed Bayesian Filtering (DBF) algorithm, the sensing agents combine their normalized likelihood functions using the logarithmic opinion pool and the discrete-time dynamic average consensus algorithm. Each agent's estimated likelihood function converges to an error ball centered on the joint likelihood function of the centralized multi-sensor Bayesian filtering algorithm. Using a new proof technique, the convergence, stability, and robustness properties of the DBF algorithm are rigorously characterized. The explicit bounds on the time step of the robust DBF algorithm are shown to depend on the time-scale of the target dynamics. Furthermore, the DBF algorithm for linear-Gaussian models can be cast into a modified form of the Kalman information filter. In the Bayesian Consensus Filtering (BCF) algorithm, the agents combine their estimated posterior pdfs multiple times within each time step using the logarithmic opinion pool scheme. Thus, each agent's consensual pdf minimizes the sum of Kullback-Leibler divergences with the local posterior pdfs. The performance and robust properties of these algorithms are validated using numerical simulations. In the third part of this dissertation, we present an attitude control strategy and a new nonlinear tracking controller for a spacecraft carrying a large object, such as an asteroid or a boulder. If the captured object is larger or comparable in size to the spacecraft and has significant modeling uncertainties, conventional nonlinear control laws that use exact feed-forward cancellation are not suitable because they exhibit a large resultant disturbance torque. The proposed nonlinear tracking control law guarantees
International Nuclear Information System (INIS)
Yan Zhenya
2005-01-01
A new transformation method is developed using the general sine-Gordon travelling wave reduction equation and a generalized transformation. With the aid of symbolic computation, this method can be used to seek more types of solutions of nonlinear differential equations, which include not only the known solutions derived by some known methods but new solutions. Here we choose the double sine-Gordon equation, the Magma equation and the generalized Pochhammer-Chree (PC) equation to illustrate the method. As a result, many types of new doubly periodic solutions are obtained. Moreover when using the method to these special nonlinear differential equations, some transformations are firstly needed. The method can be also extended to other nonlinear differential equations
Indian Academy of Sciences (India)
polynomial) division have been found in Vedic Mathematics which are dated much before Euclid's algorithm. A programming language Is used to describe an algorithm for execution on a computer. An algorithm expressed using a programming.
Xu, Yunjun; Remeikas, Charles; Pham, Khanh
2014-03-01
Cooperative trajectory planning is crucial for networked vehicles to respond rapidly in cluttered environments and has a significant impact on many applications such as air traffic or border security monitoring and assessment. One of the challenges in cooperative planning is to find a computationally efficient algorithm that can accommodate both the complexity of the environment and real hardware and configuration constraints of vehicles in the formation. Inspired by a local pursuit strategy observed in foraging ants, feasible and optimal trajectory planning algorithms are proposed in this paper for a class of nonlinear constrained cooperative vehicles in environments with densely populated obstacles. In an iterative hierarchical approach, the local behaviours, such as the formation stability, obstacle avoidance, and individual vehicle's constraints, are considered in each vehicle's (i.e. follower's) decentralised optimisation. The cooperative-level behaviours, such as the inter-vehicle collision avoidance, are considered in the virtual leader's centralised optimisation. Early termination conditions are derived to reduce the computational cost by not wasting time in the local-level optimisation if the virtual leader trajectory does not satisfy those conditions. The expected advantages of the proposed algorithms are (1) the formation can be globally asymptotically maintained in a decentralised manner; (2) each vehicle decides its local trajectory using only the virtual leader and its own information; (3) the formation convergence speed is controlled by one single parameter, which makes it attractive for many practical applications; (4) nonlinear dynamics and many realistic constraints, such as the speed limitation and obstacle avoidance, can be easily considered; (5) inter-vehicle collision avoidance can be guaranteed in both the formation transient stage and the formation steady stage; and (6) the computational cost in finding both the feasible and optimal
A Modified LQG Algorithm (MLQG for Robust Control of Nonlinear Multivariable Systems
Directory of Open Access Journals (Sweden)
Jens G. Balchen
1993-07-01
Full Text Available The original LQG algorithm is often characterized for its lack of robustness. This is because in the design of the estimator (Kalman filter the process disturbance is assumed to be white noise. If the estimator is to give good estimates, the Kalman gain is increased which means that the estimator fails to become robust. A solution to this problem is to replace the proportional Kalman gain matrix by a dynamic PI algorithm and the proportional LQ feedback gain matrix by a PI algorithm. A tuning method is developed which facilitates the tuning of a modified LQG control system (MLQG by only two tuning parameters.
Wu, Huai-Ning; Luo, Biao
2012-12-01
It is well known that the nonlinear H∞ state feedback control problem relies on the solution of the Hamilton-Jacobi-Isaacs (HJI) equation, which is a nonlinear partial differential equation that has proven to be impossible to solve analytically. In this paper, a neural network (NN)-based online simultaneous policy update algorithm (SPUA) is developed to solve the HJI equation, in which knowledge of internal system dynamics is not required. First, we propose an online SPUA which can be viewed as a reinforcement learning technique for two players to learn their optimal actions in an unknown environment. The proposed online SPUA updates control and disturbance policies simultaneously; thus, only one iterative loop is needed. Second, the convergence of the online SPUA is established by proving that it is mathematically equivalent to Newton's method for finding a fixed point in a Banach space. Third, we develop an actor-critic structure for the implementation of the online SPUA, in which only one critic NN is needed for approximating the cost function, and a least-square method is given for estimating the NN weight parameters. Finally, simulation studies are provided to demonstrate the effectiveness of the proposed algorithm.
International Nuclear Information System (INIS)
Wang Jianzhou; Jia Ruiling; Zhao Weigang; Wu Jie; Dong Yao
2012-01-01
Highlights: ► The maximal predictive step size is determined by the largest Lyapunov exponent. ► A proper forecasting step size is applied to load demand forecasting. ► The improved approach is validated by the actual load demand data. ► Non-linear fractal extrapolation method is compared with three forecasting models. ► Performance of the models is evaluated by three different error measures. - Abstract: Precise short-term load forecasting (STLF) plays a key role in unit commitment, maintenance and economic dispatch problems. Employing a subjective and arbitrary predictive step size is one of the most important factors causing the low forecasting accuracy. To solve this problem, the largest Lyapunov exponent is adopted to estimate the maximal predictive step size so that the step size in the forecasting is no more than this maximal one. In addition, in this paper a seldom used forecasting model, which is based on the non-linear fractal extrapolation (NLFE) algorithm, is considered to develop the accuracy of predictions. The suitability and superiority of the two solutions are illustrated through an application to real load forecasting using New South Wales electricity load data from the Australian National Electricity Market. Meanwhile, three forecasting models: the gray model, the seasonal autoregressive integrated moving average approach and the support vector machine method, which received high approval in STLF, are selected to compare with the NLFE algorithm. Comparison results also show that the NLFE model is outstanding, effective, practical and feasible.
Fsheikh, Ahmed H.; Wheeler, Mary Fanett; Hoteit, Ibrahim
2013-01-01
the dictionary, the solution is obtained by applying Tikhonov regularization. The proposed algorithm relies on approximate gradient estimation using an iterative stochastic ensemble method (ISEM). ISEM utilizes an ensemble of directional derivatives
Umbarkar, A. J.; Balande, U. T.; Seth, P. D.
2017-06-01
The field of nature inspired computing and optimization techniques have evolved to solve difficult optimization problems in diverse fields of engineering, science and technology. The firefly attraction process is mimicked in the algorithm for solving optimization problems. In Firefly Algorithm (FA) sorting of fireflies is done by using sorting algorithm. The original FA is proposed with bubble sort for ranking the fireflies. In this paper, the quick sort replaces bubble sort to decrease the time complexity of FA. The dataset used is unconstrained benchmark functions from CEC 2005 [22]. The comparison of FA using bubble sort and FA using quick sort is performed with respect to best, worst, mean, standard deviation, number of comparisons and execution time. The experimental result shows that FA using quick sort requires less number of comparisons but requires more execution time. The increased number of fireflies helps to converge into optimal solution whereas by varying dimension for algorithm performed better at a lower dimension than higher dimension.
Elsheikh, A. H.; Wheeler, M. F.; Hoteit, Ibrahim
2013-01-01
Calibration of subsurface flow models is an essential step for managing ground water aquifers, designing of contaminant remediation plans, and maximizing recovery from hydrocarbon reservoirs. We investigate an efficient sampling algorithm known
Miró, Anton; Pozo, Carlos; Guillén-Gosálbez, Gonzalo; Egea, Jose A; Jiménez, Laureano
2012-05-10
The estimation of parameter values for mathematical models of biological systems is an optimization problem that is particularly challenging due to the nonlinearities involved. One major difficulty is the existence of multiple minima in which standard optimization methods may fall during the search. Deterministic global optimization methods overcome this limitation, ensuring convergence to the global optimum within a desired tolerance. Global optimization techniques are usually classified into stochastic and deterministic. The former typically lead to lower CPU times but offer no guarantee of convergence to the global minimum in a finite number of iterations. In contrast, deterministic methods provide solutions of a given quality (i.e., optimality gap), but tend to lead to large computational burdens. This work presents a deterministic outer approximation-based algorithm for the global optimization of dynamic problems arising in the parameter estimation of models of biological systems. Our approach, which offers a theoretical guarantee of convergence to global minimum, is based on reformulating the set of ordinary differential equations into an equivalent set of algebraic equations through the use of orthogonal collocation methods, giving rise to a nonconvex nonlinear programming (NLP) problem. This nonconvex NLP is decomposed into two hierarchical levels: a master mixed-integer linear programming problem (MILP) that provides a rigorous lower bound on the optimal solution, and a reduced-space slave NLP that yields an upper bound. The algorithm iterates between these two levels until a termination criterion is satisfied. The capabilities of our approach were tested in two benchmark problems, in which the performance of our algorithm was compared with that of the commercial global optimization package BARON. The proposed strategy produced near optimal solutions (i.e., within a desired tolerance) in a fraction of the CPU time required by BARON.
Lim, Néhémy; Senbabaoglu, Yasin; Michailidis, George; d'Alché-Buc, Florence
2013-06-01
Reverse engineering of gene regulatory networks remains a central challenge in computational systems biology, despite recent advances facilitated by benchmark in silico challenges that have aided in calibrating their performance. A number of approaches using either perturbation (knock-out) or wild-type time-series data have appeared in the literature addressing this problem, with the latter using linear temporal models. Nonlinear dynamical models are particularly appropriate for this inference task, given the generation mechanism of the time-series data. In this study, we introduce a novel nonlinear autoregressive model based on operator-valued kernels that simultaneously learns the model parameters, as well as the network structure. A flexible boosting algorithm (OKVAR-Boost) that shares features from L2-boosting and randomization-based algorithms is developed to perform the tasks of parameter learning and network inference for the proposed model. Specifically, at each boosting iteration, a regularized Operator-valued Kernel-based Vector AutoRegressive model (OKVAR) is trained on a random subnetwork. The final model consists of an ensemble of such models. The empirical estimation of the ensemble model's Jacobian matrix provides an estimation of the network structure. The performance of the proposed algorithm is first evaluated on a number of benchmark datasets from the DREAM3 challenge and then on real datasets related to the In vivo Reverse-Engineering and Modeling Assessment (IRMA) and T-cell networks. The high-quality results obtained strongly indicate that it outperforms existing approaches. The OKVAR-Boost Matlab code is available as the archive: http://amis-group.fr/sourcecode-okvar-boost/OKVARBoost-v1.0.zip. Supplementary data are available at Bioinformatics online.
Chenlu Miao; Gang Du; Yi Xia; Danping Wang
2016-01-01
Many leader-follower relationships exist in product family design engineering problems. We use bilevel programming (BLP) to reflect the leader-follower relationship and describe such problems. Product family design problems have unique characteristics; thus, mixed integer nonlinear BLP (MINLBLP), which has both continuous and discrete variables and multiple independent lower-level problems, is widely used in product family optimization. However, BLP is difficult in theory and is an NP-hard pr...
Nonlinear observer based fault detection and isolation for a momentum wheel
DEFF Research Database (Denmark)
Jensen, Hans-Christian Becker; Wisniewski, Rafal
2001-01-01
This article realizes nonlinear Fault Detection and Isolation for a momentum wheel. The Fault Detection and Isolation is based on a Failure Mode and Effect Analysis, which states which faults might occur and can be detected. The algorithms presented in this paper are based on a geometric approach...... toachieve nonlinear Fault Detection and Isolation. The proposed algorithms are tested in a simulation study and the pros and cons of the algorithm are discussed....
2015-04-01
HPD model. In an article on measuring HPD attenuation, Berger (1986) points out that Real Ear Attenuation at Threshold (REAT) tests are...men. Audiology . 1991;30:345–356. Fedele P, Binseel M, Kalb J, Price GR. Using the auditory hazard assessment algorithm for humans (AHAAH) with
A non-linear algorithm for current signal filtering and peak detection in SiPM
International Nuclear Information System (INIS)
Putignano, M; Intermite, A; Welsch, C P
2012-01-01
Read-out of Silicon Photomultipliers is commonly achieved by means of charge integration, a method particularly susceptible to after-pulsing noise and not efficient for low level light signals. Current signal monitoring, characterized by easier electronic implementation and intrinsically faster than charge integration, is also more suitable for low level light signals and can potentially result in much decreased after-pulsing noise effects. However, its use is to date limited by the need of developing a suitable read-out algorithm for signal analysis and filtering able to achieve current peak detection and measurement with the needed precision and accuracy. In this paper we present an original algorithm, based on a piecewise linear-fitting approach, to filter the noise of the current signal and hence efficiently identifying and measuring current peaks. The proposed algorithm is then compared with the optimal linear filtering algorithm for time-encoded peak detection, based on a moving average routine, and assessed in terms of accuracy, precision, and peak detection efficiency, demonstrating improvements of 1÷2 orders of magnitude in all these quality factors.
Cengizci, Süleyman; Atay, Mehmet Tarık; Eryılmaz, Aytekin
2016-01-01
This paper is concerned with two-point boundary value problems for singularly perturbed nonlinear ordinary differential equations. The case when the solution only has one boundary layer is examined. An efficient method so called Successive Complementary Expansion Method (SCEM) is used to obtain uniformly valid approximations to this kind of solutions. Four test problems are considered to check the efficiency and accuracy of the proposed method. The numerical results are found in good agreement with exact and existing solutions in literature. The results confirm that SCEM has a superiority over other existing methods in terms of easy-applicability and effectiveness.
International Nuclear Information System (INIS)
Jaafar, Hazriq Izzuan; Ali, Nursabillilah Mohd; Selamat, Nur Asmiza; Kassim, Anuar Mohamed; Mohamed, Z; Abidin, Amar Faiz Zainal; Jamian, J J
2013-01-01
This paper presents development of an optimal PID and PD controllers for controlling the nonlinear gantry crane system. The proposed Binary Particle Swarm Optimization (BPSO) algorithm that uses Priority-based Fitness Scheme is adopted in obtaining five optimal controller gains. The optimal gains are tested on a control structure that combines PID and PD controllers to examine system responses including trolley displacement and payload oscillation. The dynamic model of gantry crane system is derived using Lagrange equation. Simulation is conducted within Matlab environment to verify the performance of system in terms of settling time (Ts), steady state error (SSE) and overshoot (OS). This proposed technique demonstrates that implementation of Priority-based Fitness Scheme in BPSO is effective and able to move the trolley as fast as possible to the various desired position
DEFF Research Database (Denmark)
Boiroux, Dimitri; Hagdrup, Morten; Mahmoudi, Zeinab
2016-01-01
patients with different physiological parameters and a time-varying insulin sensitivity using the Medtronic Virtual Patient (MVP) model. We augment the MVP model with stochastic diffusion terms, time-varying insulin sensitivity and noise-corrupted CGM measurements. We consider meal challenges where......This paper presents a novel ensemble nonlinear model predictive control (NMPC) algorithm for glucose regulation in type 1 diabetes. In this approach, we consider a number of scenarios describing different uncertainties, for instance meals or metabolic variations. We simulate a population of 9...... the uncertainty in meal size is ±50%. Numerical results show that the ensemble NMPC reduces the risk of hypoglycemia compared to standard NMPC in the case where the meal size is overestimated or correctly estimated at the expense of a slightly increased number of hyperglycemia. Therefore, ensemble MPC...
Non-linear algorithms solved with the help of the GIBIANE macro-language
International Nuclear Information System (INIS)
Ebersolt, L.; Combescure, A.; Millard, A.; Verpeaux, P.
1987-01-01
Non linear finite element problems are often solved with the help of iteratives procedures. In the finite element program CASTEM 2000, the syntax of the dataset permits the user to derive his own algorithm and tune it to his problem. These basic ideas, simple to imagine, needed a proper frame to be materialized in a general purpose finite element program, and three concepts emerged: Operators, the Gibiane macro-language. In the two first paragraphs, we will detail these concepts, in the third paragraph, we will describe the different possibilities of the program, in the fourth paragraph, we will show, by combining operators in a proper order, how to obtain the desired algorithm. (orig./GL)
On Algorithms for Nonlinear Minimax and Min-Max-Min Problems and Their Efficiency
2011-03-01
dissertation is complete, I can finally stay home after dinner to play Wii with you. LET’S GO Mario and Yellow Mushroom... xv THIS PAGE INTENTIONALLY... balance the accuracy of the approximation with problem ill-conditioning. The sim- plest smoothing algorithm creates an accurate smooth approximating...sizing in electronic circuit boards (Chen & Fan, 1998), obstacle avoidance for robots (Kirjner- Neto & Polak, 1998), optimal design centering
Directory of Open Access Journals (Sweden)
Ming Dong
2010-01-01
Full Text Available The primary objective of engineering asset management is to optimize assets service delivery potential and to minimize the related risks and costs over their entire life through the development and application of asset health and usage management in which the health and reliability prediction plays an important role. In real-life situations where an engineering asset operates under dynamic operational and environmental conditions, the lifetime of an engineering asset is generally described as monitored nonlinear time-series data and subject to high levels of uncertainty and unpredictability. It has been proved that application of data mining techniques is very useful for extracting relevant features which can be used as parameters for assets diagnosis and prognosis. In this paper, a tutorial on nonlinear time-series data mining in engineering asset health and reliability prediction is given. Besides that an overview on health and reliability prediction techniques for engineering assets is covered, this tutorial will focus on concepts, models, algorithms, and applications of hidden Markov models (HMMs and hidden semi-Markov models (HSMMs in engineering asset health prognosis, which are representatives of recent engineering asset health prediction techniques.
DEFF Research Database (Denmark)
Schmidt, Lasse; Andersen, Torben O.
2016-01-01
The application of second order sliding mode algorithms for output feedback control in hydraulic valve-cylinder drives appear attractive due to their simple realization and parametrization, and strong robustness toward bounded parameter variations and uncertainties. However, intrinsic nonlinear...
Fang, Fang; Ni, Bing-Jie; Yu, Han-Qing
2009-06-01
In this study, weighted non-linear least-squares analysis and accelerating genetic algorithm are integrated to estimate the kinetic parameters of substrate consumption and storage product formation of activated sludge. A storage product formation equation is developed and used to construct the objective function for the determination of its production kinetics. The weighted least-squares analysis is employed to calculate the differences in the storage product concentration between the model predictions and the experimental data as the sum of squared weighted errors. The kinetic parameters for the substrate consumption and the storage product formation are estimated to be the maximum heterotrophic growth rate of 0.121/h, the yield coefficient of 0.44 mg CODX/mg CODS (COD, chemical oxygen demand) and the substrate half saturation constant of 16.9 mg/L, respectively, by minimizing the objective function using a real-coding-based accelerating genetic algorithm. Also, the fraction of substrate electrons diverted to the storage product formation is estimated to be 0.43 mg CODSTO/mg CODS. The validity of our approach is confirmed by the results of independent tests and the kinetic parameter values reported in literature, suggesting that this approach could be useful to evaluate the product formation kinetics of mixed cultures like activated sludge. More importantly, as this integrated approach could estimate the kinetic parameters rapidly and accurately, it could be applied to other biological processes.
Nonlinear Multiantenna Detection Methods
Directory of Open Access Journals (Sweden)
Chen Sheng
2004-01-01
Full Text Available A nonlinear detection technique designed for multiple-antenna assisted receivers employed in space-division multiple-access systems is investigated. We derive the optimal solution of the nonlinear spatial-processing assisted receiver for binary phase shift keying signalling, which we refer to as the Bayesian detector. It is shown that this optimal Bayesian receiver significantly outperforms the standard linear beamforming assisted receiver in terms of a reduced bit error rate, at the expense of an increased complexity, while the achievable system capacity is substantially enhanced with the advent of employing nonlinear detection. Specifically, when the spatial separation expressed in terms of the angle of arrival between the desired and interfering signals is below a certain threshold, a linear beamformer would fail to separate them, while a nonlinear detection assisted receiver is still capable of performing adequately. The adaptive implementation of the optimal Bayesian detector can be realized using a radial basis function network. Two techniques are presented for constructing block-data-based adaptive nonlinear multiple-antenna assisted receivers. One of them is based on the relevance vector machine invoked for classification, while the other on the orthogonal forward selection procedure combined with the Fisher ratio class-separability measure. A recursive sample-by-sample adaptation procedure is also proposed for training nonlinear detectors based on an amalgam of enhanced -means clustering techniques and the recursive least squares algorithm.
Indian Academy of Sciences (India)
ticians but also forms the foundation of computer science. Two ... with methods of developing algorithms for solving a variety of problems but ... applications of computers in science and engineer- ... numerical calculus are as important. We will ...
Directory of Open Access Journals (Sweden)
Ye. V. Dmitriev
2007-01-01
Full Text Available Analysis of the Over-Voltage Limiter (OVL influence on electromagnetic high-frequency over-voltages at commutations with isolators of unloaded sections of wires and possibility of application of a frequency-dependent resistor in case of necessity to facilitate OVL operation conditions is provided in the paper.It is shown that it is necessary to take into account characteristics of OVL by IEEE circuit and its modifications at computer modeling of high-frequency over-voltages.
CHAM: a fast algorithm of modelling non-linear matter power spectrum in the sCreened HAlo Model
Hu, Bin; Liu, Xue-Wen; Cai, Rong-Gen
2018-05-01
We present a fast numerical screened halo model algorithm (CHAM, which stands for the sCreened HAlo Model) for modelling non-linear power spectrum for the alternative models to Λ cold dark matter. This method has three obvious advantages. First of all, it is not being restricted to a specific dark energy/modified gravity model. In principle, all of the screened scalar-tensor theories can be applied. Secondly, the least assumptions are made in the calculation. Hence, the physical picture is very easily understandable. Thirdly, it is very predictable and does not rely on the calibration from N-body simulation. As an example, we show the case of the Hu-Sawicki f(R) gravity. In this case, the typical CPU time with the current parallel PYTHON script (eight threads) is roughly within 10 min. The resulting spectra are in a good agreement with N-body data within a few percentage accuracy up to k ˜ 1 h Mpc-1.
Indian Academy of Sciences (India)
algorithm design technique called 'divide-and-conquer'. One of ... Turtle graphics, September. 1996. 5. ... whole list named 'PO' is a pointer to the first element of the list; ..... Program for computing matrices X and Y and placing the result in C *).
Indian Academy of Sciences (India)
algorithm that it is implicitly understood that we know how to generate the next natural ..... Explicit comparisons are made in line (1) where maximum and minimum is ... It can be shown that the function T(n) = 3/2n -2 is the solution to the above ...
Ren, Pengyu; Li, Bowen; Dong, Shiyao; Chen, Lin; Zhang, Yuelin
2018-01-01
Although many mathematical methods were used to analyze the neural activity under sinusoidal stimulation within linear response range in vestibular system, the reliabilities of these methods are still not reported, especially in nonlinear response range. Here we chose nonlinear least-squares algorithm (NLSA) with sinusoidal model to analyze the neural response of semicircular canal neurons (SCNs) during sinusoidal rotational stimulation (SRS) over a nonlinear response range. Our aim was to acquire a reliable mathematical method for data analysis under SRS in vestibular system. Our data indicated that the reliability of this method in an entire SCNs population was quite satisfactory. However, the reliability was strongly negatively depended on the neural discharge regularity. In addition, stimulation parameters were the vital impact factors influencing the reliability. The frequency had a significant negative effect but the amplitude had a conspicuous positive effect on the reliability. Thus, NLSA with sinusoidal model resulted a reliable mathematical tool for data analysis of neural response activity under SRS in vestibular system and more suitable for those under the stimulation with low frequency but high amplitude, suggesting that this method can be used in nonlinear response range. This method broke out of the restriction of neural activity analysis under nonlinear response range and provided a solid foundation for future study in nonlinear response range in vestibular system.
Explicit field realizations of W algebras
International Nuclear Information System (INIS)
Wei Shaowen; Liu Yuxiao; Ren Jirong; Zhang Lijie
2009-01-01
The fact that certain nonlinear W 2,s algebras can be linearized by the inclusion of a spin-1 current can provide a simple way to realize W 2,s algebras from linear W 1,2,s algebras. In this paper, we first construct the explicit field realizations of linear W 1,2,s algebras with double scalar and double spinor, respectively. Then, after a change of basis, the realizations of W 2,s algebras are presented. The results show that all these realizations are Romans-type realizations.
Explicit field realizations of W algebras
Wei, Shao-Wen; Liu, Yu-Xiao; Zhang, Li-Jie; Ren, Ji-Rong
2009-01-01
The fact that certain non-linear $W_{2,s}$ algebras can be linearized by the inclusion of a spin-1 current can provide a simple way to realize $W_{2,s}$ algebras from linear $W_{1,2,s}$ algebras. In this paper, we first construct the explicit field realizations of linear $W_{1,2,s}$ algebras with double-scalar and double-spinor, respectively. Then, after a change of basis, the realizations of $W_{2,s}$ algebras are presented. The results show that all these realizations are Romans-type realiz...
Non-Linear Back-propagation: Doing Back-Propagation withoutDerivatives of the Activation Function
DEFF Research Database (Denmark)
Hertz, John; Krogh, Anders Stærmose; Lautrup, Benny
1997-01-01
The conventional linear back-propagation algorithm is replaced by a non-linear version, which avoids the necessity for calculating the derivative of the activation function. This may be exploited in hardware realizations of neural processors. In this paper we derive the non-linear back...
Directory of Open Access Journals (Sweden)
Marwa Jouini
2017-01-01
Full Text Available This paper proposes a robust supertwisting algorithm (STA design for nonlinear systems where both matched and unmatched uncertainties are considered. The main contributions reside primarily to conceive a novel structure of STA, in order to ensure the desired performance of the uncertain nonlinear system. The modified algorithm is formed of double closed-loop feedback, in which two linear terms are added to the classical STA. In addition, an integral sliding mode switching surface is proposed to construct the attractiveness and reachability of sliding mode. Sufficient conditions are derived to guarantee the exact differentiation stability in finite time based on Lyapunov function theory. Finally, a comparative study for a variable-length pendulum system illustrates the robustness and the effectiveness of the proposed approach compared to other STA schemes.
Milic, Vladimir; Kasac, Josip; Novakovic, Branko
2015-10-01
This paper is concerned with ?-gain optimisation of input-affine nonlinear systems controlled by analytic fuzzy logic system. Unlike the conventional fuzzy-based strategies, the non-conventional analytic fuzzy control method does not require an explicit fuzzy rule base. As the first contribution of this paper, we prove, by using the Stone-Weierstrass theorem, that the proposed fuzzy system without rule base is universal approximator. The second contribution of this paper is an algorithm for solving a finite-horizon minimax problem for ?-gain optimisation. The proposed algorithm consists of recursive chain rule for first- and second-order derivatives, Newton's method, multi-step Adams method and automatic differentiation. Finally, the results of this paper are evaluated on a second-order nonlinear system.
Indian Academy of Sciences (India)
will become clear in the next article when we discuss a simple logo like programming language. ... Rod B may be used as an auxiliary store. The problem is to find an algorithm which performs this task. ... No disks are moved from A to Busing C as auxiliary rod. • move _disk (A, C);. (No + l)th disk is moved from A to C directly ...
Chow, Sy-Miin; Lu, Zhaohua; Sherwood, Andrew; Zhu, Hongtu
2016-03-01
The past decade has evidenced the increased prevalence of irregularly spaced longitudinal data in social sciences. Clearly lacking, however, are modeling tools that allow researchers to fit dynamic models to irregularly spaced data, particularly data that show nonlinearity and heterogeneity in dynamical structures. We consider the issue of fitting multivariate nonlinear differential equation models with random effects and unknown initial conditions to irregularly spaced data. A stochastic approximation expectation-maximization algorithm is proposed and its performance is evaluated using a benchmark nonlinear dynamical systems model, namely, the Van der Pol oscillator equations. The empirical utility of the proposed technique is illustrated using a set of 24-h ambulatory cardiovascular data from 168 men and women. Pertinent methodological challenges and unresolved issues are discussed.
DEFF Research Database (Denmark)
Rubæk, Tonny; Meaney, P. M.; Meincke, Peter
2007-01-01
is presented which is based on the conjugate gradient least squares (CGLS) algorithm. The iterative CGLS algorithm is capable of solving the update problem by operating on just the Jacobian and the regularizing effects of the algorithm can easily be controlled by adjusting the number of iterations. The new...
Hariharan, M; Sindhu, R; Vijean, Vikneswaran; Yazid, Haniza; Nadarajaw, Thiyagar; Yaacob, Sazali; Polat, Kemal
2018-03-01
Infant cry signal carries several levels of information about the reason for crying (hunger, pain, sleepiness and discomfort) or the pathological status (asphyxia, deaf, jaundice, premature condition and autism, etc.) of an infant and therefore suited for early diagnosis. In this work, combination of wavelet packet based features and Improved Binary Dragonfly Optimization based feature selection method was proposed to classify the different types of infant cry signals. Cry signals from 2 different databases were utilized. First database contains 507 cry samples of normal (N), 340 cry samples of asphyxia (A), 879 cry samples of deaf (D), 350 cry samples of hungry (H) and 192 cry samples of pain (P). Second database contains 513 cry samples of jaundice (J), 531 samples of premature (Prem) and 45 samples of normal (N). Wavelet packet transform based energy and non-linear entropies (496 features), Linear Predictive Coding (LPC) based cepstral features (56 features), Mel-frequency Cepstral Coefficients (MFCCs) were extracted (16 features). The combined feature set consists of 568 features. To overcome the curse of dimensionality issue, improved binary dragonfly optimization algorithm (IBDFO) was proposed to select the most salient attributes or features. Finally, Extreme Learning Machine (ELM) kernel classifier was used to classify the different types of infant cry signals using all the features and highly informative features as well. Several experiments of two-class and multi-class classification of cry signals were conducted. In binary or two-class experiments, maximum accuracy of 90.18% for H Vs P, 100% for A Vs N, 100% for D Vs N and 97.61% J Vs Prem was achieved using the features selected (only 204 features out of 568) by IBDFO. For the classification of multiple cry signals (multi-class problem), the selected features could differentiate between three classes (N, A & D) with the accuracy of 100% and seven classes with the accuracy of 97.62%. The experimental
Directory of Open Access Journals (Sweden)
Aliasghar Baziar
2015-03-01
Full Text Available Abstract In order to handle large scale problems this study has used shuffled frog leaping algorithm. This algorithm is an optimization method based on natural memetics that uses a new two-phase modification to it to have a better search in the problem space. The suggested algorithm is evaluated by comparing to some well known algorithms using several benchmark optimization problems. The simulation results have clearly shown the superiority of this algorithm over other well-known methods in the area.
International Nuclear Information System (INIS)
Zhong Jian; Dong Gang; Sun Yimei; Zhang Zhaoyang; Wu Yuqin
2016-01-01
The present work reports the development of nonlinear time series prediction method of genetic algorithm (GA) with singular spectrum analysis (SSA) for forecasting the surface wind of a point station in the South China Sea (SCS) with scatterometer observations. Before the nonlinear technique GA is used for forecasting the time series of surface wind, the SSA is applied to reduce the noise. The surface wind speed and surface wind components from scatterometer observations at three locations in the SCS have been used to develop and test the technique. The predictions have been compared with persistence forecasts in terms of root mean square error. The predicted surface wind with GA and SSA made up to four days (longer for some point station) in advance have been found to be significantly superior to those made by persistence model. This method can serve as a cost-effective alternate prediction technique for forecasting surface wind of a point station in the SCS basin. (paper)
International Nuclear Information System (INIS)
Banerjee, Amit; Abu-Mahfouz, Issam
2014-01-01
The use of evolutionary algorithms has been popular in recent years for solving the inverse problem of identifying system parameters given the chaotic response of a dynamical system. The inverse problem is reformulated as a minimization problem and population-based optimizers such as evolutionary algorithms have been shown to be efficient solvers of the minimization problem. However, to the best of our knowledge, there has been no published work that evaluates the efficacy of using the two most popular evolutionary techniques – particle swarm optimization and differential evolution algorithm, on a wide range of parameter estimation problems. In this paper, the two methods along with their variants (for a total of seven algorithms) are applied to fifteen different parameter estimation problems of varying degrees of complexity. Estimation results are analyzed using nonparametric statistical methods to identify if an algorithm is statistically superior to others over the class of problems analyzed. Results based on parameter estimation quality suggest that there are significant differences between the algorithms with the newer, more sophisticated algorithms performing better than their canonical versions. More importantly, significant differences were also found among variants of the particle swarm optimizer and the best performing differential evolution algorithm
El-Qulity, Said Ali; Mohamed, Ali Wagdy
2016-01-01
This paper proposes a nonlinear integer goal programming model (NIGPM) for solving the general problem of admission capacity planning in a country as a whole. The work aims to satisfy most of the required key objectives of a country related to the enrollment problem for higher education. The system general outlines are developed along with the solution methodology for application to the time horizon in a given plan. The up-to-date data for Saudi Arabia is used as a case study and a novel evolutionary algorithm based on modified differential evolution (DE) algorithm is used to solve the complexity of the NIGPM generated for different goal priorities. The experimental results presented in this paper show their effectiveness in solving the admission capacity for higher education in terms of final solution quality and robustness.
Wang, Jun; Zhou, Bi-hua; Zhou, Shu-dao; Sheng, Zheng
2015-01-01
The paper proposes a novel function expression method to forecast chaotic time series, using an improved genetic-simulated annealing (IGSA) algorithm to establish the optimum function expression that describes the behavior of time series. In order to deal with the weakness associated with the genetic algorithm, the proposed algorithm incorporates the simulated annealing operation which has the strong local search ability into the genetic algorithm to enhance the performance of optimization; besides, the fitness function and genetic operators are also improved. Finally, the method is applied to the chaotic time series of Quadratic and Rossler maps for validation. The effect of noise in the chaotic time series is also studied numerically. The numerical results verify that the method can forecast chaotic time series with high precision and effectiveness, and the forecasting precision with certain noise is also satisfactory. It can be concluded that the IGSA algorithm is energy-efficient and superior.
Dreano, Denis; Tandeo, P.; Pulido, M.; Ait-El-Fquih, Boujemaa; Chonavel, T.; Hoteit, Ibrahim
2017-01-01
Specification and tuning of errors from dynamical models are important issues in data assimilation. In this work, we propose an iterative expectation-maximisation (EM) algorithm to estimate the model error covariances using classical extended
Observation of the state of the nuclear reactor core by means of non-linear observation algorithms
International Nuclear Information System (INIS)
Maciel Palacio, F.E.; Espana, M.D.
1990-01-01
A combined, variable-adaptive structure, non-linear observer was designed in order to observe the state of the nuclear reactor core, based on the Absolute Stability Theory. The observer was proved under noise and modelling error conditions. Successful results were obtained in the observation of the states in both cases, showing clear improvement in the observation due to the application of adaptive and variable structure ideas. (Author) [es
Alvarez, Diego A.; Hurtado, Jorge E.; Bedoya-Ruíz, Daniel Alveiro
2012-07-01
Despite technological advances in seismic instrumentation, the assessment of the intensity of an earthquake using an observational scale as given, for example, by the modified Mercalli intensity scale is highly useful for practical purposes. In order to link the qualitative numbers extracted from the acceleration record of an earthquake and other instrumental data such as peak ground velocity, epicentral distance, and moment magnitude on the one hand and the modified Mercalli intensity scale on the other, simple statistical regression has been generally employed. In this paper, we will employ three methods of nonlinear regression, namely support vector regression, multilayer perceptrons, and genetic programming in order to find a functional dependence between the instrumental records and the modified Mercalli intensity scale. The proposed methods predict the intensity of an earthquake while dealing with nonlinearity and the noise inherent to the data. The nonlinear regressions with good estimation results have been performed using the "Did You Feel It?" database of the US Geological Survey and the database of the Center for Engineering Strong Motion Data for the California region.
Directory of Open Access Journals (Sweden)
Eusebio Eduardo Hernández Martinez
2013-01-01
Full Text Available In robotics, solving the direct kinematics problem (DKP for parallel robots is very often more difficult and time consuming than for their serial counterparts. The problem is stated as follows: given the joint variables, the Cartesian variables should be computed, namely the pose of the mobile platform. Most of the time, the DKP requires solving a non-linear system of equations. In addition, given that the system could be non-convex, Newton or Quasi-Newton (Dogleg based solvers get trapped on local minima. The capacity of such kinds of solvers to find an adequate solution strongly depends on the starting point. A well-known problem is the selection of such a starting point, which requires a priori information about the neighbouring region of the solution. In order to circumvent this issue, this article proposes an efficient method to select and to generate the starting point based on probabilistic learning. Experiments and discussion are presented to show the method performance. The method successfully avoids getting trapped on local minima without the need for human intervention, which increases its robustness when compared with a single Dogleg approach. This proposal can be extended to other structures, to any non-linear system of equations, and of course, to non-linear optimization problems.
Directory of Open Access Journals (Sweden)
Chouaib Labiod
2017-01-01
Full Text Available This paper presents torque ripple reduction with speed control of 8/6 Switched Reluctance Motor (SRM by the determination of the optimal parameters of the turn on, turn off angles Theta_(on, Theta_(off, and the supply voltage using Particle Swarm Optimization (PSO algorithm and steady state Genetic Algorithm (ssGA. With SRM model, there is difficulty in the control relapsed into highly non-linear static characteristics. For this, the Finite Elements Method (FEM has been used because it is a powerful tool to get a model closer to reality. The mechanism used in this kind of machine control consists of a speed controller in order to determine current reference which must be produced to get the desired speed, hence, hysteresis controller is used to compare current reference with current measured up to achieve switching signals needed in the inverter. Depending on this control, the intelligent routing algorithms get the fitness equation from torque ripple and speed response so as to give the optimal parameters for better results. Obtained results from the proposed strategy based on metaheuristic methods are compared with the basic case without considering the adjustment of specific parameters. Optimized results found clearly confirmed the ability and the efficiency of the proposed strategy based on metaheuristic methods in improving the performances of the SRM control considering different torque loads.
Realizability: a historical essay
Oosten, J. van
2000-01-01
The purpose of this short paper is to sketch the development of a few basic topics in the history of Realizability The number of topics is quite limited and reects very much my own personal taste biases and prejudices Realizability has over the past years developed into a subject of such dimensions
D.E. Allen (David); M.J. McAleer (Michael); M. Scharth (Marcel)
2013-01-01
textabstractIn this paper we document that realized variation measures constructed from highfrequency returns reveal a large degree of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting errors in realized volatility are substantive.
Asymmetric Realized Volatility Risk
D.E. Allen (David); M.J. McAleer (Michael); M. Scharth (Marcel)
2014-01-01
markdownabstract__Abstract__ In this paper we document that realized variation measures constructed from high-frequency returns reveal a large degree of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting errors in realized
Yang, Qin; Zou, Hong-Yan; Zhang, Yan; Tang, Li-Juan; Shen, Guo-Li; Jiang, Jian-Hui; Yu, Ru-Qin
2016-01-15
Most of the proteins locate more than one organelle in a cell. Unmixing the localization patterns of proteins is critical for understanding the protein functions and other vital cellular processes. Herein, non-linear machine learning technique is proposed for the first time upon protein pattern unmixing. Variable-weighted support vector machine (VW-SVM) is a demonstrated robust modeling technique with flexible and rational variable selection. As optimized by a global stochastic optimization technique, particle swarm optimization (PSO) algorithm, it makes VW-SVM to be an adaptive parameter-free method for automated unmixing of protein subcellular patterns. Results obtained by pattern unmixing of a set of fluorescence microscope images of cells indicate VW-SVM as optimized by PSO is able to extract useful pattern features by optimally rescaling each variable for non-linear SVM modeling, consequently leading to improved performances in multiplex protein pattern unmixing compared with conventional SVM and other exiting pattern unmixing methods. Copyright © 2015 Elsevier B.V. All rights reserved.
Asymmetric Realized Volatility Risk
Directory of Open Access Journals (Sweden)
David E. Allen
2014-06-01
Full Text Available In this paper, we document that realized variation measures constructed from high-frequency returns reveal a large degree of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting errors in realized volatility are substantive. Even though returns standardized by ex post quadratic variation measures are nearly Gaussian, this unpredictability brings considerably more uncertainty to the empirically relevant ex ante distribution of returns. Explicitly modeling this volatility risk is fundamental. We propose a dually asymmetric realized volatility model, which incorporates the fact that realized volatility series are systematically more volatile in high volatility periods. Returns in this framework display time varying volatility, skewness and kurtosis. We provide a detailed account of the empirical advantages of the model using data on the S&P 500 index and eight other indexes and stocks.
Department of Veterans Affairs — This dataset is provided as a requirement of OMB’s Integrated Data Collection (IDC) and links to VA’s Realized Cost Savings and Avoidances data in JSON format. Cost...
International Nuclear Information System (INIS)
1986-01-01
Most typical papers on the Ganil construction have been gathered in this book to somehow notice the success of its realization. Papers concern the accelerator and beam line, excluding experimental areas
Yu, Xuefei; Lin, Liangzhuo; Shen, Jie; Chen, Zhi; Jian, Jun; Li, Bin; Xin, Sherman Xuegang
2018-01-01
The mean amplitude of glycemic excursions (MAGE) is an essential index for glycemic variability assessment, which is treated as a key reference for blood glucose controlling at clinic. However, the traditional "ruler and pencil" manual method for the calculation of MAGE is time-consuming and prone to error due to the huge data size, making the development of robust computer-aided program an urgent requirement. Although several software products are available instead of manual calculation, poor agreement among them is reported. Therefore, more studies are required in this field. In this paper, we developed a mathematical algorithm based on integer nonlinear programming. Following the proposed mathematical method, an open-code computer program named MAGECAA v1.0 was developed and validated. The results of the statistical analysis indicated that the developed program was robust compared to the manual method. The agreement among the developed program and currently available popular software is satisfied, indicating that the worry about the disagreement among different software products is not necessary. The open-code programmable algorithm is an extra resource for those peers who are interested in the related study on methodology in the future.
Li, Liang; Jia, Gang; Chen, Jie; Zhu, Hongjun; Cao, Dongpu; Song, Jian
2015-08-01
Direct yaw moment control (DYC), which differentially brakes the wheels to produce a yaw moment for the vehicle stability in a steering process, is an important part of electric stability control system. In this field, most control methods utilise the active brake pressure with a feedback controller to adjust the braked wheel. However, the method might lead to a control delay or overshoot because of the lack of a quantitative project relationship between target values from the upper stability controller to the lower pressure controller. Meanwhile, the stability controller usually ignores the implementing ability of the tyre forces, which might be restrained by the combined-slip dynamics of the tyre. Therefore, a novel control algorithm of DYC based on the hierarchical control strategy is brought forward in this paper. As for the upper controller, a correctional linear quadratic regulator, which not only contains feedback control but also contains feed forward control, is introduced to deduce the object of the stability yaw moment in order to guarantee the yaw rate and side-slip angle stability. As for the medium and lower controller, the quantitative relationship between the vehicle stability object and the target tyre forces of controlled wheels is proposed to achieve smooth control performance based on a combined-slip tyre model. The simulations with the hardware-in-the-loop platform validate that the proposed algorithm can improve the stability of the vehicle effectively.
Mohebbi, Akbar
2018-02-01
In this paper we propose two fast and accurate numerical methods for the solution of multidimensional space fractional Ginzburg-Landau equation (FGLE). In the presented methods, to avoid solving a nonlinear system of algebraic equations and to increase the accuracy and efficiency of method, we split the complex problem into simpler sub-problems using the split-step idea. For a homogeneous FGLE, we propose a method which has fourth-order of accuracy in time component and spectral accuracy in space variable and for nonhomogeneous one, we introduce another scheme based on the Crank-Nicolson approach which has second-order of accuracy in time variable. Due to using the Fourier spectral method for fractional Laplacian operator, the resulting schemes are fully diagonal and easy to code. Numerical results are reported in terms of accuracy, computational order and CPU time to demonstrate the accuracy and efficiency of the proposed methods and to compare the results with the analytical solutions. The results show that the present methods are accurate and require low CPU time. It is illustrated that the numerical results are in good agreement with the theoretical ones.
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole Eiler; Hansen, P. Reinhard; Lunde, Asger
2009-01-01
and find a remarkable level of agreement. We identify some features of the high-frequency data, which are challenging for realized kernels. They are when there are local trends in the data, over periods of around 10 minutes, where the prices and quotes are driven up or down. These can be associated......Realized kernels use high-frequency data to estimate daily volatility of individual stock prices. They can be applied to either trade or quote data. Here we provide the details of how we suggest implementing them in practice. We compare the estimates based on trade and quote data for the same stock...
Modeling returns volatility: Realized GARCH incorporating realized risk measure
Jiang, Wei; Ruan, Qingsong; Li, Jianfeng; Li, Ye
2018-06-01
This study applies realized GARCH models by introducing several risk measures of intraday returns into the measurement equation, to model the daily volatility of E-mini S&P 500 index futures returns. Besides using the conventional realized measures, realized volatility and realized kernel as our benchmarks, we also use generalized realized risk measures, realized absolute deviation, and two realized tail risk measures, realized value-at-risk and realized expected shortfall. The empirical results show that realized GARCH models using the generalized realized risk measures provide better volatility estimation for the in-sample and substantial improvement in volatility forecasting for the out-of-sample. In particular, the realized expected shortfall performs best for all of the alternative realized measures. Our empirical results reveal that future volatility may be more attributable to present losses (risk measures). The results are robust to different sample estimation windows.
Rajasekar, Shanmuganathan
2016-01-01
This introductory text presents the basic aspects and most important features of various types of resonances and anti-resonances in dynamical systems. In particular, for each resonance, it covers the theoretical concepts, illustrates them with case studies, and reviews the available information on mechanisms, characterization, numerical simulations, experimental realizations, possible quantum analogues, applications and significant advances made over the years. Resonances are one of the most fundamental phenomena exhibited by nonlinear systems and refer to specific realizations of maximum response of a system due to the ability of that system to store and transfer energy received from an external forcing source. Resonances are of particular importance in physical, engineering and biological systems - they can prove to be advantageous in many applications, while leading to instability and even disasters in others. The book is self-contained, providing the details of mathematical derivations and techniques invo...
Perfect lensing with phase-conjugating surfaces: toward practical realization
International Nuclear Information System (INIS)
Maslovski, Stanislav; Tretyakov, Sergei
2012-01-01
It is theoretically known that a pair of phase-conjugating surfaces can function as a perfect lens, focusing propagating waves and enhancing evanescent waves. However, the known experimental approaches based on thin sheets of nonlinear materials cannot fully realize the required phase conjugation boundary condition. In this paper, we show that the ideal phase-conjugating surface is, in principle, physically realizable and investigate the necessary properties of nonlinear and nonreciprocal particles which can be used to build a perfect lens system. The physical principle of the lens operation is discussed in detail and directions of possible experimental realizations are outlined. (paper)
Baxstrom, Richard; Meyers, Todd
2016-01-01
Benjamin Christensen’s Häxan (The Witch, 1922) stands as a singular film within the history of cinema. Deftly weaving contemporary scientific analysis and powerfully staged historical scenes of satanic initiation, confession under torture, possession, and persecution, Häxan creatively blends spectacle and argument to provoke a humanist re-evaluation of witchcraft in European history as well as the contemporary treatment of female “hysterics” and the mentally ill. In Realizing the Witch, Baxst...
Directory of Open Access Journals (Sweden)
Franz Konstantin Fuss
2013-01-01
Full Text Available Standard methods for computing the fractal dimensions of time series are usually tested with continuous nowhere differentiable functions, but not benchmarked with actual signals. Therefore they can produce opposite results in extreme signals. These methods also use different scaling methods, that is, different amplitude multipliers, which makes it difficult to compare fractal dimensions obtained from different methods. The purpose of this research was to develop an optimisation method that computes the fractal dimension of a normalised (dimensionless and modified time series signal with a robust algorithm and a running average method, and that maximises the difference between two fractal dimensions, for example, a minimum and a maximum one. The signal is modified by transforming its amplitude by a multiplier, which has a non-linear effect on the signal’s time derivative. The optimisation method identifies the optimal multiplier of the normalised amplitude for targeted decision making based on fractal dimensions. The optimisation method provides an additional filter effect and makes the fractal dimensions less noisy. The method is exemplified by, and explained with, different signals, such as human movement, EEG, and acoustic signals.
Fuss, Franz Konstantin
2013-01-01
Standard methods for computing the fractal dimensions of time series are usually tested with continuous nowhere differentiable functions, but not benchmarked with actual signals. Therefore they can produce opposite results in extreme signals. These methods also use different scaling methods, that is, different amplitude multipliers, which makes it difficult to compare fractal dimensions obtained from different methods. The purpose of this research was to develop an optimisation method that computes the fractal dimension of a normalised (dimensionless) and modified time series signal with a robust algorithm and a running average method, and that maximises the difference between two fractal dimensions, for example, a minimum and a maximum one. The signal is modified by transforming its amplitude by a multiplier, which has a non-linear effect on the signal's time derivative. The optimisation method identifies the optimal multiplier of the normalised amplitude for targeted decision making based on fractal dimensions. The optimisation method provides an additional filter effect and makes the fractal dimensions less noisy. The method is exemplified by, and explained with, different signals, such as human movement, EEG, and acoustic signals.
Realization theory for rational systems: Minimal rational realizations
J. Nemcová (Jana); J.H. van Schuppen (Jan)
2010-01-01
htmlabstractThe study of realizations of response maps is a topic of control and system theory. Realization theory is used in system identification and control synthesis. A minimal rational realization of a given response map p is a rational realization of p such that the dimension of its state
International Nuclear Information System (INIS)
Albrecht, A.; Brandenberger, R.H.
1985-01-01
We examine cosmological phase transitions using a new approach and argue that there are many models in which the universe enters a period of exponential expansion required for an inflationary cosmology. A sufficient condition is that the interaction rates due to quantum field nonlinearities be sufficiently small compared to the expansion rate of the universe. In Coleman-Weinberg-type models this requires tuning the gauge coupling constant to a low value. In pure scalar field theories, the conditions for inflation are satisfied if the scale of symmetry breaking is of the order of the Planck scale
Concurrency in product realization
Kelly, Michael J.
1994-03-01
Technology per se does not provide a competitive advantage. Timely exploitation of technology is what gives the competitive edge, and this demands a major shift in the product development process and management of the industrial enterprise. `Teaming to win' is more than a management theme; it is the disciplined engineering practice that is essential to success in today's global marketplace. Teaming supports the concurrent engineering practices required to integrate the activities of people responsible for product realization through achievement of shorter development cycles, lower costs, and defect-free products.
Novel procedure for characterizing nonlinear systems with memory: 2017 update
Nuttall, Albert H.; Katz, Richard A.; Hughes, Derke R.; Koch, Robert M.
2017-05-01
The present article discusses novel improvements in nonlinear signal processing made by the prime algorithm developer, Dr. Albert H. Nuttall and co-authors, a consortium of research scientists from the Naval Undersea Warfare Center Division, Newport, RI. The algorithm, called the Nuttall-Wiener-Volterra or 'NWV' algorithm is named for its principal contributors [1], [2],[ 3] . The NWV algorithm significantly reduces the computational workload for characterizing nonlinear systems with memory. Following this formulation, two measurement waveforms are required in order to characterize a specified nonlinear system under consideration: (1) an excitation input waveform, x(t) (the transmitted signal); and, (2) a response output waveform, z(t) (the received signal). Given these two measurement waveforms for a given propagation channel, a 'kernel' or 'channel response', h= [h0,h1,h2,h3] between the two measurement points, is computed via a least squares approach that optimizes modeled kernel values by performing a best fit between measured response z(t) and a modeled response y(t). New techniques significantly diminish the exponential growth of the number of computed kernel coefficients at second and third order and alleviate the Curse of Dimensionality (COD) in order to realize practical nonlinear solutions of scientific and engineering interest.
International Nuclear Information System (INIS)
Chang, Jonghwa
2015-01-01
High temperature gas cooled reactor has been developed since 1956. Fundamental idea of a gas cooled reactor is to achieve high temperature which is suitable for high efficiency application such as electricity generation. The core is composed of ceramics, graphite blocks which are mechanical stable up to very high temperature. Fuel is ceramics, TRISO ( tri-isotropic coated micro particle) whose dense coating layers work as small radioactivity containment. Coolant is inert gas, helium, which is stable chemically, neutronically, and thermal hydraulically. Several test reactors such as DRE, PB-1, FSV, AVR, THTR, HTTR, HTR-10 were built and demonstrated their safety. Large GA-HTR, RSA-PBMR projects are canceled and US-NGNP project is idling. Only Chinese HTR-PM demonstrator is under construction. HTGR has long history of development. For realization and market penetration, VHTR community should look at niche market such as carbon free energy supply to industry complex, electric power for small grid, carbon free hydrogen production, power source for space colony. Technology Readiness Level should be advanced to get proper investment from industry. For this, cooperation between international R and D institutions is required. Clearly divided role between universities, research institutions, and industries will reduce complication and shorten VHTR realization day
Energy Technology Data Exchange (ETDEWEB)
Chang, Jonghwa [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)
2015-10-15
High temperature gas cooled reactor has been developed since 1956. Fundamental idea of a gas cooled reactor is to achieve high temperature which is suitable for high efficiency application such as electricity generation. The core is composed of ceramics, graphite blocks which are mechanical stable up to very high temperature. Fuel is ceramics, TRISO ( tri-isotropic coated micro particle) whose dense coating layers work as small radioactivity containment. Coolant is inert gas, helium, which is stable chemically, neutronically, and thermal hydraulically. Several test reactors such as DRE, PB-1, FSV, AVR, THTR, HTTR, HTR-10 were built and demonstrated their safety. Large GA-HTR, RSA-PBMR projects are canceled and US-NGNP project is idling. Only Chinese HTR-PM demonstrator is under construction. HTGR has long history of development. For realization and market penetration, VHTR community should look at niche market such as carbon free energy supply to industry complex, electric power for small grid, carbon free hydrogen production, power source for space colony. Technology Readiness Level should be advanced to get proper investment from industry. For this, cooperation between international R and D institutions is required. Clearly divided role between universities, research institutions, and industries will reduce complication and shorten VHTR realization day.
Nonlinear transport of dynamic system phase space
International Nuclear Information System (INIS)
Xie Xi; Xia Jiawen
1993-01-01
The inverse transform of any order solution of the differential equation of general nonlinear dynamic systems is derived, realizing theoretically the nonlinear transport for the phase space of nonlinear dynamic systems. The result is applicable to general nonlinear dynamic systems, with the transport of accelerator beam phase space as a typical example
Energy Technology Data Exchange (ETDEWEB)
Toselli, G. [ENEA, Centro Ricerche Ezio Clementel, Bologna, (Italy). Dipt. Innovazione; Mirco, A. M. [Bologna Univ., Bologna (Italy). Dipt. di Matematica
1999-07-01
In this technical report the thesis of doctor's degree in Mathematics of A.M. Mirco is reported; it has been developed at ENEA research centre 'E. Clementel' in Bologna (Italy) in the frame of a collaboration between the section MACO (Applied Physics Division - Innovation Department) of ENEA at Bologna and the Department of Mathematics of the mathematical, physical and natural sciences faculty of Bologna University. Substantially, studies and research work, developed in these last years at MACO section, are here presented; they have led to the development of a constitutive model, based on Hill potential theory, for the treatment, in plastic field, of metal material anisotropy induced by previous workings and to the construction of the corresponding FEM algorithm for the non-linear structural analysis NOSA, oriented in particular to the numerical simulation of metal forming. Subsequently, an algorithm extension (proper object of the thesis), which has given, beyond a more rigorous formalization, also significant improvements. [Italian] In questo rapporto tecnico viene riportata la tesi di laurea in matematica di A. M. Mirco, tesi svolta presso il centro ricerche E. Clementel dell'ENEA di Bologna nell'ambito di un accordo di collaborazione fra la sezione MACO (Divisione Fisica Applicata - Dipartimento di Innovazione) dell'ENEA di Bologna ed il Dipartimento di matematica della facolta' di scienze matematiche, fisiche e naturali dell'universita' degli studi di Bologna. Sostanzialmente, vengono presentati gli studi ed il lavoro di ricerca, svolti in questi ultimi anni presso la sezione MACO, che hanno portato allo sviluppo di un modello costitutivo, basato sulla teoria del potenziale di Hill, per il trattamento in campo plastico, dell'anisotropia indotta da lavorazioni precedenti per un materiale metallico ed alla costruzione del corrispondente algoritmo basato sul metodo degli elementi finiti per il codice di analisi
Realization of chiral symmetry in the ERG
International Nuclear Information System (INIS)
Echigo, Yoshio; Igarashi, Yuji
2011-01-01
We discuss within the framework of the ERG how chiral symmetry is realized in a linear σ model. A generalized Ginsparg-Wilson relation is obtained from the Ward-Takahashi identities for the Wilson action assumed to be bilinear in the Dirac fields. We construct a family of its non-perturbative solutions. The family generates the most general solutions to the Ward-Takahashi identities. Some special solutions are discussed. For each solution in this family, chiral symmetry is realized in such a way that a change in the Wilson action under non-linear symmetry transformation is canceled with a change in the functional measure. We discuss that the family of solutions reduces via a field redefinition to a family of the Wilson actions with some composite object of the scalar fields which has a simple transformation property. For this family, chiral symmetry is linearly realized with a continuum analog of the operator extension of γ 5 used on the lattice. We also show that there exist some appropriate Dirac fields which obey the standard chiral transformations with γ 5 in contrast to the lattice case. Their Yukawa interaction with scalars, however, becomes non-linear. (author)
Digital Fractional Order Controllers Realized by PIC Microprocessor: Experimental Results
Petras, I.; Grega, S.; Dorcak, L.
2003-01-01
This paper deals with the fractional-order controllers and their possible hardware realization based on PIC microprocessor and numerical algorithm coded in PIC Basic. The mathematical description of the digital fractional -order controllers and approximation in the discrete domain are presented. An example of realization of the particular case of digital fractional-order PID controller is shown and described.
A Developed ESPRIT Algorithm for DOA Estimation
Fayad, Youssef; Wang, Caiyun; Cao, Qunsheng; Hafez, Alaa El-Din Sayed
2015-05-01
A novel algorithm for estimating direction of arrival (DOAE) for target, which aspires to contribute to increase the estimation process accuracy and decrease the calculation costs, has been carried out. It has introduced time and space multiresolution in Estimation of Signal Parameter via Rotation Invariance Techniques (ESPRIT) method (TS-ESPRIT) to realize subspace approach that decreases errors caused by the model's nonlinearity effect. The efficacy of the proposed algorithm is verified by using Monte Carlo simulation, the DOAE accuracy has evaluated by closed-form Cramér-Rao bound (CRB) which reveals that the proposed algorithm's estimated results are better than those of the normal ESPRIT methods leading to the estimator performance enhancement.
On the algebraic realization of SU(4) symmetry
International Nuclear Information System (INIS)
Asatryan, G.M.; Zaslavsky, A.N.
1976-01-01
A possibility of nonlinear realization of the symmetry with linearization on the SU(4)xYxC group is discussed. Algebraic properties of SU(4) are restored from the Weinberg condition: amplitudes of goldstone scattering on particles should have a reasonable (as in the Regge theory) asymptotic behaviour. In this case the breaking appears to be minimal. Large values of psi meson masses lead to high-lying charmed trajectories in the SU(4) algebraic realization
Nonlinear acceleration of transport criticality problems
International Nuclear Information System (INIS)
Park, H.; Knoll, D.A.; Newman, C.K.
2011-01-01
We present a nonlinear acceleration algorithm for the transport criticality problem. The algorithm combines the well-known nonlinear diffusion acceleration (NDA) with a recently developed, Newton-based, nonlinear criticality acceleration (NCA) algorithm. The algorithm first employs the NDA to reduce the system to scalar flux, then the NCA is applied to the resulting drift-diffusion system. We apply a nonlinear elimination technique to eliminate the eigenvalue from the Jacobian matrix. Numerical results show that the algorithm reduces the CPU time a factor of 400 in a very diffusive system, and a factor of 5 in a non-diffusive system. (author)
Realizing Controllable Quantum States
Takayanagi, Hideaki; Nitta, Junsaku
-- 4. Mesoscopic superconductivity with unconventional superconductor or ferromagnet. Ultraefficient microrefrigerators realized with ferromagnet-superconductor junctions / F. Giazotto et al. Anomalous charge transport in triplet superconductor junctions by the synergy effect of the proximity effect and the mid gap Andreev resonant states / Y. Tanaka and S. Kashiwaya. Paramagnetic and glass states in superconductive YBa[symbol]Cu[symbol]O[symbol] ceramics of sub-micron scale grains / H. Deguchi et al. Quantum properties of single-domain triplet superconductors / A. M. Gulian and K. S. Wood. A numerical study of Josephson current in p wave superconducting junctions / Y. Asano et al. Tilted bi-crystal sapphire substrates improve properties of grain boundary YBa[symbol]Cu[symbol]O[symbol] junctions and extend their Josephson response to THZ frequencies / E. Stepantsov et al. Circuit theory analysis of AB-plane tunnel junctions of unconventional superconductor Bi[symbol]Sr[symbol]Ca[symbol]Cu[symbol]O[symbol] / I. Shigeta et al. Transport properties of normal metal/anisotropic superconductor junctions in the eutectic system Sr[symbol]RuO[symbol]Ru / M. Kawamura et al. Macroscopic quantum tunneling in d-wave superconductor Josephson / S. Kawabata et al. Quasiparticle states of high-T[symbol] oxides observed by a Zeeman magnetic field response / S. Kashiwaya et al. Experimentally realizable devices for controlling the motion of magnetic flux quanta in anisotropic superconductors: vortex lenses, vortex diodes and vortex pumps / S. Savel'ev and F. Nori. Stability of vortex-antivortex "molecules" in mesoscopic superconducting triangles / V. R. Misko et al. Superconducting network with magnetic decoration - Hofstadter butterfly in spatially modulated magnetic field / Y. Iye et al. Observation of paramagnetic supercurrent in mesoscopic superconducting rings and disks using multiple-small-tunnel-junction method / A. Kanda et al. Guidance of vortices in high
Nonlinear-Based MEMS Sensors and Active Switches for Gas Detection
Bouchaala, Adam M.
2016-05-25
The objective of this paper is to demonstrate the integration of a MOF thin film on electrostatically actuated microstructures to realize a switch triggered by gas and a sensing algorithm based on amplitude tracking. The devices are based on the nonlinear response of micromachined clamped-clamped beams. The microbeams are coated with a metal-organic framework (MOF), namely HKUST-1, to achieve high sensitivity. The softening and hardening nonlinear behaviors of the microbeams are exploited to demonstrate the ideas. For gas sensing, an amplitude-based tracking algorithm is developed to quantify the captured quantity of gas. Then, a MEMS switch triggered by gas using the nonlinear response of the microbeam is demonstrated. Noise analysis is conducted, which shows that the switch has high stability against thermal noise. The proposed switch is promising for delivering binary sensing information, and also can be used directly to activate useful functionalities, such as alarming.
Nonlinear-Based MEMS Sensors and Active Switches for Gas Detection
Bouchaala, Adam M.; Jaber, Nizar; Yassine, Omar; Shekhah, Osama; Chernikova, Valeriya; Eddaoudi, Mohamed; Younis, Mohammad I.
2016-01-01
The objective of this paper is to demonstrate the integration of a MOF thin film on electrostatically actuated microstructures to realize a switch triggered by gas and a sensing algorithm based on amplitude tracking. The devices are based on the nonlinear response of micromachined clamped-clamped beams. The microbeams are coated with a metal-organic framework (MOF), namely HKUST-1, to achieve high sensitivity. The softening and hardening nonlinear behaviors of the microbeams are exploited to demonstrate the ideas. For gas sensing, an amplitude-based tracking algorithm is developed to quantify the captured quantity of gas. Then, a MEMS switch triggered by gas using the nonlinear response of the microbeam is demonstrated. Noise analysis is conducted, which shows that the switch has high stability against thermal noise. The proposed switch is promising for delivering binary sensing information, and also can be used directly to activate useful functionalities, such as alarming.
Nonlinear-Based MEMS Sensors and Active Switches for Gas Detection
Directory of Open Access Journals (Sweden)
Adam Bouchaala
2016-05-01
Full Text Available The objective of this paper is to demonstrate the integration of a MOF thin film on electrostatically actuated microstructures to realize a switch triggered by gas and a sensing algorithm based on amplitude tracking. The devices are based on the nonlinear response of micromachined clamped-clamped beams. The microbeams are coated with a metal-organic framework (MOF, namely HKUST-1, to achieve high sensitivity. The softening and hardening nonlinear behaviors of the microbeams are exploited to demonstrate the ideas. For gas sensing, an amplitude-based tracking algorithm is developed to quantify the captured quantity of gas. Then, a MEMS switch triggered by gas using the nonlinear response of the microbeam is demonstrated. Noise analysis is conducted, which shows that the switch has high stability against thermal noise. The proposed switch is promising for delivering binary sensing information, and also can be used directly to activate useful functionalities, such as alarming.
Nonlinear-Based MEMS Sensors and Active Switches for Gas Detection
Bouchaala, Adam; Jaber, Nizar; Yassine, Omar; Shekhah, Osama; Chernikova, Valeriya; Eddaoudi, Mohamed; Younis, Mohammad I.
2016-01-01
The objective of this paper is to demonstrate the integration of a MOF thin film on electrostatically actuated microstructures to realize a switch triggered by gas and a sensing algorithm based on amplitude tracking. The devices are based on the nonlinear response of micromachined clamped-clamped beams. The microbeams are coated with a metal-organic framework (MOF), namely HKUST-1, to achieve high sensitivity. The softening and hardening nonlinear behaviors of the microbeams are exploited to demonstrate the ideas. For gas sensing, an amplitude-based tracking algorithm is developed to quantify the captured quantity of gas. Then, a MEMS switch triggered by gas using the nonlinear response of the microbeam is demonstrated. Noise analysis is conducted, which shows that the switch has high stability against thermal noise. The proposed switch is promising for delivering binary sensing information, and also can be used directly to activate useful functionalities, such as alarming. PMID:27231914
Nonlinear-Based MEMS Sensors and Active Switches for Gas Detection.
Bouchaala, Adam; Jaber, Nizar; Yassine, Omar; Shekhah, Osama; Chernikova, Valeriya; Eddaoudi, Mohamed; Younis, Mohammad I
2016-05-25
The objective of this paper is to demonstrate the integration of a MOF thin film on electrostatically actuated microstructures to realize a switch triggered by gas and a sensing algorithm based on amplitude tracking. The devices are based on the nonlinear response of micromachined clamped-clamped beams. The microbeams are coated with a metal-organic framework (MOF), namely HKUST-1, to achieve high sensitivity. The softening and hardening nonlinear behaviors of the microbeams are exploited to demonstrate the ideas. For gas sensing, an amplitude-based tracking algorithm is developed to quantify the captured quantity of gas. Then, a MEMS switch triggered by gas using the nonlinear response of the microbeam is demonstrated. Noise analysis is conducted, which shows that the switch has high stability against thermal noise. The proposed switch is promising for delivering binary sensing information, and also can be used directly to activate useful functionalities, such as alarming.
Realistic Realizations Of Threshold Circuits
Razavi, Hassan M.
1987-08-01
Threshold logic, in which each input is weighted, has many theoretical advantages over the standard gate realization, such as reducing the number of gates, interconnections, and power dissipation. However, because of the difficult synthesis procedure and complicated circuit implementation, their use in the design of digital systems is almost nonexistant. In this study, three methods of NMOS realizations are discussed, and their advantages and shortcomings are explored. Also, the possibility of using the methods to realize multi-valued logic is examined.
Beyond the SM with nonlinearly realized gauge theories
International Nuclear Information System (INIS)
ERRARI, R.
2014-01-01
A Stuckelberg Mass Term (SMT) is introduced in a SU(2) non-abelian gauge theory as an alternative to the Higgs mechanism. A lattice model is used in order to investigate the mass spectrum of the theory, in particular the presence of Higgs-like bound states. Simulations indicate the presence of neutral bound states. Further investigations are needed in order to compare the model with experiments.
Electron dose map inversion based on several algorithms
International Nuclear Information System (INIS)
Li Gui; Zheng Huaqing; Wu Yican; Fds Team
2010-01-01
The reconstruction to the electron dose map in radiation therapy was investigated by constructing the inversion model of electron dose map with different algorithms. The inversion model of electron dose map based on nonlinear programming was used, and this model was applied the penetration dose map to invert the total space one. The realization of this inversion model was by several inversion algorithms. The test results with seven samples show that except the NMinimize algorithm, which worked for just one sample, with great error,though,all the inversion algorithms could be realized to our inversion model rapidly and accurately. The Levenberg-Marquardt algorithm, having the greatest accuracy and speed, could be considered as the first choice in electron dose map inversion.Further tests show that more error would be created when the data close to the electron range was used (tail error). The tail error might be caused by the approximation of mean energy spectra, and this should be considered to improve the method. The time-saving and accurate algorithms could be used to achieve real-time dose map inversion. By selecting the best inversion algorithm, the clinical need in real-time dose verification can be satisfied. (authors)
Fu, Y. B.; Ogden, R. W.
2001-05-01
This collection of papers by leading researchers in the field of finite, nonlinear elasticity concerns itself with the behavior of objects that deform when external forces or temperature gradients are applied. This process is extremely important in many industrial settings, such as aerospace and rubber industries. This book covers the various aspects of the subject comprehensively with careful explanations of the basic theories and individual chapters each covering a different research direction. The authors discuss the use of symbolic manipulation software as well as computer algorithm issues. The emphasis is placed firmly on covering modern, recent developments, rather than the very theoretical approach often found. The book will be an excellent reference for both beginners and specialists in engineering, applied mathematics and physics.
Optimal Control of Complex Systems Based on Improved Dual Heuristic Dynamic Programming Algorithm
Directory of Open Access Journals (Sweden)
Hui Li
2017-01-01
Full Text Available When applied to solving the data modeling and optimal control problems of complex systems, the dual heuristic dynamic programming (DHP technique, which is based on the BP neural network algorithm (BP-DHP, has difficulty in prediction accuracy, slow convergence speed, poor stability, and so forth. In this paper, a dual DHP technique based on Extreme Learning Machine (ELM algorithm (ELM-DHP was proposed. Through constructing three kinds of network structures, the paper gives the detailed realization process of the DHP technique in the ELM. The controller designed upon the ELM-DHP algorithm controlled a molecular distillation system with complex features, such as multivariability, strong coupling, and nonlinearity. Finally, the effectiveness of the algorithm is verified by the simulation that compares DHP and HDP algorithms based on ELM and BP neural network. The algorithm can also be applied to solve the data modeling and optimal control problems of similar complex systems.
Physical Realizations of Quantum Computing
Kanemitsu, Shigeru; Salomaa, Martti; Takagi, Shin; Are the DiVincenzo Criteria Fulfilled in 2004 ?
2006-01-01
The contributors of this volume are working at the forefront of various realizations of quantum computers. They survey the recent developments in each realization, in the context of the DiVincenzo criteria, including nuclear magnetic resonance, Josephson junctions, quantum dots, and trapped ions. There are also some theoretical contributions which have relevance in the physical realizations of a quantum computer. This book fills the gap between elementary introductions to the subject and highly specialized research papers to allow beginning graduate students to understand the cutting-edge of r
International Nuclear Information System (INIS)
Chatterjee, Kausik; Roadcap, John R.; Singh, Surendra
2014-01-01
The objective of this paper is the exposition of a recently-developed, novel Green's function Monte Carlo (GFMC) algorithm for the solution of nonlinear partial differential equations and its application to the modeling of the plasma sheath region around a cylindrical conducting object, carrying a potential and moving at low speeds through an otherwise neutral medium. The plasma sheath is modeled in equilibrium through the GFMC solution of the nonlinear Poisson–Boltzmann (NPB) equation. The traditional Monte Carlo based approaches for the solution of nonlinear equations are iterative in nature, involving branching stochastic processes which are used to calculate linear functionals of the solution of nonlinear integral equations. Over the last several years, one of the authors of this paper, K. Chatterjee has been developing a philosophically-different approach, where the linearization of the equation of interest is not required and hence there is no need for iteration and the simulation of branching processes. Instead, an approximate expression for the Green's function is obtained using perturbation theory, which is used to formulate the random walk equations within the problem sub-domains where the random walker makes its walks. However, as a trade-off, the dimensions of these sub-domains have to be restricted by the limitations imposed by perturbation theory. The greatest advantage of this approach is the ease and simplicity of parallelization stemming from the lack of the need for iteration, as a result of which the parallelization procedure is identical to the parallelization procedure for the GFMC solution of a linear problem. The application area of interest is in the modeling of the communication breakdown problem during a space vehicle's re-entry into the atmosphere. However, additional application areas are being explored in the modeling of electromagnetic propagation through the atmosphere/ionosphere in UHF/GPS applications
Energy Technology Data Exchange (ETDEWEB)
Chatterjee, Kausik, E-mail: kausik.chatterjee@aggiemail.usu.edu [Strategic and Military Space Division, Space Dynamics Laboratory, North Logan, UT 84341 (United States); Center for Atmospheric and Space Sciences, Utah State University, Logan, UT 84322 (United States); Roadcap, John R., E-mail: john.roadcap@us.af.mil [Air Force Research Laboratory, Kirtland AFB, NM 87117 (United States); Singh, Surendra, E-mail: surendra-singh@utulsa.edu [Department of Electrical Engineering, The University of Tulsa, Tulsa, OK 74104 (United States)
2014-11-01
The objective of this paper is the exposition of a recently-developed, novel Green's function Monte Carlo (GFMC) algorithm for the solution of nonlinear partial differential equations and its application to the modeling of the plasma sheath region around a cylindrical conducting object, carrying a potential and moving at low speeds through an otherwise neutral medium. The plasma sheath is modeled in equilibrium through the GFMC solution of the nonlinear Poisson–Boltzmann (NPB) equation. The traditional Monte Carlo based approaches for the solution of nonlinear equations are iterative in nature, involving branching stochastic processes which are used to calculate linear functionals of the solution of nonlinear integral equations. Over the last several years, one of the authors of this paper, K. Chatterjee has been developing a philosophically-different approach, where the linearization of the equation of interest is not required and hence there is no need for iteration and the simulation of branching processes. Instead, an approximate expression for the Green's function is obtained using perturbation theory, which is used to formulate the random walk equations within the problem sub-domains where the random walker makes its walks. However, as a trade-off, the dimensions of these sub-domains have to be restricted by the limitations imposed by perturbation theory. The greatest advantage of this approach is the ease and simplicity of parallelization stemming from the lack of the need for iteration, as a result of which the parallelization procedure is identical to the parallelization procedure for the GFMC solution of a linear problem. The application area of interest is in the modeling of the communication breakdown problem during a space vehicle's re-entry into the atmosphere. However, additional application areas are being explored in the modeling of electromagnetic propagation through the atmosphere/ionosphere in UHF/GPS applications.
Proposal and realization advertising campaign
RYCHLÁ, Marie
2008-01-01
The Bachelor Paper contains proposal and realization advertising campaign, including make charge for cost amount. The advertising campaign is made for chosen product of firm. Advertising campaign is planning by the medium of broadsheet and advertising on the Internet.
Realization of logical functions by vector programs
Energy Technology Data Exchange (ETDEWEB)
Lapkin, L Ya
1983-03-01
Recent computing and control applications often require program realization of finite automata in general and of an important particular class of memoryless automata specified by systems of Boolean functions. Logical control and computing machines which receive sequences of discrete signals on the input and convert them into sequences of discrete output signals using finite memory may be described by a finite automation model. However, in distinction from the circuit interpretation of finite automata, the automaton algorithm represents the structure of the automaton program and not the structure of the machine itself. Therefore, the complexity of the computer realization of an automaton is the complexity of the computer program, and not the complexity of the hardware. Two classes of programs currently used to evalute boolean functions are operator programs and binary programs. However, computing machines, including microcomputers, are equipped with additional possibilities for evaluation of Boolean functions, which are not utilized in programs of these two basic classes. In this article, we consider the design of vector programs for program realization of systems of Boolean functions. 3 references.
Nonlinear photonic metasurfaces
Li, Guixin; Zhang, Shuang; Zentgraf, Thomas
2017-03-01
Compared with conventional optical elements, 2D photonic metasurfaces, consisting of arrays of antennas with subwavelength thickness (the 'meta-atoms'), enable the manipulation of light-matter interactions on more compact platforms. The use of metasurfaces with spatially varying arrangements of meta-atoms that have subwavelength lateral resolution allows control of the polarization, phase and amplitude of light. Many exotic phenomena have been successfully demonstrated in linear optics; however, to meet the growing demand for the integration of more functionalities into a single optoelectronic circuit, the tailorable nonlinear optical properties of metasurfaces will also need to be exploited. In this Review, we discuss the design of nonlinear photonic metasurfaces — in particular, the criteria for choosing the materials and symmetries of the meta-atoms — for the realization of nonlinear optical chirality, nonlinear geometric Berry phase and nonlinear wavefront engineering. Finally, we survey the application of nonlinear photonic metasurfaces in optical switching and modulation, and we conclude with an outlook on their use for terahertz nonlinear optics and quantum information processing.
International Nuclear Information System (INIS)
Potemki, Valeri G.; Borisevich, Valentine D.; Yupatov, Sergei V.
1996-01-01
This paper describes the the next evolution step in development of the direct method for solving systems of Nonlinear Algebraic Equations (SNAE). These equations arise from the finite difference approximation of original nonlinear partial differential equations (PDE). This method has been extended on the SNAE with three variables. The solving SNAE bases on Reiterating General Singular Value Decomposition of rectangular matrix pencils (RGSVD-algorithm). In contrast to the computer algebra algorithm in integer arithmetic based on the reduction to the Groebner's basis that algorithm is working in floating point arithmetic and realizes the reduction to the Kronecker's form. The possibilities of the method are illustrated on the example of solving the one-dimensional diffusion equation for 3-component model isotope mixture in a ga centrifuge. The implicit scheme for the finite difference equations without simplifying the nonlinear properties of the original equations is realized. The technique offered provides convergence to the solution for the single run. The Toolbox SNAE is developed in the framework of the high performance numeric computation and visualization software MATLAB. It includes more than 30 modules in MATLAB language for solving SNAE with two and three variables. (author)
THERAPEUTIC SUPPORT OF REALIZATION OF THE COMPETENCE APPROACH IN EDUCATION
Directory of Open Access Journals (Sweden)
Viktoriia A. Lykova
2010-08-01
Full Text Available The article analyses mechanisms of realization of the competence approach in education. Its therapeutic support actualizes factors of nonlinearity, processuality, subjectivity, conformity with nature, feedback in the educational environment. Behind each person there is a variety of tendencies, therefore to foresee or plan, «limit by standards» what exactly will be personally significant for a particular student in pedagogical interaction, is impossible. Therapeutic competence of teachers allows to realize individual learning pathways with support on a «fan of indicators» within a circle of competences.
Başhan, Ali; Uçar, Yusuf; Murat Yağmurlu, N.; Esen, Alaattin
2018-01-01
In the present paper, a Crank-Nicolson-differential quadrature method (CN-DQM) based on utilizing quintic B-splines as a tool has been carried out to obtain the numerical solutions for the nonlinear Schrödinger (NLS) equation. For this purpose, first of all, the Schrödinger equation has been converted into coupled real value differential equations and then they have been discretized using both the forward difference formula and the Crank-Nicolson method. After that, Rubin and Graves linearization techniques have been utilized and the differential quadrature method has been applied to obtain an algebraic equation system. Next, in order to be able to test the efficiency of the newly applied method, the error norms, L2 and L_{∞}, as well as the two lowest invariants, I1 and I2, have been computed. Besides those, the relative changes in those invariants have been presented. Finally, the newly obtained numerical results have been compared with some of those available in the literature for similar parameters. This comparison clearly indicates that the currently utilized method, namely CN-DQM, is an effective and efficient numerical scheme and allows us to propose to solve a wide range of nonlinear equations.
A Trust-region-based Sequential Quadratic Programming Algorithm
DEFF Research Database (Denmark)
Henriksen, Lars Christian; Poulsen, Niels Kjølstad
This technical note documents the trust-region-based sequential quadratic programming algorithm used in other works by the authors. The algorithm seeks to minimize a convex nonlinear cost function subject to linear inequalty constraints and nonlinear equality constraints.......This technical note documents the trust-region-based sequential quadratic programming algorithm used in other works by the authors. The algorithm seeks to minimize a convex nonlinear cost function subject to linear inequalty constraints and nonlinear equality constraints....
The variable refractive index correction algorithm based on a stereo light microscope
International Nuclear Information System (INIS)
Pei, W; Zhu, Y Y
2010-01-01
Refraction occurs at least twice on both the top and the bottom surfaces of the plastic plate covering the micro channel in a microfluidic chip. The refraction and the nonlinear model of a stereo light microscope (SLM) may severely affect measurement accuracy. In this paper, we study the correlation between optical paths of the SLM and present an algorithm to adjust the refractive index based on the SLM. Our algorithm quantizes the influence of cover plate and double optical paths on the measurement accuracy, and realizes non-destructive, non-contact and precise 3D measurement of a hyaloid and closed container
Digital, realizable Wiener filtering in two-dimensions
International Nuclear Information System (INIS)
Ekstrom, M.P.
1979-01-01
The extension of Wiener's classical mean-square filtering theory to the estimation of two-dimensional (2-D), discrete random fields is discussed. In analogy with the 1-D case, the optimal realizable filter is derived by solution of a 2-D discrete Wiener--Hopf equation using a spectral factorization procedure. Computational algorithms for performing the required calculations are discussed. 3 figures
Multiple Realizability and Biological Laws
Raerinne, Jani P.; Eronen, Markus I.
2012-01-01
We critically analyze Alexander Rosenberg's argument based on the multiple realizability of biological properties that there are no biological laws. The argument is intuitive and suggestive. Nevertheless, a closer analysis reveals that the argument rests on dubious assumptions about the nature of
Realizations of the canonical representation
Indian Academy of Sciences (India)
Traditionally, the canonical representation is realized on the Hilbert space ... Fix a decomposition R2n = Rn × Rn ..... to an orthonormal basis {ψ1,ψ2,. ..... [7] Vemuri M K, A non-commutative Sobolev inequality and its application to spectral.
DEFF Research Database (Denmark)
Asif, Rameez
2016-01-01
We have evaluated that in-line non-linear compensation schemes decrease the complexity of digital backward propagation and enhance the transmission performance of 40/112/224 Gbit/s mixed line rate network. Multiple bit rates, i.e. 40/112/224 Gbit/s and modulation formats (i.e. DP-QPSK and DP-16QAM......) are transmitted over 1280 km of Large $$\\hbox {A}_{eff}$$ A e f f Pure-Silica core fiber. Both grouped and un-grouped spectral allocation schemes are investigated. Optical add-drop multiplexers are used to drop the required wavelength for signal processing in the transmission link. Moreover, hybrid mid...
Nativi, S; Mazzetti, P
2004-01-01
In a previous work, an operative procedure to estimate precipitable and liquid water in non-raining conditions over sea was developed and assessed. The procedure is based on a fast non-linear physical inversion scheme and a forward model; it is valid for most of satellite microwave radiometers and it also estimates water effective profiles. This paper presents two improvements of the procedure: first, a refinement to provide modularity of the software components and portability across different computation system architectures; second, the adoption of the CERN MINUIT minimisation package, which addresses the problem of global minimisation but is computationally more demanding. Together with the increased computational performance that allowed to impose stricter requirements on the quality of fit, these refinements improved fitting precision and reliability, and allowed to relax the requirements on the initial guesses for the model parameters. The re-analysis of the same data-set considered in the previous pap...
International Nuclear Information System (INIS)
Boyd, R.W.
1992-01-01
Nonlinear optics is the study of the interaction of intense laser light with matter. This book is a textbook on nonlinear optics at the level of a beginning graduate student. The intent of the book is to provide an introduction to the field of nonlinear optics that stresses fundamental concepts and that enables the student to go on to perform independent research in this field. This book covers the areas of nonlinear optics, quantum optics, quantum electronics, laser physics, electrooptics, and modern optics
Effective Complexity of Stationary Process Realizations
Directory of Open Access Journals (Sweden)
Arleta Szkoła
2011-06-01
Full Text Available The concept of effective complexity of an object as the minimal description length of its regularities has been initiated by Gell-Mann and Lloyd. The regularities are modeled by means of ensembles, which is the probability distributions on finite binary strings. In our previous paper [1] we propose a definition of effective complexity in precise terms of algorithmic information theory. Here we investigate the effective complexity of binary strings generated by stationary, in general not computable, processes. We show that under not too strong conditions long typical process realizations are effectively simple. Our results become most transparent in the context of coarse effective complexity which is a modification of the original notion of effective complexity that needs less parameters in its definition. A similar modification of the related concept of sophistication has been suggested by Antunes and Fortnow.
Complex fluid network optimization and control integrative design based on nonlinear dynamic model
International Nuclear Information System (INIS)
Sui, Jinxue; Yang, Li; Hu, Yunan
2016-01-01
In view of distribution according to complex fluid network’s needs, this paper proposed one optimization computation method of the nonlinear programming mathematical model based on genetic algorithm. The simulation result shows that the overall energy consumption of the optimized fluid network has a decrease obviously. The control model of the fluid network is established based on nonlinear dynamics. We design the control law based on feedback linearization, take the optimal value by genetic algorithm as the simulation data, can also solve the branch resistance under the optimal value. These resistances can provide technical support and reference for fluid network design and construction, so can realize complex fluid network optimization and control integration design.
Sequential reconstruction of driving-forces from nonlinear nonstationary dynamics
Güntürkün, Ulaş
2010-07-01
This paper describes a functional analysis-based method for the estimation of driving-forces from nonlinear dynamic systems. The driving-forces account for the perturbation inputs induced by the external environment or the secular variations in the internal variables of the system. The proposed algorithm is applicable to the problems for which there is too little or no prior knowledge to build a rigorous mathematical model of the unknown dynamics. We derive the estimator conditioned on the differentiability of the unknown system’s mapping, and smoothness of the driving-force. The proposed algorithm is an adaptive sequential realization of the blind prediction error method, where the basic idea is to predict the observables, and retrieve the driving-force from the prediction error. Our realization of this idea is embodied by predicting the observables one-step into the future using a bank of echo state networks (ESN) in an online fashion, and then extracting the raw estimates from the prediction error and smoothing these estimates in two adaptive filtering stages. The adaptive nature of the algorithm enables to retrieve both slowly and rapidly varying driving-forces accurately, which are illustrated by simulations. Logistic and Moran-Ricker maps are studied in controlled experiments, exemplifying chaotic state and stochastic measurement models. The algorithm is also applied to the estimation of a driving-force from another nonlinear dynamic system that is stochastic in both state and measurement equations. The results are judged by the posterior Cramer-Rao lower bounds. The method is finally put into test on a real-world application; extracting sun’s magnetic flux from the sunspot time series.
GPU Computing in Bayesian Inference of Realized Stochastic Volatility Model
International Nuclear Information System (INIS)
Takaishi, Tetsuya
2015-01-01
The realized stochastic volatility (RSV) model that utilizes the realized volatility as additional information has been proposed to infer volatility of financial time series. We consider the Bayesian inference of the RSV model by the Hybrid Monte Carlo (HMC) algorithm. The HMC algorithm can be parallelized and thus performed on the GPU for speedup. The GPU code is developed with CUDA Fortran. We compare the computational time in performing the HMC algorithm on GPU (GTX 760) and CPU (Intel i7-4770 3.4GHz) and find that the GPU can be up to 17 times faster than the CPU. We also code the program with OpenACC and find that appropriate coding can achieve the similar speedup with CUDA Fortran
PRAGMATIC TRANSFER IN REQUEST REALIZATIONS
Directory of Open Access Journals (Sweden)
Indawan Syahri
2007-01-01
Full Text Available This study investigates the pragmatic transfer in English request realizations made by EFL learners, i.e. the proficient learners. The subjects were students of an English Study Program who obtained TOEFL-like scores of at least 450. The data were collected by means of DCT-questionnaires and Role-plays. The results show that the subjects realize requests in the form of external modifications more frequently. Most of them embed their requests with supportive moves dominantly. They enfold the acts with the moves before, after or in both positions. Of the three positions, they mostly insert the moves initial position, i.e., through inductive patterns. This is due to pragmatic transfer.
Bloembergen, Nicolaas
1996-01-01
Nicolaas Bloembergen, recipient of the Nobel Prize for Physics (1981), wrote Nonlinear Optics in 1964, when the field of nonlinear optics was only three years old. The available literature has since grown by at least three orders of magnitude.The vitality of Nonlinear Optics is evident from the still-growing number of scientists and engineers engaged in the study of new nonlinear phenomena and in the development of new nonlinear devices in the field of opto-electronics. This monograph should be helpful in providing a historical introduction and a general background of basic ideas both for expe
Cosmological effects of nonlinear electrodynamics
International Nuclear Information System (INIS)
Novello, M; Goulart, E; Salim, J M; Bergliaffa, S E Perez
2007-01-01
It will be shown that a given realization of nonlinear electrodynamics, used as a source of Einstein's equations, generates a cosmological model with interesting features, namely a phase of current cosmic acceleration, and the absence of an initial singularity, thus pointing to a way of solving two important problems in cosmology
Design and realization of simulators
International Nuclear Information System (INIS)
Mathey, C.
1984-01-01
The two main categories of simulators are training simulators of which aim is the education of the nuclear power plant operators, and the study simulators. The French park of simulators is reviewed, as also their field of utilization. One deals with the simulator design: general description, calculation tools, middleware, and programming, mathematical models and numerical methods. Then, the instructor post of the EDF's simulators are more particularly described. The realization of a simulator includes two main stages: the development of the material and, the development of the software [fr
PREFACE: Nanospintronics design and realization
Akai, Hisazumi; Katayama-Yoshida, Hiroshi; Kasai, Hideaki
2004-12-01
This special issue of Journal of Physics: Condensed Matter contains selected papers from the 1st International Conference on Nanospintronics Design and Realization (ICNDR 2004), which was held in Kyoto, Japan, 24--28 May 2004. This conference was organized by the Nanospintronics Design and Realization project members: Hideaki Kasai, Osaka (Chair of the Conference) Hisazumi Akai, Osaka Hajime Asahi, Osaka Wilson Agerico Diño, Osaka Hiroshi Harima, Kyoto Tomoyuki Kakeshita, Osaka Junjiro Kanamori, Kyoto Hiroshi Katayama-Yoshida, Osaka Koichi Kusakabe, Osaka Hiroshi Nakanishi, Osaka (Secretary) Tamio Oguchi, Hiroshima Teruo Ono, Osaka Naoshi Suzuki, Osaka Hitoshi Tabata, Osaka under the auspices of the Japan Ministry of Education, Culture, Sports, Science and Technology (MEXT) Special Coordination Funds for Promoting Science and Technology, and the sponsorship of Osaka University and the International Institute for Advanced Studies (IIAS). The conference is intended to provide an international forum for experimental and theoretical researchers, in the rapidly developing field of nanospintronics. It aims to: provide an overview of our current understanding of the physics of spin transport in (magnetic) semiconductors and hybrid magnetic/semiconductor structures; provide a venue to present and discuss the latest developments in using spin-dependent phenomena in nano-(opto-) electronics and computing applications; provide a venue for discussion and assessment of other possible means of exploiting the spin-dependent phenomena in future nano-(opto-) electronic and computing applications; address current (and foreseeable future) problems, of fundamental and applied nature, in an effort to bridge the physics and technology gap between semiconducting and magnetic materials. All of these being geared towards bringing about the realization of a functioning nanospintronics. A total of 127 delegates from 15 countries took part in ICNDR 2004, which was comprised of 62 invited
International Nuclear Information System (INIS)
Ferkous, F.; Saihi, Y.
2018-01-01
Quantitative structure-activity relationships were constructed for 107 inhibitors of HIV-1 reverse transcriptase that are derivatives of 1-[(2-hydroxyethoxy)methyl]-6-(phenylthio)thymine (HEPT). A combination of a support vector machine (SVM) and oscillating search (OS) algorithms for feature selection was adopted to select the most appropriate descriptors. The application was optimized to obtain an SVM model to predict the biological activity EC50 of the HEPT derivatives with a minimum number of descriptors (SpMax4 B h (e) MLOGP MATS5m) and high values of R2 and Q2 (0.8662, 0.8769). The statistical results showed good correlation between the activity and three best descriptors were included in the best SVM model. The values of R2 and Q2 confirmed the stability and good predictive ability of the model. The SVM technique was adequate to produce an effective QSAR model and outperformed those in the literature and the predictive stages for the inhibitory activity of reverse transcriptase by HEPT derivatives. (author)
Hardware Realization of Chaos Based Symmetric Image Encryption
Barakat, Mohamed L.
2012-06-01
This thesis presents a novel work on hardware realization of symmetric image encryption utilizing chaos based continuous systems as pseudo random number generators. Digital implementation of chaotic systems results in serious degradations in the dynamics of the system. Such defects are illuminated through a new technique of generalized post proceeding with very low hardware cost. The thesis further discusses two encryption algorithms designed and implemented as a block cipher and a stream cipher. The security of both systems is thoroughly analyzed and the performance is compared with other reported systems showing a superior results. Both systems are realized on Xilinx Vetrix-4 FPGA with a hardware and throughput performance surpassing known encryption systems.
Graphics processor efficiency for realization of rapid tabular computations
International Nuclear Information System (INIS)
Dudnik, V.A.; Kudryavtsev, V.I.; Us, S.A.; Shestakov, M.V.
2016-01-01
Capabilities of graphics processing units (GPU) and central processing units (CPU) have been investigated for realization of fast-calculation algorithms with the use of tabulated functions. The realization of tabulated functions is exemplified by the GPU/CPU architecture-based processors. Comparison is made between the operating efficiencies of GPU and CPU, employed for tabular calculations at different conditions of use. Recommendations are formulated for the use of graphical and central processors to speed up scientific and engineering computations through the use of tabulated functions
DEFF Research Database (Denmark)
Mosegaard, Klaus
2012-01-01
For non-linear inverse problems, the mathematical structure of the mapping from model parameters to data is usually unknown or partly unknown. Absence of information about the mathematical structure of this function prevents us from presenting an analytical solution, so our solution depends on our......-heuristics are inefficient for large-scale, non-linear inverse problems, and that the 'no-free-lunch' theorem holds. We discuss typical objections to the relevance of this theorem. A consequence of the no-free-lunch theorem is that algorithms adapted to the mathematical structure of the problem perform more efficiently than...... pure meta-heuristics. We study problem-adapted inversion algorithms that exploit the knowledge of the smoothness of the misfit function of the problem. Optimal sampling strategies exist for such problems, but many of these problems remain hard. © 2012 Springer-Verlag....
Nonlinear dynamics of structures
Oller, Sergio
2014-01-01
This book lays the foundation of knowledge that will allow a better understanding of nonlinear phenomena that occur in structural dynamics. This work is intended for graduate engineering students who want to expand their knowledge on the dynamic behavior of structures, specifically in the nonlinear field, by presenting the basis of dynamic balance in non‐linear behavior structures due to the material and kinematics mechanical effects. Particularly, this publication shows the solution of the equation of dynamic equilibrium for structure with nonlinear time‐independent materials (plasticity, damage and frequencies evolution), as well as those time dependent non‐linear behavior materials (viscoelasticity and viscoplasticity). The convergence conditions for the non‐linear dynamic structure solution are studied, and the theoretical concepts and its programming algorithms are presented.
Rodrigues, Nils; Weiskopf, Daniel
2018-01-01
Conventional dot plots use a constant dot size and are typically applied to show the frequency distribution of small data sets. Unfortunately, they are not designed for a high dynamic range of frequencies. We address this problem by introducing nonlinear dot plots. Adopting the idea of nonlinear scaling from logarithmic bar charts, our plots allow for dots of varying size so that columns with a large number of samples are reduced in height. For the construction of these diagrams, we introduce an efficient two-way sweep algorithm that leads to a dense and symmetrical layout. We compensate aliasing artifacts at high dot densities by a specifically designed low-pass filtering method. Examples of nonlinear dot plots are compared to conventional dot plots as well as linear and logarithmic histograms. Finally, we include feedback from an expert review.
Directory of Open Access Journals (Sweden)
Xiao-Fang Zhong
2017-12-01
Full Text Available The irregular wave disturbance attenuation problem for jacket-type offshore platforms involving the nonlinear characteristics is studied. The main contribution is that a digital-control-based approximation of optimal wave disturbances attenuation controller (AOWDAC is proposed based on iteration control theory, which consists of a feedback item of offshore state, a feedforward item of wave force and a nonlinear compensated component with iterative sequences. More specifically, by discussing the discrete model of nonlinear offshore platform subject to wave forces generated from the Joint North Sea Wave Project (JONSWAP wave spectrum and linearized wave theory, the original wave disturbances attenuation problem is formulated as the nonlinear two-point-boundary-value (TPBV problem. By introducing two vector sequences of system states and nonlinear compensated item, the solution of introduced nonlinear TPBV problem is obtained. Then, a numerical algorithm is designed to realize the feasibility of AOWDAC based on the deviation of performance index between the adjacent iteration processes. Finally, applied the proposed AOWDAC to a jacket-type offshore platform in Bohai Bay, the vibration amplitudes of the displacement and the velocity, and the required energy consumption can be reduced significantly.
Yoshida, Zensho
2010-01-01
This book gives a general, basic understanding of the mathematical structure "nonlinearity" that lies in the depths of complex systems. Analyzing the heterogeneity that the prefix "non" represents with respect to notions such as the linear space, integrability and scale hierarchy, "nonlinear science" is explained as a challenge of deconstruction of the modern sciences. This book is not a technical guide to teach mathematical tools of nonlinear analysis, nor a zoology of so-called nonlinear phenomena. By critically analyzing the structure of linear theories, and cl
Nayfeh, Ali Hasan
1995-01-01
Nonlinear Oscillations is a self-contained and thorough treatment of the vigorous research that has occurred in nonlinear mechanics since 1970. The book begins with fundamental concepts and techniques of analysis and progresses through recent developments and provides an overview that abstracts and introduces main nonlinear phenomena. It treats systems having a single degree of freedom, introducing basic concepts and analytical methods, and extends concepts and methods to systems having degrees of freedom. Most of this material cannot be found in any other text. Nonlinear Oscillations uses sim
Symmetry realization via a dynamical inverse Higgs mechanism
Rothstein, Ira Z.; Shrivastava, Prashant
2018-05-01
The Ward identities associated with spontaneously broken symmetries can be saturated by Goldstone bosons. However, when space-time symmetries are broken, the number of Goldstone bosons necessary to non-linearly realize the symmetry can be less than the number of broken generators. The loss of Goldstones may be due to a redundancy or the generation of a gap. In either case the associated Goldstone may be removed from the spectrum. This phenomena is called an Inverse Higgs Mechanism (IHM) and its appearance has a well defined mathematical condition. However, there are cases when a Goldstone boson associated with a broken generator does not appear in the low energy theory despite the lack of the existence of an associated IHM. In this paper we will show that in such cases the relevant broken symmetry can be realized, without the aid of an associated Goldstone, if there exists a proper set of operator constraints, which we call a Dynamical Inverse Higgs Mechanism (DIHM). We consider the spontaneous breaking of boosts, rotations and conformal transformations in the context of Fermi liquids, finding three possible paths to symmetry realization: pure Goldstones, no Goldstones and DIHM, or some mixture thereof. We show that in the two dimensional degenerate electron system the DIHM route is the only consistent way to realize spontaneously broken boosts and dilatations, while in three dimensions these symmetries could just as well be realized via the inclusion of non-derivatively coupled Goldstone bosons. We present the action, including the leading order non-linearities, for the rotational Goldstone (angulon), and discuss the constraint associated with the possible DIHM that would need to be imposed to remove it from the spectrum. Finally we discuss the conditions under which Goldstone bosons are non-derivatively coupled, a necessary condition for the existence of a Dynamical Inverse Higgs Constraint (DIHC), generalizing the results for Vishwanath and Wantanabe.
Dreams, Perception, and Creative Realization.
Glaskin, Katie
2015-10-01
This article draws on the ethnography of Aboriginal Australia to argue that perceptual openness, extending from waking life into dreaming experience, provides an important cognitive framework for the apprehension of dreamt experience in these contexts. I argue that this perceptual openness is analogous to the "openness to experience" described as a personality trait that had been linked with dream recall frequency (among other things). An implication of identifying perceptual openness at a cultural rather than at an individual level is two-fold. It provides an example of the ways in which cultural differences affect perception, indicative of cognitive diversity; and, given the relationship between dreams and creativity suggested anecdotally and through research, a cultural orientation toward perceptual openness is also likely to have implications for the realization of creativity that occurs through dreams. Such creativity though cannot be separated from the relational context in which such dreamt material is elaborated and understood. Copyright © 2015 Cognitive Science Society, Inc.
Palmero, Faustino; Lemos, M; Sánchez-Rey, Bernardo; Casado-Pascual, Jesús
2018-01-01
This book presents an overview of the most recent advances in nonlinear science. It provides a unified view of nonlinear properties in many different systems and highlights many new developments. While volume 1 concentrates on mathematical theory and computational techniques and challenges, which are essential for the study of nonlinear science, this second volume deals with nonlinear excitations in several fields. These excitations can be localized and transport energy and matter in the form of breathers, solitons, kinks or quodons with very different characteristics, which are discussed in the book. They can also transport electric charge, in which case they are known as polarobreathers or solectrons. Nonlinear excitations can influence function and structure in biology, as for example, protein folding. In crystals and other condensed matter, they can modify transport properties, reaction kinetics and interact with defects. There are also engineering applications in electric lattices, Josephson junction a...
Institute of Scientific and Technical Information of China (English)
马金全; 葛临东; 童莉
2014-01-01
脉冲噪声环境下波达方向( DOA)估计是阵列信号处理领域一个新兴研究方向。针对α稳定分布噪声环境下经典MUSIC算法性能退化的问题,提出了一种新的基于非线性压缩核函数( NCCF)的DOA估计算法。该算法利用基于NCCF的有界矩阵代替了MUSIC的协方差矩阵,通过对有界矩阵进行特征分解确定信号子空间和噪声子空间,借用MUSIC谱估计公式进行谱峰搜索,得到DOA的估计值。仿真结果表明,NCCF-MUSIC算法运算复杂度较低,相比于基于分数低阶统计量( FLOS)的MUSIC方法和基于广义类相关熵( GCAS)的MUSIC算法,该方法具有更好的准确度和稳定性。%Direction of arrival ( DOA) estimation in the impulse noise environment is a new research direc-tion in the array signal processing field. To solve the problem of performance degradation when applying classic MUSIC algorithm for DOA estimation in the α-stable distribution noise environment,a novel DOA estimation algorithm based on a nonlinear compress core function ( NCCF ) is provided and named as the NCCF-MUSIC. To obtain a DOA estimation,the NCCF-MUSIC method replaces the covariance matrix in MUSIC by a bounded matrix based on the NCCF,and then determines the signal subspace and the noise subspace by feature decomposition, and finally, introduces the MUSIC spectrum estimation algorithm to make a spectral peak searching. Simulation results show that the new NCCF-MUSIC method with a lower computation cost has the higher performance in accuracy and validity than the MUSIC methods based on fractional lower order statistics ( FLOS) or based on generalized correntropy-analogous statistics ( GCAS) .
System Realization of Broad Band Digital Beam Forming for Digital Array Radar
Directory of Open Access Journals (Sweden)
Wang Feng
2013-09-01
Full Text Available Broad band Digital Beam Forming (DBF is the key technique for the realization of Digital Array Radar (DAR. We propose the method of combination realization of the channel equalization and DBF time delay filter function by using adaptive Sample Matrix Inversion algorithm. The broad band DBF function is realized on a new DBF module based on parallel fiber optic engines and Field Program Gate Array (FPGA. Good performance is achieved when it is used to some radar products.
Boyd, Robert W
2013-01-01
Nonlinear Optics is an advanced textbook for courses dealing with nonlinear optics, quantum electronics, laser physics, contemporary and quantum optics, and electrooptics. Its pedagogical emphasis is on fundamentals rather than particular, transitory applications. As a result, this textbook will have lasting appeal to a wide audience of electrical engineering, physics, and optics students, as well as those in related fields such as materials science and chemistry.Key Features* The origin of optical nonlinearities, including dependence on the polarization of light* A detailed treatment of the q
A Realization Approach for Residual Expressions
DEFF Research Database (Denmark)
Skovmose Kallesøe, Carsten; Izadi-Zamanabadi, Roozbeh; Wisniewski, Rafal
2006-01-01
This paper is concerned with state space realization of inherent redundant information in subsystems, which are identified by structural analysis (SA) approach. The identified subsystems are assumed to involve algebraic variables, representing unknown signals. The proposed realization method...
Realization of an integral using anticommuting variables
International Nuclear Information System (INIS)
Valuev, B.N.
1979-01-01
It is shown that the integral defined by Berezin over anticommuting variables may be realized as a trace on the Clifford algebra. In fact, this realization makes precise the definition of the integral
Primitive recursive realizability and basic propositional logic
Plisko, Valery
2007-01-01
Two notions of primitive recursive realizability for arithmetic sentences are considered. The first one is strictly primitive recursive realizability introduced by Z. Damnjanovic in 1994. We prove that intuitionistic predicate logic is not sound with this kind of realizability. Namely there
National Research Council Canada - National Science Library
Drazin, P. G
1992-01-01
This book is an introduction to the theories of bifurcation and chaos. It treats the solution of nonlinear equations, especially difference and ordinary differential equations, as a parameter varies...
Gasinski, Leszek
2005-01-01
Hausdorff Measures and Capacity. Lebesgue-Bochner and Sobolev Spaces. Nonlinear Operators and Young Measures. Smooth and Nonsmooth Analysis and Variational Principles. Critical Point Theory. Eigenvalue Problems and Maximum Principles. Fixed Point Theory.
Nonlinear Statistical Signal Processing: A Particle Filtering Approach
International Nuclear Information System (INIS)
Candy, J.
2007-01-01
A introduction to particle filtering is discussed starting with an overview of Bayesian inference from batch to sequential processors. Once the evolving Bayesian paradigm is established, simulation-based methods using sampling theory and Monte Carlo realizations are discussed. Here the usual limitations of nonlinear approximations and non-gaussian processes prevalent in classical nonlinear processing algorithms (e.g. Kalman filters) are no longer a restriction to perform Bayesian inference. It is shown how the underlying hidden or state variables are easily assimilated into this Bayesian construct. Importance sampling methods are then discussed and shown how they can be extended to sequential solutions implemented using Markovian state-space models as a natural evolution. With this in mind, the idea of a particle filter, which is a discrete representation of a probability distribution, is developed and shown how it can be implemented using sequential importance sampling/resampling methods. Finally, an application is briefly discussed comparing the performance of the particle filter designs with classical nonlinear filter implementations
Classical realizability in the CPS target language
DEFF Research Database (Denmark)
Frey, Jonas
2016-01-01
Motivated by considerations about Krivine's classical realizability, we introduce a term calculus for an intuitionistic logic with record types, which we call the CPS target language. We give a reformulation of the constructions of classical realizability in this language, using the categorical...... techniques of realizability triposes and toposes. We argue that the presentation of classical realizability in the CPS target language simplifies calculations in realizability toposes, in particular it admits a nice presentation of conjunction as intersection type which is inspired by Girard's ludics....
Spurious Solutions Of Nonlinear Differential Equations
Yee, H. C.; Sweby, P. K.; Griffiths, D. F.
1992-01-01
Report utilizes nonlinear-dynamics approach to investigate possible sources of errors and slow convergence and non-convergence of steady-state numerical solutions when using time-dependent approach for problems containing nonlinear source terms. Emphasizes implications for development of algorithms in CFD and computational sciences in general. Main fundamental conclusion of study is that qualitative features of nonlinear differential equations cannot be adequately represented by finite-difference method and vice versa.
NONLINEAR MODEL PREDICTIVE CONTROL OF CHEMICAL PROCESSES
Directory of Open Access Journals (Sweden)
SILVA R. G.
1999-01-01
Full Text Available A new algorithm for model predictive control is presented. The algorithm utilizes a simultaneous solution and optimization strategy to solve the model's differential equations. The equations are discretized by equidistant collocation, and along with the algebraic model equations are included as constraints in a nonlinear programming (NLP problem. This algorithm is compared with the algorithm that uses orthogonal collocation on finite elements. The equidistant collocation algorithm results in simpler equations, providing a decrease in computation time for the control moves. Simulation results are presented and show a satisfactory performance of this algorithm.
Algorithms over partially ordered sets
DEFF Research Database (Denmark)
Baer, Robert M.; Østerby, Ole
1969-01-01
in partially ordered sets, answer the combinatorial question of how many maximal chains might exist in a partially ordered set withn elements, and we give an algorithm for enumerating all maximal chains. We give (in § 3) algorithms which decide whether a partially ordered set is a (lower or upper) semi......-lattice, and whether a lattice has distributive, modular, and Boolean properties. Finally (in § 4) we give Algol realizations of the various algorithms....
Controller Design of Complex System Based on Nonlinear Strength
Directory of Open Access Journals (Sweden)
Rongjun Mu
2015-01-01
Full Text Available This paper presents a new idea of controller design for complex systems. The nonlinearity index method was first developed for error propagation of nonlinear system. The nonlinearity indices access the boundary between the strong and the weak nonlinearities of the system model. The algorithm of nonlinearity index according to engineering application is first proposed in this paper. Applying this method on nonlinear systems is an effective way to measure the nonlinear strength of dynamics model over the full flight envelope. The nonlinearity indices access the boundary between the strong and the weak nonlinearities of system model. According to the different nonlinear strength of dynamical model, the control system is designed. The simulation time of dynamical complex system is selected by the maximum value of dynamic nonlinearity indices. Take a missile as example; dynamical system and control characteristic of missile are simulated. The simulation results show that the method is correct and appropriate.
Ruszczynski, Andrzej
2011-01-01
Optimization is one of the most important areas of modern applied mathematics, with applications in fields from engineering and economics to finance, statistics, management science, and medicine. While many books have addressed its various aspects, Nonlinear Optimization is the first comprehensive treatment that will allow graduate students and researchers to understand its modern ideas, principles, and methods within a reasonable time, but without sacrificing mathematical precision. Andrzej Ruszczynski, a leading expert in the optimization of nonlinear stochastic systems, integrates the theory and the methods of nonlinear optimization in a unified, clear, and mathematically rigorous fashion, with detailed and easy-to-follow proofs illustrated by numerous examples and figures. The book covers convex analysis, the theory of optimality conditions, duality theory, and numerical methods for solving unconstrained and constrained optimization problems. It addresses not only classical material but also modern top...
Nonlinear filtering for LIDAR signal processing
Directory of Open Access Journals (Sweden)
D. G. Lainiotis
1996-01-01
Full Text Available LIDAR (Laser Integrated Radar is an engineering problem of great practical importance in environmental monitoring sciences. Signal processing for LIDAR applications involves highly nonlinear models and consequently nonlinear filtering. Optimal nonlinear filters, however, are practically unrealizable. In this paper, the Lainiotis's multi-model partitioning methodology and the related approximate but effective nonlinear filtering algorithms are reviewed and applied to LIDAR signal processing. Extensive simulation and performance evaluation of the multi-model partitioning approach and its application to LIDAR signal processing shows that the nonlinear partitioning methods are very effective and significantly superior to the nonlinear extended Kalman filter (EKF, which has been the standard nonlinear filter in past engineering applications.
Nonlinear positron acoustic solitary waves
International Nuclear Information System (INIS)
Tribeche, Mouloud; Aoutou, Kamel; Younsi, Smain; Amour, Rabia
2009-01-01
The problem of nonlinear positron acoustic solitary waves involving the dynamics of mobile cold positrons is addressed. A theoretical work is presented to show their existence and possible realization in a simple four-component plasma model. The results should be useful for the understanding of the localized structures that may occur in space and laboratory plasmas as new sources of cold positrons are now well developed.
Directory of Open Access Journals (Sweden)
Ye-Wei Zhang
2017-01-01
Full Text Available This paper presents a novel design by integrating geometrical and material nonlinear energy sink (NES with a piezoelectric-based vibration energy harvester under shock excitation, which can realize vibration control and energy harvesting. The nonlinear spring and hysteresis behavior of the NES could reflect geometrical and material nonlinearity, respectively. Two configurations of the piezoelectric device, including the piezoelectric element embedded between the NES mass and the single-degree-of-freedom system or ground, are utilised to examine the energy dissipated by damper and hysteresis behavior of NES and the energy harvested by the piezoelectric element. Similar numerical research methods of Runge-Kutta algorithm are used to investigate the two configurations. The energy transaction measure (ETM is adopted to examine the instantaneous energy transaction between the primary and the NES-piezoelectricity system. And it demonstrates that the dissipated and harvested energy transaction is transferred from the primary system to the NES-piezoelectricity system and the instantaneous transaction of mechanical energy occupies a major part of the energy of transaction. Both figurations could realize vibration control efficiently.
Nonlinear dynamical system approaches towards neural prosthesis
International Nuclear Information System (INIS)
Torikai, Hiroyuki; Hashimoto, Sho
2011-01-01
An asynchronous discrete-state spiking neurons is a wired system of shift registers that can mimic nonlinear dynamics of an ODE-based neuron model. The control parameter of the neuron is the wiring pattern among the registers and thus they are suitable for on-chip learning. In this paper an asynchronous discrete-state spiking neuron is introduced and its typical nonlinear phenomena are demonstrated. Also, a learning algorithm for a set of neurons is presented and it is demonstrated that the algorithm enables the set of neurons to reconstruct nonlinear dynamics of another set of neurons with unknown parameter values. The learning function is validated by FPGA experiments.
Experimental verification of transient nonlinear acoustical holography.
Jing, Yun; Cannata, Jonathan; Wang, Tianren
2013-05-01
This paper presents an experimental study on nonlinear transient acoustical holography. The validity and effectiveness of a recently proposed nonlinear transient acoustical holography algorithm is evaluated in the presence of noise. The acoustic field measured on a post-focal plane of a high-intensity focused transducer is backward projected to reconstruct the pressure distributions on the focal and a pre-focal plane, which are shown to be in good agreement with the measurement. In contrast, the conventional linear holography produces erroneous results in this case where the nonlinearity involved is strong. Forward acoustic field projection was also carried out to further verify the algorithm.
DEFF Research Database (Denmark)
Mahnke, Martina; Uprichard, Emma
2014-01-01
Imagine sailing across the ocean. The sun is shining, vastness all around you. And suddenly [BOOM] you’ve hit an invisible wall. Welcome to the Truman Show! Ever since Eli Pariser published his thoughts on a potential filter bubble, this movie scenario seems to have become reality, just with slight...... changes: it’s not the ocean, it’s the internet we’re talking about, and it’s not a TV show producer, but algorithms that constitute a sort of invisible wall. Building on this assumption, most research is trying to ‘tame the algorithmic tiger’. While this is a valuable and often inspiring approach, we...
Photonic crystal Fano resonances for realizing optical switches, lasers and non-reciprocal elements
DEFF Research Database (Denmark)
Bekele, Dagmawi Alemayehu; Yu, Yi; Hu, Hao
2017-01-01
structure in combination with cavity-enhanced nonlinearity can be used to realize non-reciprocal transmission at ultra-low power and with large bandwidth. A novel type of laser structure, denoted a Fano laser, is discussed in which one of the mirrors is based on a Fano resonance. Finally, the design...
Minimal-memory realization of pearl-necklace encoders of general quantum convolutional codes
International Nuclear Information System (INIS)
Houshmand, Monireh; Hosseini-Khayat, Saied
2011-01-01
Quantum convolutional codes, like their classical counterparts, promise to offer higher error correction performance than block codes of equivalent encoding complexity, and are expected to find important applications in reliable quantum communication where a continuous stream of qubits is transmitted. Grassl and Roetteler devised an algorithm to encode a quantum convolutional code with a ''pearl-necklace'' encoder. Despite their algorithm's theoretical significance as a neat way of representing quantum convolutional codes, it is not well suited to practical realization. In fact, there is no straightforward way to implement any given pearl-necklace structure. This paper closes the gap between theoretical representation and practical implementation. In our previous work, we presented an efficient algorithm to find a minimal-memory realization of a pearl-necklace encoder for Calderbank-Shor-Steane (CSS) convolutional codes. This work is an extension of our previous work and presents an algorithm for turning a pearl-necklace encoder for a general (non-CSS) quantum convolutional code into a realizable quantum convolutional encoder. We show that a minimal-memory realization depends on the commutativity relations between the gate strings in the pearl-necklace encoder. We find a realization by means of a weighted graph which details the noncommutative paths through the pearl necklace. The weight of the longest path in this graph is equal to the minimal amount of memory needed to implement the encoder. The algorithm has a polynomial-time complexity in the number of gate strings in the pearl-necklace encoder.
Amorphous graphene: a realization of Zachariasen’s glass
International Nuclear Information System (INIS)
Kumar, Avishek; Thorpe, M F; Wilson, Mark
2012-01-01
Amorphous graphene is a realization of a two-dimensional Zachariasen glass as first proposed 80 years ago. Planar continuous random networks of this archetypal two-dimensional network are generated by two complementary simulation methods. In the first, a Monte Carlo bond switching algorithm is employed to systematically amorphize a crystalline graphene sheet. In the second, molecular dynamics simulations are utilized to quench from the high temperature liquid state. The two approaches lead to similar results as detailed here, through the pair distribution function and the associated diffraction pattern. Details of the structure, including ring statistics and angular distortions, are shown to be sensitive to preparation conditions, and await experimental confirmation.
On one method of realization of commutation relation algebra
International Nuclear Information System (INIS)
Sveshnikov, K.A.
1983-01-01
Method for constructing the commulation relation representations based on the purely algebraic construction of joined algebraic representation with specially selected composition law has been suggested9 Purely combinatorial construction realizing commulation relations representation has been obtained proceeding from formal equivalence of operatopr action on vector and adding a simbol to a sequences of symbols. The above method practically has the structure of calculating algorithm, which assigns some rule of ''word'' formation of an initial set of ''letters''. In other words, a computer language with definite relations between words (an analogy between quantum mechanics and computer linguistics has been applied)
Zhang, Yajun; Chai, Tianyou; Wang, Hong; Wang, Dianhui; Chen, Xinkai
2018-06-01
Complex industrial processes are multivariable and generally exhibit strong coupling among their control loops with heavy nonlinear nature. These make it very difficult to obtain an accurate model. As a result, the conventional and data-driven control methods are difficult to apply. Using a twin-tank level control system as an example, a novel multivariable decoupling control algorithm with adaptive neural-fuzzy inference system (ANFIS)-based unmodeled dynamics (UD) compensation is proposed in this paper for a class of complex industrial processes. At first, a nonlinear multivariable decoupling controller with UD compensation is introduced. Different from the existing methods, the decomposition estimation algorithm using ANFIS is employed to estimate the UD, and the desired estimating and decoupling control effects are achieved. Second, the proposed method does not require the complicated switching mechanism which has been commonly used in the literature. This significantly simplifies the obtained decoupling algorithm and its realization. Third, based on some new lemmas and theorems, the conditions on the stability and convergence of the closed-loop system are analyzed to show the uniform boundedness of all the variables. This is then followed by the summary on experimental tests on a heavily coupled nonlinear twin-tank system that demonstrates the effectiveness and the practicability of the proposed method.
Evaluation of the performance of different firefly algorithms to the ...
African Journals Online (AJOL)
of firefly algorithms are applied to solve the nonlinear ELD problem. ... problem using those recent variants and the classical firefly algorithm for different test cases. Efficiency ...... International Journal of Machine. Learning and Computing, Vol.
Filter Pattern Search Algorithms for Mixed Variable Constrained Optimization Problems
National Research Council Canada - National Science Library
Abramson, Mark A; Audet, Charles; Dennis, Jr, J. E
2004-01-01
.... This class combines and extends the Audet-Dennis Generalized Pattern Search (GPS) algorithms for bound constrained mixed variable optimization, and their GPS-filter algorithms for general nonlinear constraints...
Corrugated Membrane Nonlinear Deformation Process Calculation
Directory of Open Access Journals (Sweden)
A. S. Nikolaeva
2015-01-01
Full Text Available Elastic elements are widely used in instrumentation. They are used to create a particular interference between the parts, for accumulating mechanical energy, as the motion transmission elements, elastic supports, and sensing elements of measuring devices. Device reliability and quality depend on the calculation accuracy of the elastic elements. A corrugated membrane is rather common embodiment of the elastic element.The corrugated membrane properties depend largely on its profile i.e. a generatrix of the meridian surface.Unlike other types of pressure elastic members (bellows, tube spring, the elastic characteristics of which are close to linear, an elastic characteristic of the corrugated membrane (typical movement versus external load is nonlinear. Therefore, the corrugated membranes can be used to measure quantities, nonlinearly related to the pressure (e.g., aircraft air speed, its altitude, pipeline fluid or gas flow rate. Another feature of the corrugated membrane is that significant movements are possible within the elastic material state. However, a significant non-linearity of membrane characteristics leads to severe complicated calculation.This article is aimed at calculating the corrugated membrane to obtain the elastic characteristics and the deformed shape of the membrane meridian, as well as at investigating the processes of buckling. As the calculation model, a thin-walled axisymmetric shell rotation is assumed. The material properties are linearly elastic. We consider a corrugated membrane of sinusoidal profile. The membrane load is a uniform pressure.The algorithm for calculating the mathematical model of an axisymmetric corrugated membrane of constant thickness, based on the Reissner’s theory of elastic thin shells, was realized as the author's program in C language. To solve the nonlinear problem were used a method of changing the subspace of control parameters, developed by S.S., Gavriushin, and a parameter marching method
Nonlinear dynamics aspects of particle accelerators
International Nuclear Information System (INIS)
Jowett, J.M.; Turner, S.; Month, M.
1986-01-01
These proceedings contain the lectures presented at the named winter school. They deal with the application of dynamical systems to accelerator theory. Especially considered are the statistical description of charged-beam plasmas, integrable and nonintegrable Hamiltonian systems, single particle dynamics and nonlinear resonances in circular accelerators, nonlinear dynamics aspects of modern storage rings, nonlinear beam-beam resonances, synchro-betatron resonances, observations of the beam-beam interactions, the dynamics of the beam-beam interactions, beam-beam simulations, the perturbation method in nonlinear dynamics, theories of statistical equilibrium in electron-positron storage rings, nonlinear dissipative phenomena in electron storage rings, the dynamical aperture, the transition to chaos for area-preserving maps, special processors for particle tracking, algorithms for tracking of charged particles in circular accelerators, the breakdown of stability, and a personal perspective of nonlinear dynamics. (HSI)
Introduction to nonlinear finite element analysis
Kim, Nam-Ho
2015-01-01
This book introduces the key concepts of nonlinear finite element analysis procedures. The book explains the fundamental theories of the field and provides instructions on how to apply the concepts to solving practical engineering problems. Instead of covering many nonlinear problems, the book focuses on three representative problems: nonlinear elasticity, elastoplasticity, and contact problems. The book is written independent of any particular software, but tutorials and examples using four commercial programs are included as appendices: ANSYS, NASTRAN, ABAQUS, and MATLAB. In particular, the MATLAB program includes all source codes so that students can develop their own material models, or different algorithms. This book also: · Presents clear explanations of nonlinear finite element analysis for elasticity, elastoplasticity, and contact problems · Includes many informative examples of nonlinear analyses so that students can clearly understand the nonlinear theory · ...
Nonlinear dynamics aspects of particle accelerators. Proceedings
Energy Technology Data Exchange (ETDEWEB)
Jowett, J M; Turner, S; Month, M
1986-01-01
These proceedings contain the lectures presented at the named winter school. They deal with the application of dynamical systems to accelerator theory. Especially considered are the statistical description of charged-beam plasmas, integrable and nonintegrable Hamiltonian systems, single particle dynamics and nonlinear resonances in circular accelerators, nonlinear dynamics aspects of modern storage rings, nonlinear beam-beam resonances, synchro-betatron resonances, observations of the beam-beam interactions, the dynamics of the beam-beam interactions, beam-beam simulations, the perturbation method in nonlinear dynamics, theories of statistical equilibrium in electron-positron storage rings, nonlinear dissipative phenomena in electron storage rings, the dynamical aperture, the transition to chaos for area-preserving maps, special processors for particle tracking, algorithms for tracking of charged particles in circular accelerators, the breakdown of stability, and a personal perspective of nonlinear dynamics. (HSI).
Optimal groundwater remediation using artificial neural networks and the genetic algorithm
Energy Technology Data Exchange (ETDEWEB)
Rogers, Leah L. [Stanford Univ., CA (United States)
1992-08-01
An innovative computational approach for the optimization of groundwater remediation is presented which uses artificial neural networks (ANNs) and the genetic algorithm (GA). In this approach, the ANN is trained to predict an aspect of the outcome of a flow and transport simulation. Then the GA searches through realizations or patterns of pumping and uses the trained network to predict the outcome of the realizations. This approach has advantages of parallel processing of the groundwater simulations and the ability to ``recycle`` or reuse the base of knowledge formed by these simulations. These advantages offer reduction of computational burden of the groundwater simulations relative to a more conventional approach which uses nonlinear programming (NLP) with a quasi-newtonian search. Also the modular nature of this approach facilitates substitution of different groundwater simulation models.
Optimal groundwater remediation using artificial neural networks and the genetic algorithm
International Nuclear Information System (INIS)
Rogers, L.L.
1992-08-01
An innovative computational approach for the optimization of groundwater remediation is presented which uses artificial neural networks (ANNs) and the genetic algorithm (GA). In this approach, the ANN is trained to predict an aspect of the outcome of a flow and transport simulation. Then the GA searches through realizations or patterns of pumping and uses the trained network to predict the outcome of the realizations. This approach has advantages of parallel processing of the groundwater simulations and the ability to ''recycle'' or reuse the base of knowledge formed by these simulations. These advantages offer reduction of computational burden of the groundwater simulations relative to a more conventional approach which uses nonlinear programming (NLP) with a quasi-newtonian search. Also the modular nature of this approach facilitates substitution of different groundwater simulation models
Engineering high-order nonlinear dissipation for quantum superconducting circuits
Mundhada, S. O.; Grimm, A.; Touzard, S.; Shankar, S.; Minev, Z. K.; Vool, U.; Mirrahimi, M.; Devoret, M. H.
Engineering nonlinear driven-dissipative processes is essential for quantum control. In the case of a harmonic oscillator, nonlinear dissipation can stabilize a decoherence-free manifold, leading to protected quantum information encoding. One possible approach to implement such nonlinear interactions is to combine the nonlinearities provided by Josephson circuits with parametric pump drives. However, it is usually hard to achieve strong nonlinearities while avoiding undesired couplings. Here we propose a scheme to engineer a four-photon drive and dissipation in a harmonic oscillator by cascading experimentally demonstrated two-photon processes. We also report experimental progress towards realization of such a scheme. Work supported by: ARO, ONR, AFOSR and YINQE.
Different realizations of Cooper-Frye sampling with conservation laws
Schwarz, C.; Oliinychenko, D.; Pang, L.-G.; Ryu, S.; Petersen, H.
2018-01-01
Approaches based on viscous hydrodynamics for the hot and dense stage and hadronic transport for the final dilute rescattering stage are successfully applied to the dynamic description of heavy ion reactions at high beam energies. One crucial step in such hybrid approaches is the so-called particlization, which is the transition between the hydrodynamic description and the microscopic degrees of freedom. For this purpose, individual particles are sampled on the Cooper-Frye hypersurface. In this work, four different realizations of the sampling algorithms are compared, with three of them incorporating the global conservation laws of quantum numbers in each event. The algorithms are compared within two types of scenarios: a simple ‘box’ hypersurface consisting of only one static cell and a typical particlization hypersurface for Au+Au collisions at \\sqrt{{s}{NN}}=200 {GeV}. For all algorithms the mean multiplicities (or particle spectra) remain unaffected by global conservation laws in the case of large volumes. In contrast, the fluctuations of the particle numbers are affected considerably. The fluctuations of the newly developed SPREW algorithm based on the exponential weight, and the recently suggested SER algorithm based on ensemble rejection, are smaller than those without conservation laws and agree with the expectation from the canonical ensemble. The previously applied mode sampling algorithm produces dramatically larger fluctuations than expected in the corresponding microcanonical ensemble, and therefore should be avoided in fluctuation studies. This study might be of interest for the investigation of particle fluctuations and correlations, e.g. the suggested signatures for a phase transition or a critical endpoint, in hybrid approaches that are affected by global conservation laws.
De Götzen , Amalia; Mion , Luca; Tache , Olivier
2007-01-01
International audience; We call sound algorithms the categories of algorithms that deal with digital sound signal. Sound algorithms appeared in the very infancy of computer. Sound algorithms present strong specificities that are the consequence of two dual considerations: the properties of the digital sound signal itself and its uses, and the properties of auditory perception.
Wang, Lui; Bayer, Steven E.
1991-01-01
Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solving methods) based loosely on the processes of natural genetics and Darwinian survival of the fittest. Basic genetic algorithms concepts are introduced, genetic algorithm applications are introduced, and results are presented from a project to develop a software tool that will enable the widespread use of genetic algorithm technology.
Real-time simulation of the nonlinear visco-elastic deformations of soft tissues.
Basafa, Ehsan; Farahmand, Farzam
2011-05-01
Mass-spring-damper (MSD) models are often used for real-time surgery simulation due to their fast response and fairly realistic deformation replication. An improved real time simulation model of soft tissue deformation due to a laparoscopic surgical indenter was developed and tested. The mechanical realization of conventional MSD models was improved using nonlinear springs and nodal dampers, while their high computational efficiency was maintained using an adapted implicit integration algorithm. New practical algorithms for model parameter tuning, collision detection, and simulation were incorporated. The model was able to replicate complex biological soft tissue mechanical properties under large deformations, i.e., the nonlinear and viscoelastic behaviors. The simulated response of the model after tuning of its parameters to the experimental data of a deer liver sample, closely tracked the reference data with high correlation and maximum relative differences of less than 5 and 10%, for the tuning and testing data sets respectively. Finally, implementation of the proposed model and algorithms in a graphical environment resulted in a real-time simulation with update rates of 150 Hz for interactive deformation and haptic manipulation, and 30 Hz for visual rendering. The proposed real time simulation model of soft tissue deformation due to a laparoscopic surgical indenter was efficient, realistic, and accurate in ex vivo testing. This model is a suitable candidate for testing in vivo during laparoscopic surgery.
Numerical realization of the variational method for generating self-trapped beams.
Duque, Erick I; Lopez-Aguayo, Servando; Malomed, Boris A
2018-03-19
We introduce a numerical variational method based on the Rayleigh-Ritz optimization principle for predicting two-dimensional self-trapped beams in nonlinear media. This technique overcomes the limitation of the traditional variational approximation in performing analytical Lagrangian integration and differentiation. Approximate soliton solutions of a generalized nonlinear Schrödinger equation are obtained, demonstrating robustness of the beams of various types (fundamental, vortices, multipoles, azimuthons) in the course of their propagation. The algorithm offers possibilities to produce more sophisticated soliton profiles in general nonlinear models.
Numerical realization of the variational method for generating self-trapped beams
Duque, Erick I.; Lopez-Aguayo, Servando; Malomed, Boris A.
2018-03-01
We introduce a numerical variational method based on the Rayleigh-Ritz optimization principle for predicting two-dimensional self-trapped beams in nonlinear media. This technique overcomes the limitation of the traditional variational approximation in performing analytical Lagrangian integration and differentiation. Approximate soliton solutions of a generalized nonlinear Schr\\"odinger equation are obtained, demonstrating robustness of the beams of various types (fundamental, vortices, multipoles, azimuthons) in the course of their propagation. The algorithm offers possibilities to produce more sophisticated soliton profiles in general nonlinear models.
Cao, Jianfang; Cui, Hongyan; Shi, Hao; Jiao, Lijuan
2016-01-01
A back-propagation (BP) neural network can solve complicated random nonlinear mapping problems; therefore, it can be applied to a wide range of problems. However, as the sample size increases, the time required to train BP neural networks becomes lengthy. Moreover, the classification accuracy decreases as well. To improve the classification accuracy and runtime efficiency of the BP neural network algorithm, we proposed a parallel design and realization method for a particle swarm optimization (PSO)-optimized BP neural network based on MapReduce on the Hadoop platform using both the PSO algorithm and a parallel design. The PSO algorithm was used to optimize the BP neural network's initial weights and thresholds and improve the accuracy of the classification algorithm. The MapReduce parallel programming model was utilized to achieve parallel processing of the BP algorithm, thereby solving the problems of hardware and communication overhead when the BP neural network addresses big data. Datasets on 5 different scales were constructed using the scene image library from the SUN Database. The classification accuracy of the parallel PSO-BP neural network algorithm is approximately 92%, and the system efficiency is approximately 0.85, which presents obvious advantages when processing big data. The algorithm proposed in this study demonstrated both higher classification accuracy and improved time efficiency, which represents a significant improvement obtained from applying parallel processing to an intelligent algorithm on big data.
Nonlinear Elliptic Differential Equations with Multivalued Nonlinearities
Indian Academy of Sciences (India)
In this paper we study nonlinear elliptic boundary value problems with monotone and nonmonotone multivalued nonlinearities. First we consider the case of monotone nonlinearities. In the first result we assume that the multivalued nonlinearity is defined on all R R . Assuming the existence of an upper and of a lower ...
Product Realization | College of Engineering & Applied Science
Olympiad Girls Who Code Club FIRST Tech Challenge NSF I-Corps Site of Southeastern Wisconsin UW-Milwaukee Product Realization Course Companies need time and talent to develop new product prototypes. Students need
Modelling and Forecasting Multivariate Realized Volatility
DEFF Research Database (Denmark)
Halbleib, Roxana; Voev, Valeri
2011-01-01
This paper proposes a methodology for dynamic modelling and forecasting of realized covariance matrices based on fractionally integrated processes. The approach allows for flexible dependence patterns and automatically guarantees positive definiteness of the forecast. We provide an empirical appl...
Researchers Realize Major Breakthrough in Understanding Endometriosis
... 16, 2014 Researchers Realize Major Breakthrough in Understanding Endometriosis For a disease that affects an estimated 6 ... 10% of women, surprisingly little is known about endometriosis — a disorder that causes uterine tissue to grow ...
Matrix realization of string algebra axioms and conditions of invariance
International Nuclear Information System (INIS)
Babichev, L.F.; Kuvshinov, V.I.; Fedorov, F.I.
1990-01-01
The matrix representations of Witten's and B-algebras of the field string theory in finite dimensional space of the ghost states are suggested for the case of Virasoro algebra truncated to its SU(1,1) subalgebra. In this case all algebraic operations of Witten's and B-algebras are realized in explicit form as some matrix operations in the graded complex vector space. The structure of string action coincides with the universal non-linear cubic matrix form of action for the gauge field theories. These representations lead to matrix conditions of theory invariance which can be used for finding of the explicit form of corresponding operators of the string algebras. (author)
Dynamical realizations of l-conformal Newton–Hooke group
International Nuclear Information System (INIS)
Galajinsky, Anton; Masterov, Ivan
2013-01-01
The method of nonlinear realizations and the technique previously developed in [A. Galajinsky, I. Masterov, Nucl. Phys. B 866 (2013) 212, (arXiv:1208.1403)] are used to construct a dynamical system without higher derivative terms, which holds invariant under the l-conformal Newton–Hooke group. A configuration space of the model involves coordinates, which parametrize a particle moving in d spatial dimensions and a conformal mode, which gives rise to an effective external field. The dynamical system describes a generalized multi-dimensional oscillator, which undergoes accelerated/decelerated motion in an ellipse in accord with evolution of the conformal mode. Higher derivative formulations are discussed as well. It is demonstrated that the multi-dimensional Pais–Uhlenbeck oscillator enjoys the l=3/2 -conformal Newton–Hooke symmetry for a particular choice of its frequencies
Learning, Realizability and Games in Classical Arithmetic
Aschieri, Federico
2010-12-01
In this dissertation we provide mathematical evidence that the concept of learning can be used to give a new and intuitive computational semantics of classical proofs in various fragments of Predicative Arithmetic. First, we extend Kreisel modified realizability to a classical fragment of first order Arithmetic, Heyting Arithmetic plus EM1 (Excluded middle axiom restricted to Sigma^0_1 formulas). We introduce a new realizability semantics we call "Interactive Learning-Based Realizability". Our realizers are self-correcting programs, which learn from their errors and evolve through time. Secondly, we extend the class of learning based realizers to a classical version PCFclass of PCF and, then, compare the resulting notion of realizability with Coquand game semantics and prove a full soundness and completeness result. In particular, we show there is a one-to-one correspondence between realizers and recursive winning strategies in the 1-Backtracking version of Tarski games. Third, we provide a complete and fully detailed constructive analysis of learning as it arises in learning based realizability for HA+EM1, Avigad's update procedures and epsilon substitution method for Peano Arithmetic PA. We present new constructive techniques to bound the length of learning processes and we apply them to reprove - by means of our theory - the classic result of Godel that provably total functions of PA can be represented in Godel's system T. Last, we give an axiomatization of the kind of learning that is needed to computationally interpret Predicative classical second order Arithmetic. Our work is an extension of Avigad's and generalizes the concept of update procedure to the transfinite case. Transfinite update procedures have to learn values of transfinite sequences of non computable functions in order to extract witnesses from classical proofs.
Realization of FRC interior and exterior furniture
Šonka, Š.; Frantová, M.; Štemberk, P.; Havrda, J.; Janouch, P.
2017-09-01
This article deals with the implementation of fibre reinforced concrete for interior and exterior furniture. The use of fibre reinforced concrete for non-traditional and small structures brings some specifics in design and realization. These are, in particular, the design of a suitable mixture, the choice of the shape of the structure in relation to the technological possibilities of realization, the static effects and finally the actual production of the element.
The linguistic realization of information packaging
Vallduví, Enric; Engdahl, Elisabet
1996-01-01
There is increasing awareness of the large degree of crosslinguistic diversity involved in the structural realization of information packaging (or information structure). Whereas English and many Germanic languages primarily exploit intonation for informational purposes, in other languages, like Catalan, syntax plays the primary role in the realization of information packaging and intonation is reduced to a secondary role. In yet another group of languages the primary structural correlate is ...
Identification of Nonlinear Dynamic Systems Possessing Some Non-linearities
Directory of Open Access Journals (Sweden)
Y. N. Pavlov
2015-01-01
Full Text Available The subject of this work is the problem of identification of nonlinear dynamic systems based on the experimental data obtained by applying test signals to the system. The goal is to determinate coefficients of differential equations of systems by experimental frequency hodographs and separate similar, but different, in essence, forces: dissipative forces with the square of the first derivative in the motion equations and dissipative force from the action of dry friction. There was a proposal to use the harmonic linearization method to approximate each of the nonlinearity of "quadratic friction" and "dry friction" by linear friction with the appropriate harmonic linearization coefficient.Assume that a frequency transfer function of the identified system has a known form. Assume as well that there are disturbances while obtaining frequency characteristics of the realworld system. As a result, the points of experimentally obtained hodograph move randomly. Searching for solution of the identification problem was in the hodograph class, specified by the system model, which has the form of the frequency transfer function the same as the form of the frequency transfer function of the system identified. Minimizing a proximity criterion (measure of the experimentally obtained system hodograph and the system hodograph model for all the experimental points described and previously published by one of the authors allowed searching for the unknown coefficients of the frequenc ransfer function of the system model. The paper shows the possibility to identify a nonlinear dynamic system with multiple nonlinearities, obtained on the experimental samples of the frequency system hodograph. The proposed algorithm allows to select the nonlinearity of the type "quadratic friction" and "dry friction", i.e. also in the case where the nonlinearity is dependent on the same dynamic parameter, in particular, on the derivative of the system output value. For the dynamic
International Nuclear Information System (INIS)
Liu Chunliang; Xie Xi; Chen Yinbao
1991-01-01
The universal nonlinear dynamic system equation is equivalent to its nonlinear Volterra's integral equation, and any order approximate analytical solution of the nonlinear Volterra's integral equation is obtained by exact analytical method, thus giving another derivation procedure as well as another computation algorithm for the solution of the universal nonlinear dynamic system equation
New algorithms for parallel MRI
International Nuclear Information System (INIS)
Anzengruber, S; Ramlau, R; Bauer, F; Leitao, A
2008-01-01
Magnetic Resonance Imaging with parallel data acquisition requires algorithms for reconstructing the patient's image from a small number of measured lines of the Fourier domain (k-space). In contrast to well-known algorithms like SENSE and GRAPPA and its flavors we consider the problem as a non-linear inverse problem. However, in order to avoid cost intensive derivatives we will use Landweber-Kaczmarz iteration and in order to improve the overall results some additional sparsity constraints.
Realization of an X-Band RF System for LCLS
McIntosh, Peter; Brooks, William; Emma, Paul; Rago, Carl
2005-01-01
A single X-band (11.424 GHz) accelerating structure is to be incorporated in the LCLS Linac design to linearize the energy-time correlation (or gradient) across each bunch, features which originate in the preceding accelerating structures (L0 and L1). This harmonic RF system will operate near the negative RF crest to decelerate the beam, reducing these non-linear components of the correlation, providing a more efficient compression in the downstream bunch compressor chicanes (BC1 and BC2). These non-linear correlation components, if allowed to grow, would lead to Coherent Synchrotron Radiation (CSR) instabilities in the chicanes, effectively destroying the coherence of the photon radiation in the main LCLS undulator. The many years devoted at SLAC in the development of X-band RF components for the NLC/JLC linear collider project, has enabled the technical and financial realization of such an RF system for LCLS. This paper details the requirements for the X-band system and the proposed scheme planned for achie...
Joux, Antoine
2009-01-01
Illustrating the power of algorithms, Algorithmic Cryptanalysis describes algorithmic methods with cryptographically relevant examples. Focusing on both private- and public-key cryptographic algorithms, it presents each algorithm either as a textual description, in pseudo-code, or in a C code program.Divided into three parts, the book begins with a short introduction to cryptography and a background chapter on elementary number theory and algebra. It then moves on to algorithms, with each chapter in this section dedicated to a single topic and often illustrated with simple cryptographic applic
Numerical study of propagation properties of surface plasmon polaritons in nonlinear media
Sagor, Rakibul Hasan; Ghulam Saber, Md.; Alsunaidi, Mohammad
2016-01-01
We present a time-domain algorithm for simulating nonlinear propagation of surface plasmon polaritons (SPPs) in chalcogenide glass. Due to the high non-linearity property and strong dispersion and confinement chalcogenide glasses are widely known
Tracking Positioning Algorithm for Direction of Arrival Based on Direction Lock Loop
Directory of Open Access Journals (Sweden)
Xiu-Zhi Cheng
2015-06-01
Full Text Available In order to solve the problem of poor real-time performance, low accuracy and high computational complexity in the traditional process of locating and tracking of Direction of Arrival (DOA of moving targets, this paper proposes a DOA algorithm based on the Direction Lock Loop (DILL which adopts Lock Loop structure to realize the estimation and location of DOA and can adjust the direction automatically along with the changes of a signal’s angular variation to track the position of the signal. Meanwhile, to reduce the influence of nonlinearity and noise on its performance, the UKF filter is designed for eliminating interference of the estimated target signal to improve accuracy of the signal tracking and stability of the system. Simulation results prove that the algorithm can not only get a high resolution DOA estimate signal, but can also locate and track multiple mobile targets effectively with enhanced accuracy, efficiency and stability.
Elsheikh, Ahmed H.; Wheeler, Mary Fanett; Hoteit, Ibrahim
2013-01-01
is parameterized using an overcomplete dictionary of basis functions built using the K-SVD algorithm. The proposed algorithm is the first ensemble based algorithm that tackels the sparse nonlinear parameter estimation problem. © 2013 Elsevier Ltd.
Yee, H. C.; Sweby, P. K.; Griffiths, D. F.
1990-01-01
Spurious stable as well as unstable steady state numerical solutions, spurious asymptotic numerical solutions of higher period, and even stable chaotic behavior can occur when finite difference methods are used to solve nonlinear differential equations (DE) numerically. The occurrence of spurious asymptotes is independent of whether the DE possesses a unique steady state or has additional periodic solutions and/or exhibits chaotic phenomena. The form of the nonlinear DEs and the type of numerical schemes are the determining factor. In addition, the occurrence of spurious steady states is not restricted to the time steps that are beyond the linearized stability limit of the scheme. In many instances, it can occur below the linearized stability limit. Therefore, it is essential for practitioners in computational sciences to be knowledgeable about the dynamical behavior of finite difference methods for nonlinear scalar DEs before the actual application of these methods to practical computations. It is also important to change the traditional way of thinking and practices when dealing with genuinely nonlinear problems. In the past, spurious asymptotes were observed in numerical computations but tended to be ignored because they all were assumed to lie beyond the linearized stability limits of the time step parameter delta t. As can be seen from the study, bifurcations to and from spurious asymptotic solutions and transitions to computational instability not only are highly scheme dependent and problem dependent, but also initial data and boundary condition dependent, and not limited to time steps that are beyond the linearized stability limit.
Recent advances in multiparametric nonlinear programming
Domí nguez, Luis F.; Narciso, Diogo A.; Pistikopoulos, Efstratios N.
2010-01-01
In this paper, we present recent developments in multiparametric nonlinear programming. For the case of convex problems, we highlight key issues regarding the full characterization of the parametric solution space and we discuss, through an illustrative example problem, four alternative state-of-the-art multiparametric nonlinear programming algorithms. We also identify a number of main challenges for the non-convex case and highlight future research directions. © 2009 Elsevier Ltd. All rights reserved.
Recent advances in multiparametric nonlinear programming
Domínguez, Luis F.
2010-05-01
In this paper, we present recent developments in multiparametric nonlinear programming. For the case of convex problems, we highlight key issues regarding the full characterization of the parametric solution space and we discuss, through an illustrative example problem, four alternative state-of-the-art multiparametric nonlinear programming algorithms. We also identify a number of main challenges for the non-convex case and highlight future research directions. © 2009 Elsevier Ltd. All rights reserved.
Feedforward Nonlinear Control Using Neural Gas Network
Machón-González, Iván; López-García, Hilario
2017-01-01
Nonlinear systems control is a main issue in control theory. Many developed applications suffer from a mathematical foundation not as general as the theory of linear systems. This paper proposes a control strategy of nonlinear systems with unknown dynamics by means of a set of local linear models obtained by a supervised neural gas network. The proposed approach takes advantage of the neural gas feature by which the algorithm yields a very robust clustering procedure. The direct model of the ...
Hougardy, Stefan
2016-01-01
Algorithms play an increasingly important role in nearly all fields of mathematics. This book allows readers to develop basic mathematical abilities, in particular those concerning the design and analysis of algorithms as well as their implementation. It presents not only fundamental algorithms like the sieve of Eratosthenes, the Euclidean algorithm, sorting algorithms, algorithms on graphs, and Gaussian elimination, but also discusses elementary data structures, basic graph theory, and numerical questions. In addition, it provides an introduction to programming and demonstrates in detail how to implement algorithms in C++. This textbook is suitable for students who are new to the subject and covers a basic mathematical lecture course, complementing traditional courses on analysis and linear algebra. Both authors have given this "Algorithmic Mathematics" course at the University of Bonn several times in recent years.
Realization of THz Band Mixer Using Graphene
Directory of Open Access Journals (Sweden)
E. Ghasemi Mizuji
2014-05-01
Full Text Available In this article a new method for creating mixer component in infrared and THz is suggested. Since the nonlinear property of admittance creates frequency components that do not exist in the input signal and the electrical conductivity is associated with admittance, in our work we have proven and simulated that the nonlinear property of graphene admittance can produce mixer component. The simulation results show that the mixer component is larger than other components, therefore the mixer works properly. Because of nano scale of graphene structure, this method paves the road to achieve super compact circuits.
Perspectives on Nonlinear Filtering
Law, Kody
2015-01-01
The solution to the problem of nonlinear filtering may be given either as an estimate of the signal (and ideally some measure of concentration), or as a full posterior distribution. Similarly, one may evaluate the fidelity of the filter either by its ability to track the signal or its proximity to the posterior filtering distribution. Hence, the field enjoys a lively symbiosis between probability and control theory, and there are plenty of applications which benefit from algorithmic advances, from signal processing, to econometrics, to large-scale ocean, atmosphere, and climate modeling. This talk will survey some recent theoretical results involving accurate signal tracking with noise-free (degenerate) dynamics in high-dimensions (infinite, in principle, but say d between 103 and 108 , depending on the size of your application and your computer), and high-fidelity approximations of the filtering distribution in low dimensions (say d between 1 and several 10s).
Perspectives on Nonlinear Filtering
Law, Kody
2015-01-07
The solution to the problem of nonlinear filtering may be given either as an estimate of the signal (and ideally some measure of concentration), or as a full posterior distribution. Similarly, one may evaluate the fidelity of the filter either by its ability to track the signal or its proximity to the posterior filtering distribution. Hence, the field enjoys a lively symbiosis between probability and control theory, and there are plenty of applications which benefit from algorithmic advances, from signal processing, to econometrics, to large-scale ocean, atmosphere, and climate modeling. This talk will survey some recent theoretical results involving accurate signal tracking with noise-free (degenerate) dynamics in high-dimensions (infinite, in principle, but say d between 103 and 108 , depending on the size of your application and your computer), and high-fidelity approximations of the filtering distribution in low dimensions (say d between 1 and several 10s).
Tel, G.
We define the notion of total algorithms for networks of processes. A total algorithm enforces that a "decision" is taken by a subset of the processes, and that participation of all processes is required to reach this decision. Total algorithms are an important building block in the design of
International Nuclear Information System (INIS)
Jain, N.
1999-03-01
Phase-shifting interferometry has many advantages, and the phase shifting nature of the Liquid Crystal Point Diffraction Interferometer (LCPDI) promises to provide significant improvement over other current OMEGA wavefront sensors. However, while phase-shifting capabilities improve its accuracy as an interferometer, phase-shifting itself introduces errors. Phase-shifting algorithms are designed to eliminate certain types of phase-shift errors, and it is important to chose an algorithm that is best suited for use with the LCPDI. Using polarization microscopy, the authors have observed a correlation between LC alignment around the microsphere and fringe behavior. After designing a procedure to compare phase-shifting algorithms, they were able to predict the accuracy of two particular algorithms through computer modeling of device-specific phase shift-errors
Genetic design of interpolated non-linear controllers for linear plants
International Nuclear Information System (INIS)
Ajlouni, N.
2000-01-01
The techniques of genetic algorithms are proposed as a means of designing non-linear PID control systems. It is shown that the use of genetic algorithms for this purpose results in highly effective non-linear PID control systems. These results are illustrated by using genetic algorithms to design a non-linear PID control system and contrasting the results with an optimally tuned linear PID controller. (author)
Nonlinear Principal Component Analysis Using Strong Tracking Filter
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
The paper analyzes the problem of blind source separation (BSS) based on the nonlinear principal component analysis (NPCA) criterion. An adaptive strong tracking filter (STF) based algorithm was developed, which is immune to system model mismatches. Simulations demonstrate that the algorithm converges quickly and has satisfactory steady-state accuracy. The Kalman filtering algorithm and the recursive leastsquares type algorithm are shown to be special cases of the STF algorithm. Since the forgetting factor is adaptively updated by adjustment of the Kalman gain, the STF scheme provides more powerful tracking capability than the Kalman filtering algorithm and recursive least-squares algorithm.
Quantum Computations: Fundamentals and Algorithms
International Nuclear Information System (INIS)
Duplij, S.A.; Shapoval, I.I.
2007-01-01
Basic concepts of quantum information theory, principles of quantum calculations and the possibility of creation on this basis unique on calculation power and functioning principle device, named quantum computer, are concerned. The main blocks of quantum logic, schemes of quantum calculations implementation, as well as some known today effective quantum algorithms, called to realize advantages of quantum calculations upon classical, are presented here. Among them special place is taken by Shor's algorithm of number factorization and Grover's algorithm of unsorted database search. Phenomena of decoherence, its influence on quantum computer stability and methods of quantum errors correction are described
Electronic circuit realization of the logistic map
Indian Academy of Sciences (India)
at some key events of this bifurcation diagram with their computer-simulation counterparts. A list of ... Discrete-time dynamical systems are a particular type of nonlinear dynamical systems .... After the latest value is sampled and C1 charges to.
International Nuclear Information System (INIS)
Krommes, J.A.
2000-01-01
Recent results and future challenges in the systematic analytical description of plasma turbulence are described. First, the importance of statistical realizability is stressed, and the development and successes of the Realizable Markovian Closure are briefly reviewed. Next, submarginal turbulence (linearly stable but nonlinearly self-sustained fluctuations) is considered and the relevance of nonlinear instability in neutral-fluid shear flows to submarginal turbulence in magnetized plasmas is discussed. For the Hasegawa-Wakatani equations, a self-consistency loop that leads to steady-state vortex regeneration in the presence of dissipation is demonstrated and a partial unification of recent work of Drake (for plasmas) and of Waleffe (for neutral fluids) is given. Brief remarks are made on the difficulties facing a quantitatively accurate statistical description of submarginal turbulence. Finally, possible connections between intermittency, submarginal turbulence, and self-organized criticality (SOC) are considered and outstanding questions are identified
The economic value of realized volatility
DEFF Research Database (Denmark)
Christoffersen, Peter; Feunou, Bruno; Jacobs, Kris
2014-01-01
Many studies have documented that daily realized volatility estimates based on intraday returns provide volatility forecasts that are superior to forecasts constructed from daily returns only. We investigate whether these forecasting improvements translate into economic value added. To do so, we ...
Banach spaces that realize minimal fillings
International Nuclear Information System (INIS)
Bednov, B. B.; Borodin, P. A.
2014-01-01
It is proved that a real Banach space realizes minimal fillings for all its finite subsets (a shortest network spanning a fixed finite subset always exists and has the minimum possible length) if and only if it is a predual of L 1 . The spaces L 1 are characterized in terms of Steiner points (medians). Bibliography: 25 titles. (paper)
Zero-intelligence realized variance estimation
Gatheral, J.; Oomen, R.C.A.
2010-01-01
Given a time series of intra-day tick-by-tick price data, how can realized variance be estimated? The obvious estimator—the sum of squared returns between trades—is biased by microstructure effects such as bid-ask bounce and so in the past, practitioners were advised to drop most of the data and
FPGA Realization of Memory 10 Viterbi Decoder
DEFF Research Database (Denmark)
Paaske, Erik; Bach, Thomas Bo; Andersen, Jakob Dahl
1997-01-01
sequence mode when feedback from the Reed-Solomon decoder is available. The Viterbi decoder is realized using two Altera FLEX 10K50 FPGA's. The overall operating speed is 30 kbit/s, and since up to three iterations are performed for each frame and only one decoder is used, the operating speed...
Evaluating realized genetic gains from tree improvement.
J.B. St. Clair
1993-01-01
Tree improvement has become an essential part of the management of forest lands for wood production, and predicting yields and realized gains from forests planted with genetically-improved trees will become increasingly important. This paper discusses concepts of tree improvement and genetic gain important to growth and yield modeling, and reviews previous studies of...
Retrieval of high-order susceptibilities of nonlinear metamaterials
International Nuclear Information System (INIS)
Wang Zhi-Yu; Qiu Jin-Peng; Chen Hua; Mo Jiong-Jiong; Yu Fa-Xin
2017-01-01
Active metamaterials embedded with nonlinear elements are able to exhibit strong nonlinearity in microwave regime. However, existing S -parameter based parameter retrieval approaches developed for linear metamaterials do not apply in nonlinear cases. In this paper, a retrieval algorithm of high-order susceptibilities for nonlinear metamaterials is derived. Experimental demonstration shows that, by measuring the power level of each harmonic while sweeping the incident power, high-order susceptibilities of a thin-layer nonlinear metamaterial can be effectively retrieved. The proposedapproach can be widely used in the research of active metamaterials. (paper)
Flutter analysis of an airfoil with multiple nonlinearities and uncertainties
Directory of Open Access Journals (Sweden)
Haitao Liao
2013-09-01
Full Text Available An original method for calculating the limit cycle oscillations of nonlinear aero-elastic system is presented. The problem of determining the maximum vibration amplitude of limit cycle is transformed into a nonlinear optimization problem. The harmonic balance method and the Floquet theory are selected to construct the general nonlinear equality and inequality constraints. The resulting constrained maximization problem is then solved by using the MultiStart algorithm. Finally, the proposed approach is validated and used to analyse the limit cycle oscillations of an airfoil with multiple nonlinearities and uncertainties. Numerical examples show that the coexistence of multiple nonlinearities may lead to low amplitude limit cycle oscillation.
DEFF Research Database (Denmark)
Hansen, Peter Reinhard; Lunde, Asger; Voev, Valeri
We introduce a multivariate GARCH model that utilizes and models realized measures of volatility and covolatility. The realized measures extract information contained in high-frequency data that is particularly beneficial during periods with variation in volatility and covolatility. Applying the ...
Experiments with parallel algorithms for combinatorial problems
G.A.P. Kindervater (Gerard); H.W.J.M. Trienekens
1985-01-01
textabstractIn the last decade many models for parallel computation have been proposed and many parallel algorithms have been developed. However, few of these models have been realized and most of these algorithms are supposed to run on idealized, unrealistic parallel machines. The parallel machines
[Nonlinear magnetohydrodynamics
International Nuclear Information System (INIS)
1994-01-01
Resistive MHD equilibrium, even for small resistivity, differs greatly from ideal equilibrium, as do the dynamical consequences of its instabilities. The requirement, imposed by Faraday's law, that time independent magnetic fields imply curl-free electric fields, greatly restricts the electric fields allowed inside a finite-resistivity plasma. If there is no flow and the implications of the Ohm's law are taken into account (and they need not be, for ideal equilibria), the electric field must equal the resistivity times the current density. The vanishing of the divergence of the current density then provides a partial differential equation which, together with boundary conditions, uniquely determines the scalar potential, the electric field, and the current density, for any given resistivity profile. The situation parallels closely that of driven shear flows in hydrodynamics, in that while dissipative steady states are somewhat more complex than ideal ones, there are vastly fewer of them to consider. Seen in this light, the vast majority of ideal MHD equilibria are just irrelevant, incapable of being set up in the first place. The steady state whose stability thresholds and nonlinear behavior needs to be investigated ceases to be an arbitrary ad hoc exercise dependent upon the whim of the investigator, but is determined by boundary conditions and choice of resistivity profile
Realized GARCH: A Complete Model of Returns and Realized Measures of Volatility
DEFF Research Database (Denmark)
Hansen, Peter Reinhard; Huang, Zhuo (Albert); Shek, Howard Howan
GARCH models have been successful in modeling financial returns. Still, much is to be gained by incorporating a realized measure of volatility in these models. In this paper we introduce a new framework for the joint modeling of returns and realized measures of volatility. The Realized GARCH...... framework nests most GARCH models as special cases and is, in many ways, a natural extension of standard GARCH models. We pay special attention to linear and log-linear Realized GARCH specifications. This class of models has several attractive features. It retains the simplicity and tractability...... to latent volatility. This equation facilitates a simple modeling of the dependence between returns and future volatility that is commonly referred to as the leverage effect. An empirical application with DJIA stocks and an exchange traded index fund shows that a simple Realized GARCH structure leads...
Scalable Nonlinear Compact Schemes
Energy Technology Data Exchange (ETDEWEB)
Ghosh, Debojyoti [Argonne National Lab. (ANL), Argonne, IL (United States); Constantinescu, Emil M. [Univ. of Chicago, IL (United States); Brown, Jed [Univ. of Colorado, Boulder, CO (United States)
2014-04-01
In this work, we focus on compact schemes resulting in tridiagonal systems of equations, specifically the fifth-order CRWENO scheme. We propose a scalable implementation of the nonlinear compact schemes by implementing a parallel tridiagonal solver based on the partitioning/substructuring approach. We use an iterative solver for the reduced system of equations; however, we solve this system to machine zero accuracy to ensure that no parallelization errors are introduced. It is possible to achieve machine-zero convergence with few iterations because of the diagonal dominance of the system. The number of iterations is specified a priori instead of a norm-based exit criterion, and collective communications are avoided. The overall algorithm thus involves only point-to-point communication between neighboring processors. Our implementation of the tridiagonal solver differs from and avoids the drawbacks of past efforts in the following ways: it introduces no parallelization-related approximations (multiprocessor solutions are exactly identical to uniprocessor ones), it involves minimal communication, the mathematical complexity is similar to that of the Thomas algorithm on a single processor, and it does not require any communication and computation scheduling.
Rectangular-cladding silicon slot waveguide with improved nonlinear performance
Huang, Zengzhi; Huang, Qingzhong; Wang, Yi; Xia, Jinsong
2018-04-01
Silicon slot waveguides have great potential in hybrid silicon integration to realize nonlinear optical applications. We propose a rectangular-cladding hybrid silicon slot waveguide. Simulation result shows that, with a rectangular-cladding, the slot waveguide can be formed by narrower silicon strips, so the two-photon absorption (TPA) loss in silicon is decreased. When the cladding material is a nonlinear polymer, the calculated TPA figure of merit (FOMTPA) is 4.4, close to the value of bulk nonlinear polymer of 5.0. This value confirms the good nonlinear performance of rectangular-cladding silicon slot waveguides.
Towards the experimental realization of hybrid quantum systems
International Nuclear Information System (INIS)
Koller, C.
2012-01-01
One of the main interests of quantum physics in this new millennium is the exploitation of quantum mechanical principles in technical applications. One approach here is to use entanglement and superpositions of states to realize powerful algorithms capable of solving challenging computational tasks on a much faster time scale than a classical computer ever could. To find the quantum analogue of a classical bit one needs a quantum mechanical two level system that can be used to store and process quantum information. Most of the current approaches to find such a 'qubit' have the intention to find a single system that is able to fulfill all desirable tasks. But actually most quantum systems are only favorable for very specific tasks (e.g storage, processing, data exchange,..), similar as it is in classical computing. For some qubits the main disadvantages is that their quantum state is very fragile. Those systems loose their 'quantum information' (that is the possibility to store superpositions of their states coherently) easily. They 'decohere' on a timescale that is much shorter then any more involving algorithm. Other systems can keep those superposition states for quite a while, but are so difficult to address that the number of operations that can be made is very limited. The task of a so called hybrid quantum system is now to combine the strengths of these different systems, using e.g. one for manipulation and an other system for storage. Similar to a processor/memory architecture in conventional computers these systems could use a kind of bus system to couple between them. The main task of this thesis was to make steps towards the realization of such a system using two different combinations of quantum systems. Both are planned to use superconducting qubits (transmons) as processor qubit and either atoms (ultra cold rubidium 87 ensembles) or solid state spin systems (Nitrogen Vacancies in diamonds - NV centers) as memory. (author)
Dynamic training algorithm for dynamic neural networks
International Nuclear Information System (INIS)
Tan, Y.; Van Cauwenberghe, A.; Liu, Z.
1996-01-01
The widely used backpropagation algorithm for training neural networks based on the gradient descent has a significant drawback of slow convergence. A Gauss-Newton method based recursive least squares (RLS) type algorithm with dynamic error backpropagation is presented to speed-up the learning procedure of neural networks with local recurrent terms. Finally, simulation examples concerning the applications of the RLS type algorithm to identification of nonlinear processes using a local recurrent neural network are also included in this paper
Realizations of κ-Minkowski space, Drinfeld twists, and related symmetry algebras
Energy Technology Data Exchange (ETDEWEB)
Juric, Tajron; Meljanac, Stjepan; Pikutic, Danijel [Ruder Boskovic Institute, Theoretical Physics Division, Zagreb (Croatia)
2015-11-15
Realizations of κ-Minkowski space linear in momenta are studied for time-, space- and light-like deformations. We construct and classify all such linear realizations and express them in terms of the gl(n) generators. There are three one-parameter families of linear realizations for timelike and space-like deformations, while for light-like deformations, there are only four linear realizations. The relation between a deformed Heisenberg algebra, the star product, the coproduct of momenta, and the twist operator is presented. It is proved that for each linear realization there exists a Drinfeld twist satisfying normalization and cocycle conditions. κ-Deformed igl(n)-Hopf algebras are presented for all cases. The κ-Poincare-Weyl and κ-Poincare-Hopf algebras are discussed. The left-right dual κ-Minkowski algebra is constructed from the transposed twists. The corresponding realizations are nonlinear. All Drinfeld twists related to κ-Minkowski space are obtained from our construction. Finally, some physical applications are discussed. (orig.)
Realizations of κ-Minkowski space, Drinfeld twists, and related symmetry algebras
International Nuclear Information System (INIS)
Juric, Tajron; Meljanac, Stjepan; Pikutic, Danijel
2015-01-01
Realizations of κ-Minkowski space linear in momenta are studied for time-, space- and light-like deformations. We construct and classify all such linear realizations and express them in terms of the gl(n) generators. There are three one-parameter families of linear realizations for timelike and space-like deformations, while for light-like deformations, there are only four linear realizations. The relation between a deformed Heisenberg algebra, the star product, the coproduct of momenta, and the twist operator is presented. It is proved that for each linear realization there exists a Drinfeld twist satisfying normalization and cocycle conditions. κ-Deformed igl(n)-Hopf algebras are presented for all cases. The κ-Poincare-Weyl and κ-Poincare-Hopf algebras are discussed. The left-right dual κ-Minkowski algebra is constructed from the transposed twists. The corresponding realizations are nonlinear. All Drinfeld twists related to κ-Minkowski space are obtained from our construction. Finally, some physical applications are discussed. (orig.)
Convergence criteria for systems of nonlinear elliptic partial differential equations
International Nuclear Information System (INIS)
Sharma, R.K.
1986-01-01
This thesis deals with convergence criteria for a special system of nonlinear elliptic partial differential equations. A fixed-point algorithm is used, which iteratively solves one linearized elliptic partial differential equation at a time. Conditions are established that help foresee the convergence of the algorithm. Under reasonable hypotheses it is proved that the algorithm converges for such nonlinear elliptic systems. Extensive experimental results are reported and they show the algorithm converges in a wide variety of cases and the convergence is well correlated with the theoretical conditions introduced in this thesis
SPP propagation in nonlinear glass-metal interface
Sagor, Rakibul Hasan; Alsunaidi, Mohammad A.; Ooi, Boon S.
2011-01-01
The non-linear propagation of Surface-Plasmon-Polaritons (SPP) in single interface of metal and chalcogenide glass (ChG) is considered. A time domain simulation algorithm is developed using the Finite Difference Time Domain (FDTD) method
NIM Realization of the Gallium Triple Point
Xiaoke, Yan; Ping, Qiu; Yuning, Duan; Yongmei, Qu
2003-09-01
In the last three years (1999 to 2001), the gallium triple-point cell has been successfully developed, and much corresponding research has been carried out at the National Institute of Metrology (NIM), Beijing, China. This paper presents the cell design, apparatus and procedure for realizing the gallium triple point, and presents studies on the different freezing methods. The reproducibility is 0.03 mK, and the expanded uncertainty of realization of the gallium triple point is evaluated to be 0.17 mK (p=0.99, k=2.9). Also, the reproducibility of the gallium triple point was compared with that of the triple point of water.
Enablers & Barriers for Realizing Modularity Benefits
DEFF Research Database (Denmark)
Storbjerg, Simon Haahr; Brunø, Thomas Ditlev; Thyssen, Jesper
2012-01-01
far less attention compared to the theories and methods concerning modularization of technical systems. Harvesting the full potential of modularization, particularly in relation to product development agility, depends on more than an optimal architecture. Key enablers in this context......Although modularization is becoming both a well-described domain in academia and a broadly applied concept in business, many of today’s firm still struggle to realize the promised benefits of this approach. Managing modularization is a complex matter, and in spite of this, a topic that has received...... are the organizational and systems related aspects. Recognizing the need for guidance to realize the benefits of modularity, the purpose of this study is through a literature study and a case study to improve the insight into the organizational and systems related enablers and barriers with regard to obtaining the full...
Exploring heterogeneous market hypothesis using realized volatility
Chin, Wen Cheong; Isa, Zaidi; Mohd Nor, Abu Hassan Shaari
2013-04-01
This study investigates the heterogeneous market hypothesis using high frequency data. The cascaded heterogeneous trading activities with different time durations are modelled by the heterogeneous autoregressive framework. The empirical study indicated the presence of long memory behaviour and predictability elements in the financial time series which supported heterogeneous market hypothesis. Besides the common sum-of-square intraday realized volatility, we also advocated two power variation realized volatilities in forecast evaluation and risk measurement in order to overcome the possible abrupt jumps during the credit crisis. Finally, the empirical results are used in determining the market risk using the value-at-risk approach. The findings of this study have implications for informationally market efficiency analysis, portfolio strategies and risk managements.
Realization of superconductive films by screen printing
International Nuclear Information System (INIS)
Baudry, H.
1988-01-01
Screen printing is a promising method to manufacture superconductive lines making use of superconductive ceramics. An ink has been realized with YBa 2 Cu 3 0 7-x' and the process conditions defined by thermal analysis. A superconductive transition is observed after screen printing on MgO. The firing of the layer is made at 920 0 C followed by a reoxidation step at 420 0 C. The silver electrical contacts are also screen printed [fr
New techniques used to realize silicon photocells
International Nuclear Information System (INIS)
Siffert, P.
1978-01-01
The techniques used to realize the terrestrial silicon solar cells being considered the possible improvements of these methods are discussed. The various approaches under development to prepare silicon sheets in a continuous way are considered for both self-supporting or substrate deposited layers. Finally, the various methods used or under investigation to obtain the surface potential barrier are considered; MIS, heterojunction and ion implantation [fr
Experimental functional realization of attribute grammar system
Directory of Open Access Journals (Sweden)
I. Attali
2002-07-01
Full Text Available In this paper we present an experimental functional realization of attribute grammar(AG system for personal computers. For AG system functioning only Turbo Prolog compiler is required. The system functioning is based on a specially elaborated metalanguage for AG description, universal syntactic and semantic constructors. The AG system provides automatic generation of target compiler (syntax--oriented software using Turbo Prolog as object language.
Oil shale mines and their realizable production
International Nuclear Information System (INIS)
Habicht, K.
1994-01-01
The production of Estonian oil shale depends on its marketing opportunities. The realizable production is a function of the oil shale price, which in turn depends on production costs. The latter are dependent on which mines are producing oil shale and on the volume of production. The purpose of the present article is to analyze which mines should operate under various realizable production scenarios and what should be their annual output so that the total cost of oil shale production (including maintenance at idle mines) is minimized. This paper is also targeted at observing the change in the average production cost per ton of oil shale depending on the realizable output. The calculations are based on data for the first four months of 1993, as collected by N. Barabaner (Estonian Academy of Sciences, Institute of Economy). The data include the total production volume and production cost from the mines of RE 'Eesti Polevkivi' (State Enterprise 'Estonian Oil Shale'). They also project expenses from mine closings in case of conservation. The latter costs were allocated among mines in direct proportion to their respective number of employees. (author)
Coset realization of unifying W-algebras
International Nuclear Information System (INIS)
Blumenhagen, R.; Huebel, R.
1994-06-01
We construct several quantum coset W-algebras, e.g. sl(2,R)/U(1) and sl(2,R)+sl(2,R)/sl(2,R), and argue that they are finitely nonfreely generated. Furthermore, we discuss in detail their role as unifying W-algebras of Casimir W-algebras. We show that it is possible to give coset realizations of various types of unifying W-algebras, e.g. the diagonal cosets based on the symplectic Lie algebras sp(2n) realize the unifying W-algebras which have previously been introduced as 'WD -n '. In addition, minimal models of WD -n are studied. The coset realizations provide a generalization of level-rank-duality of dual coset pairs. As further examples of finitely nonfreely generated quantum W-algebras we discuss orbifolding of W-algebras which on the quantum level has different properties than in the classical case. We demonstrate in some examples that the classical limit according to Bowcock and Watts of these nonfreely finitely generated quantum W-algebras probably yields infinitely nonfreely generated classical W-algebras. (orig.)
Dynamic large eddy simulation: Stability via realizability
Mokhtarpoor, Reza; Heinz, Stefan
2017-10-01
The concept of dynamic large eddy simulation (LES) is highly attractive: such methods can dynamically adjust to changing flow conditions, which is known to be highly beneficial. For example, this avoids the use of empirical, case dependent approximations (like damping functions). Ideally, dynamic LES should be local in physical space (without involving artificial clipping parameters), and it should be stable for a wide range of simulation time steps, Reynolds numbers, and numerical schemes. These properties are not trivial, but dynamic LES suffers from such problems over decades. We address these questions by performing dynamic LES of periodic hill flow including separation at a high Reynolds number Re = 37 000. For the case considered, the main result of our studies is that it is possible to design LES that has the desired properties. It requires physical consistency: a PDF-realizable and stress-realizable LES model, which requires the inclusion of the turbulent kinetic energy in the LES calculation. LES models that do not honor such physical consistency can become unstable. We do not find support for the previous assumption that long-term correlations of negative dynamic model parameters are responsible for instability. Instead, we concluded that instability is caused by the stable spatial organization of significant unphysical states, which are represented by wall-type gradient streaks of the standard deviation of the dynamic model parameter. The applicability of our realizability stabilization to other dynamic models (including the dynamic Smagorinsky model) is discussed.
Luo, Biao; Liu, Derong; Wu, Huai-Ning
2018-06-01
Reinforcement learning has proved to be a powerful tool to solve optimal control problems over the past few years. However, the data-based constrained optimal control problem of nonaffine nonlinear discrete-time systems has rarely been studied yet. To solve this problem, an adaptive optimal control approach is developed by using the value iteration-based Q-learning (VIQL) with the critic-only structure. Most of the existing constrained control methods require the use of a certain performance index and only suit for linear or affine nonlinear systems, which is unreasonable in practice. To overcome this problem, the system transformation is first introduced with the general performance index. Then, the constrained optimal control problem is converted to an unconstrained optimal control problem. By introducing the action-state value function, i.e., Q-function, the VIQL algorithm is proposed to learn the optimal Q-function of the data-based unconstrained optimal control problem. The convergence results of the VIQL algorithm are established with an easy-to-realize initial condition . To implement the VIQL algorithm, the critic-only structure is developed, where only one neural network is required to approximate the Q-function. The converged Q-function obtained from the critic-only VIQL method is employed to design the adaptive constrained optimal controller based on the gradient descent scheme. Finally, the effectiveness of the developed adaptive control method is tested on three examples with computer simulation.
Westra, H.J.R.
2012-01-01
In this Thesis, nonlinear dynamics and nonlinear interactions are studied from a micromechanical point of view. Single and doubly clamped beams are used as model systems where nonlinearity plays an important role. The nonlinearity also gives rise to rich dynamic behavior with phenomena like
Recent Advances in Explicit Multiparametric Nonlinear Model Predictive Control
Domínguez, Luis F.
2011-01-19
In this paper we present recent advances in multiparametric nonlinear programming (mp-NLP) algorithms for explicit nonlinear model predictive control (mp-NMPC). Three mp-NLP algorithms for NMPC are discussed, based on which novel mp-NMPC controllers are derived. The performance of the explicit controllers are then tested and compared in a simulation example involving the operation of a continuous stirred-tank reactor (CSTR). © 2010 American Chemical Society.
On the complexity of computing two nonlinearity measures
DEFF Research Database (Denmark)
Find, Magnus Gausdal
2014-01-01
We study the computational complexity of two Boolean nonlinearity measures: the nonlinearity and the multiplicative complexity. We show that if one-way functions exist, no algorithm can compute the multiplicative complexity in time 2O(n) given the truth table of length 2n, in fact under the same ...
Ripple distribution for nonlinear fiber-optic channels.
Sorokina, Mariia; Sygletos, Stylianos; Turitsyn, Sergei
2017-02-06
We demonstrate data rates above the threshold imposed by nonlinearity on conventional optical signals by applying novel probability distribution, which we call ripple distribution, adapted to the properties of the fiber channel. Our results offer a new direction for signal coding, modulation and practical nonlinear distortions compensation algorithms.
Robust fault-sensitive synchronization of a class of nonlinear systems
International Nuclear Information System (INIS)
Xu Shi-Yun; Tang Yong; Sun Hua-Dong; Yang Ying; Liu Xian
2011-01-01
Aiming at enhancing the quality as well as the reliability of synchronization, this paper is concerned with the fault detection issue within the synchronization process for a class of nonlinear systems in the existence of external disturbances. To handle such problems, the concept of robust fault-sensitive (RFS) synchronization is proposed, and a method of determining such a kind of synchronization is developed. Under the framework of RFS synchronization, the master and the slave systems are robustly synchronized, and at the same time, sensitive to possible faults based on a mixed H − /H ∞ performance. The design of desired output feedback controller is realized by solving a linear matrix inequality, and the fault sensitivity H − index can be optimized via a convex optimization algorithm. A master-slave configuration composed of identical Chua's circuits is adopted as a numerical example to demonstrate the effectiveness and applicability of the analytical results. (general)
Design of a Low-Power VLSI Macrocell for Nonlinear Adaptive Video Noise Reduction
Directory of Open Access Journals (Sweden)
Sergio Saponara
2004-09-01
Full Text Available A VLSI macrocell for edge-preserving video noise reduction is proposed in the paper. It is based on a nonlinear rational filter enhanced by a noise estimator for blind and dynamic adaptation of the filtering parameters to the input signal statistics. The VLSI filter features a modular architecture allowing the extension of both mask size and filtering directions. Both spatial and spatiotemporal algorithms are supported. Simulation results with monochrome test videos prove its efficiency for many noise distributions with PSNR improvements up to 3.8 dB with respect to a nonadaptive solution. The VLSI macrocell has been realized in a 0.18 ÃŽÂ¼m CMOS technology using a standard-cells library; it allows for real-time processing of main video formats, up to 30 fps (frames per second 4CIF, with a power consumption in the order of few mW.
Robust Backstepping Control for Cold Rolling Main Drive System with Nonlinear Uncertainties
Directory of Open Access Journals (Sweden)
Xu Yang
2013-01-01
Full Text Available The nonlinear model of main drive system in cold rolling process, which considers the influence with parameter uncertainties such as clearance and variable friction coefficient, as well as external disturbance by roll eccentricity and variation of strip material quality, is built. By transformation, the lower triangular structure form of main drive system is obtained. The backstepping algorithm based on signal compensation is proposed to design a linear time-invariant (LTI robust controller, including a nominal controller and a robust compensator. A comparison with PI controller shows that the controller has better disturbance attenuation performance and tracking behaviors. Meanwhile, according to its LTI characteristic, the robust controller can be realized easily; therefore it is also appropriated to high speed dynamic rolling process.
Nonlinear laser-plasma interactions
Kaw, P. K.
2017-12-01
Soon after lasers were invented, there was tremendous curiosity on the nonlinear phenomena which would result in their interaction with a fully ionized plasma. Apart from the basic interest, it was realized that it could be used for the achievement of nuclear fusion in the laboratory. This led us to a paper on the propagation of a laser beam into an inhomogeneous fusion plasma, where it was first demonstrated that light would go up to the critical layer (where the frequency matches the plasma frequency) and get reflected from there with a reflection coefficient of order unity. The reflection coefficient was determined by collisional effects. Since the wave was expected to slow down to near zero group speed at the reflection point, the dominant collision frequency determining the reflection coefficient was the collision frequency at the reflection point. It turned out that the absorption of light was rather small for fusion temperatures. This placed a premium on investigation of nonlinear phenomena which might contribute to the absorption and penetration of the light into high-density plasma. An early investigation showed that electron jitter with respect to ions would be responsible for the excitation of decay instabilities which convert light waves into electrostatic plasma waves and ion waves near the critical frequency. These electrostatic waves would then get absorbed into the plasma even in the collisionless case and lead to plasma heating which is nonlinear. Detailed estimates of this heating were made. Similar nonlinear processes which could lead to stimulated scattering of light in the underdense region (ω >ω _p) were investigated together with a number of other workers. All these nonlinear processes need a critical threshold power for excitation. Another important process which was discovered around the same time had to do with filamentation and trapping of light when certain thresholds were exceeded. All of this work has been extensively verified in
International Nuclear Information System (INIS)
Kim, Jae Eum
2014-01-01
DC electrical outputs of a piezoelectric vibration energy harvester by nonlinear rectifying circuitry can hardly be obtained either by any mathematical models developed so far or by finite element analysis. To address the issue, this work used an equivalent electrical circuit model and newly developed an algorithm to efficiently identify relevant circuit parameters of arbitrarily-shaped cantilevered piezoelectric energy harvesters. The developed algorithm was then realized as a dedicated software module by adopting ANSYS finite element analysis software for the parameters identification and the Tcl/Tk programming language for a graphical user interface and linkage with ANSYS. For verifications, various AC electrical outputs by the developed software were compared with those by traditional finite element analysis. DC electrical outputs through rectifying circuitry were also examined for varying values of the smoothing capacitance and load resistance.
Energy Technology Data Exchange (ETDEWEB)
Kim, Jae Eum [Catholic University of Daegu, Gyeongsan (Korea, Republic of)
2014-10-15
DC electrical outputs of a piezoelectric vibration energy harvester by nonlinear rectifying circuitry can hardly be obtained either by any mathematical models developed so far or by finite element analysis. To address the issue, this work used an equivalent electrical circuit model and newly developed an algorithm to efficiently identify relevant circuit parameters of arbitrarily-shaped cantilevered piezoelectric energy harvesters. The developed algorithm was then realized as a dedicated software module by adopting ANSYS finite element analysis software for the parameters identification and the Tcl/Tk programming language for a graphical user interface and linkage with ANSYS. For verifications, various AC electrical outputs by the developed software were compared with those by traditional finite element analysis. DC electrical outputs through rectifying circuitry were also examined for varying values of the smoothing capacitance and load resistance.
APM Best Practices Realizing Application Performance Management
Sydor, Michael J
2011-01-01
The objective of APM Best Practices: Realizing Application Performance Management is to establish reliable application performance management (APM) practices - to demonstrate value, to do it quickly, and to adapt to the client circumstances. It's important to balance long-term goals with short-term deliverables, but without compromising usefulness or correctness. The successful strategy is to establish a few reasonable goals, achieve them quickly, and then iterate over the same topics two more times, with each successive iteration expanding the skills and capabilities of the APM team. This str
Analysis of Popper's Experiment and Its Realization
Qureshi, T.
2012-04-01
An experiment proposed by Karl Popper to test the standard interpretation of quantum mechanics was realized by Kim and Shih. We use a quantum mechanical calculation to analyze Popper's proposal, and find a surprising result for the location of the virtual slit. We also analyze Kim and Shih's experiment, and demonstrate that although it ingeniously overcomes the problem of temporal spreading of the wave-packet, it is inconclusive about Popper's test. We point out that another experiment which (unknowingly) implements Popper's test in a conclusive way, has actually been carried out. Its results are in contradiction with Popper's prediction, and agree with our analysis.
Energy Technology Data Exchange (ETDEWEB)
Torello, David [GW Woodruff School of Mechanical Engineering, Georgia Tech (United States); Kim, Jin-Yeon [School of Civil and Environmental Engineering, Georgia Tech (United States); Qu, Jianmin [Department of Civil and Environmental Engineering, Northwestern University (United States); Jacobs, Laurence J. [School of Civil and Environmental Engineering, Georgia Tech and GW Woodruff School of Mechanical Engineering, Georgia Tech (United States)
2015-03-31
This research considers the effects of diffraction, attenuation, and the nonlinearity of generating sources on measurements of nonlinear ultrasonic Rayleigh wave propagation. A new theoretical framework for correcting measurements made with air-coupled and contact piezoelectric receivers for the aforementioned effects is provided based on analytical models and experimental considerations. A method for extracting the nonlinearity parameter β{sub 11} is proposed based on a nonlinear least squares curve-fitting algorithm that is tailored for Rayleigh wave measurements. Quantitative experiments are conducted to confirm the predictions for the nonlinearity of the piezoelectric source and to demonstrate the effectiveness of the curve-fitting procedure. These experiments are conducted on aluminum 2024 and 7075 specimens and a β{sub 11}{sup 7075}/β{sub 11}{sup 2024} measure of 1.363 agrees well with previous literature and earlier work.
General solution of string inspired nonlinear equations
International Nuclear Information System (INIS)
Bandos, I.A.; Ivanov, E.; Kapustnikov, A.A.; Ulanov, S.A.
1998-07-01
We present the general solution of the system of coupled nonlinear equations describing dynamics of D-dimensional bosonic string in the geometric (or embedding) approach. The solution is parametrized in terms of two sets of the left- and right-moving Lorentz harmonic variables providing a special coset space realization of the product of two (D-2) dimensional spheres S D-2 = SO(1,D-1)/SO(1,1)xSO(D-2) contained in K D-2 . (author)
Algorithm 896: LSA: Algorithms for Large-Scale Optimization
Czech Academy of Sciences Publication Activity Database
Lukšan, Ladislav; Matonoha, Ctirad; Vlček, Jan
2009-01-01
Roč. 36, č. 3 (2009), 16-1-16-29 ISSN 0098-3500 R&D Pro jects: GA AV ČR IAA1030405; GA ČR GP201/06/P397 Institutional research plan: CEZ:AV0Z10300504 Keywords : algorithms * design * large-scale optimization * large-scale nonsmooth optimization * large-scale nonlinear least squares * large-scale nonlinear minimax * large-scale systems of nonlinear equations * sparse pro blems * partially separable pro blems * limited-memory methods * discrete Newton methods * quasi-Newton methods * primal interior-point methods Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.904, year: 2009
Ranking scientific publications: the effect of nonlinearity
Yao, Liyang; Wei, Tian; Zeng, An; Fan, Ying; di, Zengru
2014-10-01
Ranking the significance of scientific publications is a long-standing challenge. The network-based analysis is a natural and common approach for evaluating the scientific credit of papers. Although the number of citations has been widely used as a metric to rank papers, recently some iterative processes such as the well-known PageRank algorithm have been applied to the citation networks to address this problem. In this paper, we introduce nonlinearity to the PageRank algorithm when aggregating resources from different nodes to further enhance the effect of important papers. The validation of our method is performed on the data of American Physical Society (APS) journals. The results indicate that the nonlinearity improves the performance of the PageRank algorithm in terms of ranking effectiveness, as well as robustness against malicious manipulations. Although the nonlinearity analysis is based on the PageRank algorithm, it can be easily extended to other iterative ranking algorithms and similar improvements are expected.
Ranking scientific publications: the effect of nonlinearity.
Yao, Liyang; Wei, Tian; Zeng, An; Fan, Ying; Di, Zengru
2014-10-17
Ranking the significance of scientific publications is a long-standing challenge. The network-based analysis is a natural and common approach for evaluating the scientific credit of papers. Although the number of citations has been widely used as a metric to rank papers, recently some iterative processes such as the well-known PageRank algorithm have been applied to the citation networks to address this problem. In this paper, we introduce nonlinearity to the PageRank algorithm when aggregating resources from different nodes to further enhance the effect of important papers. The validation of our method is performed on the data of American Physical Society (APS) journals. The results indicate that the nonlinearity improves the performance of the PageRank algorithm in terms of ranking effectiveness, as well as robustness against malicious manipulations. Although the nonlinearity analysis is based on the PageRank algorithm, it can be easily extended to other iterative ranking algorithms and similar improvements are expected.
Nonlinear Optimization with Financial Applications
Bartholomew-Biggs, Michael
2005-01-01
The book introduces the key ideas behind practical nonlinear optimization. Computational finance - an increasingly popular area of mathematics degree programs - is combined here with the study of an important class of numerical techniques. The financial content of the book is designed to be relevant and interesting to specialists. However, this material - which occupies about one-third of the text - is also sufficiently accessible to allow the book to be used on optimization courses of a more general nature. The essentials of most currently popular algorithms are described, and their performan
Realization of fiber optic displacement sensors
Guzowski, Bartlomiej; Lakomski, Mateusz
2018-03-01
Fiber optic sensors are very promising because of their inherent advantages such as very small size, hard environment tolerance and impact of electromagnetic fields. In this paper three different types of Intensity Fiber Optic Displacement Sensors (I-FODS) are presented. Three configurations of I-FODS were realized in two varieties. In the first one, the cleaved multimode optical fibers (MMF) were used to collect reflected light, while in the second variety the MMF ended with ball lenses were chosen. To ensure an accurate alignment of optical fibers in the sensor head the MTP C9730 optical fiber ferrules were used. In this paper the influence of distribution of transmitting and detecting optical fibers on sensitivity and linear range of operation of developed I-FODS were investigated. We have shown, that I-FODS with ball lenses receive average 10.5% more reflected power in comparison to the cleaved optical fibers and they increase linearity range of I-FODS by 33%. In this paper, an analysis of each type of the realized sensor and detailed discussion are given.
Realization of quantum Fourier transform over ZN
International Nuclear Information System (INIS)
Fu Xiang-Qun; Bao Wan-Su; Li Fa-Da; Zhang Yu-Chao
2014-01-01
Since the difficulty in preparing the equal superposition state of amplitude is 1/√N, we construct a quantile transform of quantum Fourier transform (QFT) over Z N based on the elementary transforms, such as Hadamard transform and Pauli transform. The QFT over Z N can then be realized by the quantile transform, and used to further design its quantum circuit and analyze the requirements for the quantum register and quantum gates. However, the transform needs considerable quantum computational resources and it is difficult to construct a high-dimensional quantum register. Hence, we investigate the design of t-bit quantile transform, and introduce the definition of t-bit semiclassical QFT over Z N . According to probability amplitude, we prove that the transform can be used to realize QFT over Z N and further design its quantum circuit. For this transform, the requirements for the quantum register, the one-qubit gate, and two-qubit gate reduce obviously when compared with those for the QFT over Z N . (general)
PLA realizations for VLSI state machines
Gopalakrishnan, S.; Whitaker, S.; Maki, G.; Liu, K.
1990-01-01
A major problem associated with state assignment procedures for VLSI controllers is obtaining an assignment that produces minimal or near minimal logic. The key item in Programmable Logic Array (PLA) area minimization is the number of unique product terms required by the design equations. This paper presents a state assignment algorithm for minimizing the number of product terms required to implement a finite state machine using a PLA. Partition algebra with predecessor state information is used to derive a near optimal state assignment. A maximum bound on the number of product terms required can be obtained by inspecting the predecessor state information. The state assignment algorithm presented is much simpler than existing procedures and leads to the same number of product terms or less. An area-efficient PLA structure implemented in a 1.0 micron CMOS process is presented along with a summary of the performance for a controller implemented using this design procedure.
Energy Technology Data Exchange (ETDEWEB)
Kanamori, Masashi, E-mail: kanamori.masashi@jaxa.jp; Takahashi, Takashi, E-mail: takahashi.takashi@jaxa.jp; Aoyama, Takashi, E-mail: aoyama.takashi@jaxa.jp [Japan Aerospace Exploration Agency, 7-44-1, Jindaijihigashi-machi, Chofu, Tokyo (Japan)
2015-10-28
Shown in this paper is an introduction of a prediction tool for the propagation of loud noise with the application to the aeronautics in mind. The tool, named SPnoise, is based on HOWARD approach, which can express almost exact multidimensionality of the diffraction effect at the cost of back scattering. This paper argues, in particular, the prediction of the effect of atmospheric turbulence on sonic boom as one of the important issues in aeronautics. Thanks to the simple and efficient modeling of the atmospheric turbulence, SPnoise successfully re-creates the feature of the effect, which often emerges in the region just behind the front and rear shock waves in the sonic boom signature.
Gauge fields in nonlinear group realizations involving two-dimensional space-time symmetry
International Nuclear Information System (INIS)
Machacek, M.E.; McCliment, E.R.
1975-01-01
It is shown that gauge fields may be consistently introduced into a model Lagrangian previously considered by the authors. The model is suggested by the spontaneous breaking of a Lorentz-type group into a quasiphysical two-dimensional space-time and one internal degree of freedom, loosely associated with charge. The introduction of zero-mass gauge fields makes possible the absorption via the Higgs mechanism of the Goldstone fields that appear in the model despite the fact that the Goldstone fields do not transform as scalars. Specifically, gauge invariance of the Yang-Mills type requires the introduction of two sets of massless gauge fields. The transformation properties in two-dimensional space-time suggest that one set is analogous to a charge doublet that behaves like a second-rank tensor in real four-dimensional space time. The other set suggests a spin-one-like charge triplet. Via the Higgs mechanism, the first set absorbs the Goldstone fields and acquires mass. The second set remains massless. If massive gauge fields are introduced, the associated currents are not conserved and the Higgs mechanism is no longer fully operative. The Goldstone fields are not eliminated, but coupling between the Goldstone fields and the gauge fields does shift the mass of the antisymmetric second-rank-tensor gauge field components
SPP propagation in nonlinear glass-metal interface
Sagor, Rakibul Hasan
2011-12-01
The non-linear propagation of Surface-Plasmon-Polaritons (SPP) in single interface of metal and chalcogenide glass (ChG) is considered. A time domain simulation algorithm is developed using the Finite Difference Time Domain (FDTD) method. The general polarization algorithm incorporated in the auxiliary differential equation (ADE) is used to model frequency-dependent dispersion relation and third-order nonlinearity of ChG. The main objective is to observe the nonlinear behavior of SPP propagation and study the dynamics of the whole structure. © 2011 IEEE.
How do dispersal costs and habitat selection influence realized population connectivity?
Burgess, Scott C; Treml, Eric A; Marshall, Dustin J
2012-06-01
Despite the importance of dispersal for population connectivity, dispersal is often costly to the individual. A major impediment to understanding connectivity has been a lack of data combining the movement of individuals and their survival to reproduction in the new habitat (realized connectivity). Although mortality often occurs during dispersal (an immediate cost), in many organisms costs are paid after dispersal (deferred costs). It is unclear how such deferred costs influence the mismatch between dispersal and realized connectivity. Through a series of experiments in the field and laboratory, we estimated both direct and indirect deferred costs in a marine bryozoan (Bugula neritina). We then used the empirical data to parameterize a theoretical model in order to formalize predictions about how dispersal costs influence realized connectivity. Individuals were more likely to colonize poor-quality habitat after prolonged dispersal durations. Individuals that colonized poor-quality habitat performed poorly after colonization because of some property of the habitat (an indirect deferred cost) rather than from prolonged dispersal per se (a direct deferred cost). Our theoretical model predicted that indirect deferred costs could result in nonlinear mismatches between spatial patterns of potential and realized connectivity. The deferred costs of dispersal are likely to be crucial for determining how well patterns of dispersal reflect realized connectivity. Ignoring these deferred costs could lead to inaccurate predictions of spatial population dynamics.
The (G/G)-expansion method for a discrete nonlinear Schrödinger ...
Indian Academy of Sciences (India)
With the aid of symbolic computation, we choose a discrete nonlinear Schrödinger equation to illustrate the validity and advantages of the improved algorithm. As a result ... It is shown that the improved algorithm is effective and can be used for many other nonlinear differential-difference equations in mathematical physics.
Rodrigues, João Fabrício Mota; Coelho, Marco Túlio Pacheco; Ribeiro, Bruno R.
2018-04-01
Species distribution models (SDM) have been broadly used in ecology to address theoretical and practical problems. Currently, there are two main approaches to generate SDMs: (i) correlative, which is based on species occurrences and environmental predictor layers and (ii) process-based models, which are constructed based on species' functional traits and physiological tolerances. The distributions estimated by each approach are based on different components of species niche. Predictions of correlative models approach species realized niches, while predictions of process-based are more akin to species fundamental niche. Here, we integrated the predictions of fundamental and realized distributions of the freshwater turtle Trachemys dorbigni. Fundamental distribution was estimated using data of T. dorbigni's egg incubation temperature, and realized distribution was estimated using species occurrence records. Both types of distributions were estimated using the same regression approaches (logistic regression and support vector machines), both considering macroclimatic and microclimatic temperatures. The realized distribution of T. dorbigni was generally nested in its fundamental distribution reinforcing theoretical assumptions that the species' realized niche is a subset of its fundamental niche. Both modelling algorithms produced similar results but microtemperature generated better results than macrotemperature for the incubation model. Finally, our results reinforce the conclusion that species realized distributions are constrained by other factors other than just thermal tolerances.
The Volterra's integral equation theory for accelerator single-freedom nonlinear components
International Nuclear Information System (INIS)
Wang Sheng; Xie Xi
1996-01-01
The Volterra's integral equation equivalent to the dynamic equation of accelerator single-freedom nonlinear components is given, starting from which the transport operator of accelerator single-freedom nonlinear components and its inverse transport operator are obtained. Therefore, another algorithm for the expert system of the beam transport operator of accelerator single-freedom nonlinear components is developed
Parameter Estimation and Prediction of a Nonlinear Storage Model: an algebraic approach
Doeswijk, T.G.; Keesman, K.J.
2005-01-01
Generally, parameters that are nonlinear in system models are estimated by nonlinear least-squares optimization algorithms. In this paper, if a nonlinear discrete-time model with a polynomial quotient structure in input, output, and parameters, a method is proposed to re-parameterize the model such
New Exact Travelling Wave and Periodic Solutions of Discrete Nonlinear Schroedinger Equation
International Nuclear Information System (INIS)
Yang Qin; Dai Chaoqing; Zhang Jiefang
2005-01-01
Some new exact travelling wave and period solutions of discrete nonlinear Schroedinger equation are found by using a hyperbolic tangent function approach, which was usually presented to find exact travelling wave solutions of certain nonlinear partial differential models. Now we can further extend the new algorithm to other nonlinear differential-different models.
Bazhenov V.A.; Sacharov A.S.; Guliar A. I.; Pyskunov S.O.; Maksymiuk Y.V.
2014-01-01
Based MSSE created shell CE general type, which allows you to analyze the stress-strain state of axisymmetrical shells and plates in problems of physical and geometric nonlinearity. The principal nonlinear elasticity theory, algorithms for solving systems of nonlinear equations for determining the temperature and plastic deformation.
FEATURES APPLICATION CIRCUIT MOMENT FINITE ELEMENT (MSSE NONLINEAR CALCULATIONS OF PLATES AND SHELLS
Directory of Open Access Journals (Sweden)
Bazhenov V.A.
2014-06-01
Full Text Available Based MSSE created shell CE general type, which allows you to analyze the stress-strain state of axisymmetrical shells and plates in problems of physical and geometric nonlinearity. The principal nonlinear elasticity theory, algorithms for solving systems of nonlinear equations for determining the temperature and plastic deformation.
Nonlinear Impairment Compensation Using Expectation Maximization for PDM 16-QAM Systems
DEFF Research Database (Denmark)
Zibar, Darko; Winther, Ole; Franceschi, Niccolo
2012-01-01
We show experimentally that by using non-linear signal processing based algorithm, expectation maximization, nonlinear system tolerance can be increased by 2 dB. Expectation maximization is also effective in combating I/Q modulator nonlinearities and laser linewidth....
Modeling Autoregressive Processes with Moving-Quantiles-Implied Nonlinearity
Directory of Open Access Journals (Sweden)
Isao Ishida
2015-01-01
Full Text Available We introduce and investigate some properties of a class of nonlinear time series models based on the moving sample quantiles in the autoregressive data generating process. We derive a test fit to detect this type of nonlinearity. Using the daily realized volatility data of Standard & Poor’s 500 (S&P 500 and several other indices, we obtained good performance using these models in an out-of-sample forecasting exercise compared with the forecasts obtained based on the usual linear heterogeneous autoregressive and other models of realized volatility.
Benchmarking monthly homogenization algorithms
Venema, V. K. C.; Mestre, O.; Aguilar, E.; Auer, I.; Guijarro, J. A.; Domonkos, P.; Vertacnik, G.; Szentimrey, T.; Stepanek, P.; Zahradnicek, P.; Viarre, J.; Müller-Westermeier, G.; Lakatos, M.; Williams, C. N.; Menne, M.; Lindau, R.; Rasol, D.; Rustemeier, E.; Kolokythas, K.; Marinova, T.; Andresen, L.; Acquaotta, F.; Fratianni, S.; Cheval, S.; Klancar, M.; Brunetti, M.; Gruber, C.; Prohom Duran, M.; Likso, T.; Esteban, P.; Brandsma, T.
2011-08-01
The COST (European Cooperation in Science and Technology) Action ES0601: Advances in homogenization methods of climate series: an integrated approach (HOME) has executed a blind intercomparison and validation study for monthly homogenization algorithms. Time series of monthly temperature and precipitation were evaluated because of their importance for climate studies and because they represent two important types of statistics (additive and multiplicative). The algorithms were validated against a realistic benchmark dataset. The benchmark contains real inhomogeneous data as well as simulated data with inserted inhomogeneities. Random break-type inhomogeneities were added to the simulated datasets modeled as a Poisson process with normally distributed breakpoint sizes. To approximate real world conditions, breaks were introduced that occur simultaneously in multiple station series within a simulated network of station data. The simulated time series also contained outliers, missing data periods and local station trends. Further, a stochastic nonlinear global (network-wide) trend was added. Participants provided 25 separate homogenized contributions as part of the blind study as well as 22 additional solutions submitted after the details of the imposed inhomogeneities were revealed. These homogenized datasets were assessed by a number of performance metrics including (i) the centered root mean square error relative to the true homogeneous value at various averaging scales, (ii) the error in linear trend estimates and (iii) traditional contingency skill scores. The metrics were computed both using the individual station series as well as the network average regional series. The performance of the contributions depends significantly on the error metric considered. Contingency scores by themselves are not very informative. Although relative homogenization algorithms typically improve the homogeneity of temperature data, only the best ones improve precipitation data
Multi-objective optimum design of fast tool servo based on improved differential evolution algorithm
International Nuclear Information System (INIS)
Zhu, Zhiwei; Zhou, Xiaoqin; Liu, Qiang; Zhao, Shaoxin
2011-01-01
The flexure-based mechanism is a promising realization of fast tool servo (FTS), and the optimum determination of flexure hinge parameters is one of the most important elements in the FTS design. This paper presents a multi-objective optimization approach to optimizing the dimension and position parameters of the flexure-based mechanism, which is based on the improved differential evolution algorithm embedding chaos and nonlinear simulated anneal algorithm. The results of optimum design show that the proposed algorithm has excellent performance and a well-balanced compromise is made between two conflicting objectives, the stroke and natural frequency of the FTS mechanism. The validation tests based on finite element analysis (FEA) show good agreement with the results obtained by using the proposed theoretical algorithm of this paper. Finally, a series of experimental tests are conducted to validate the design process and assess the performance of the FTS mechanism. The designed FTS reaches up to a stroke of 10.25 μm with at least 2 kHz bandwidth. Both of the FEA and experimental results demonstrate that the parameters of the flexure-based mechanism determined by the proposed approaches can achieve the specified performance and the proposed approach is suitable for the optimum design of FTS mechanism and of excellent performances
Inverse operator theory method and its applications in nonlinear physics
International Nuclear Information System (INIS)
Fang Jinqing
1993-01-01
Inverse operator theory method, which has been developed by G. Adomian in recent years, and its applications in nonlinear physics are described systematically. The method can be an unified effective procedure for solution of nonlinear and/or stochastic continuous dynamical systems without usual restrictive assumption. It is realized by Mathematical Mechanization by us. It will have a profound on the modelling of problems of physics, mathematics, engineering, economics, biology, and so on. Some typical examples of the application are given and reviewed
APPLICATION OF NONLINEAR PID CONTROLLER IN SUPERCONDUCTING MAGNETIC ENERGY STORAGE
PENG, Xiaotao; CHENG, Shijie
2011-01-01
As a new control strategy, Nonlinear PID(NLPID) controller has been introduced in the power system successfully. The controller is free of planting model foundation in the design procedure and realized simply. In this paper, a nonlinear PID controller used for superconducting magnetic energy storage (SMES) unit connected to a power system is proposed. Purpose of designing such controller is to improve the stability of the power system in a relatively wide operation range. The design procedure...
Macroscopic and non-linear quantum games
International Nuclear Information System (INIS)
Aerts, D.; D'Hooghe, A.; Posiewnik, A.; Pykacz, J.
2005-01-01
Full text: We consider two models of quantum games. The first one is Marinatto and Weber's 'restricted' quantum game in which only the identity and the spin-flip operators are used. We show that this quantum game allows macroscopic mechanistic realization with the use of a version of the 'macroscopic quantum machine' described by Aerts already in 1980s. In the second model we use non-linear quantum state transformations which operate on points of spin-1/2 on the Bloch sphere and which can be used to distinguish optimally between two non-orthogonal states. We show that efficiency of these non-linear strategies out-perform any linear ones. Some hints on the possible theory of non-linear quantum games are given. (author)
Experiencing and the realization of motherhood by teenage mothers
Directory of Open Access Journals (Sweden)
Ewa Rzechowska
2015-04-01
Full Text Available Background Early motherhood constitutes a difficult challenge for girls, and the level of their performance in that role is varied. In this article, teenage motherhood as a process is considered. The objective of the research was to determine the paths by which teenage girls enter the mother role. Particular attention was paid to the nature of individual differences in the ways of experiencing and the realization of the successive steps of teenage motherhood: how the girls reacted to the fact of being a mother, what they experienced and how they behaved during pregnancy and performed child care. Participants and procedure In the research, 166 mothers who had given birth to their children between the 15th and 19th year of life were included (at the moment of giving birth to the child, the age of the mother was M = 17.22. A follower interview was used. It was directed towards recreating the course of their lives from the period preceding becoming pregnant to the period of pregnancy and looking after the child, taking into consideration the complex situations connected with life and development of the female teenagers. Results In the research, we applied the Reconstruction Strategy of the Process Transformation, setting the direction of qualitative analyses: (1 the level of single cases (case study, and (2 the level of the collection of cases (extracting groups of girls with common characteristics using the artificial intelligence algorithm C4.5. The analysis revealed the diversity and the internal structure of paths of the experience and realization of early motherhood: from negating oneself as a responsible mother to accepting the role of mother. Conclusions The final result is constituted by the model revealing the transformation of teenage motherhood and mechanisms underlying it.
Design with Nonlinear Constraints
Tang, Chengcheng
2015-12-10
Most modern industrial and architectural designs need to satisfy the requirements of their targeted performance and respect the limitations of available fabrication technologies. At the same time, they should reflect the artistic considerations and personal taste of the designers, which cannot be simply formulated as optimization goals with single best solutions. This thesis aims at a general, flexible yet e cient computational framework for interactive creation, exploration and discovery of serviceable, constructible, and stylish designs. By formulating nonlinear engineering considerations as linear or quadratic expressions by introducing auxiliary variables, the constrained space could be e ciently accessed by the proposed algorithm Guided Projection, with the guidance of aesthetic formulations. The approach is introduced through applications in different scenarios, its effectiveness is demonstrated by examples that were difficult or even impossible to be computationally designed before. The first application is the design of meshes under both geometric and static constraints, including self-supporting polyhedral meshes that are not height fields. Then, with a formulation bridging mesh based and spline based representations, the application is extended to developable surfaces including origami with curved creases. Finally, general approaches to extend hard constraints and soft energies are discussed, followed by a concluding remark outlooking possible future studies.
Iterative solution of a nonlinear system arising in phase change problems
International Nuclear Information System (INIS)
Williams, M.A.
1987-01-01
We consider several iterative methods for solving the nonlinear system arising from an enthalpy formulation of a phase change problem. We present the formulation of the problem. Implicit discretization of the governing equations results in a mildly nonlinear system at each time step. We discuss solving this system using Jacobi, Gauss-Seidel, and SOR iterations and a new modified preconditioned conjugate gradient (MPCG) algorithm. The new MPCG algorithm and its properties are discussed in detail. Numerical results are presented comparing the performance of the SOR algorithm and the MPCG algorithm with 1-step SSOR preconditioning. The MPCG algorithm exhibits a superlinear rate of convergence. The SOR algorithm exhibits a linear rate of convergence. Thus, the MPCG algorithm requires fewer iterations to converge than the SOR algorithm. However in most cases, the SOR algorithm requires less total computation time than the MPCG algorithm. Hence, the SOR algorithm appears to be more appropriate for the class of problems considered. 27 refs., 11 figs
Design and Realization of Universal Data Interface
Directory of Open Access Journals (Sweden)
Jong-Woo Kim
2005-03-01
Full Text Available KARI studied data interface of Space Applications for developing Space Experimental Instrument in International Space Station, designed, and manufactured the UDIS (International Sapce Station Universal Data Interface simulator according to requirements of the data interface. This paper explains the design and implementation of UDIS for space application. UDIS is the instrument which simulate to interface the data from ISS to experiment module, payload and habitation module and use the development of a experiment system in the space. This simulator will be used to the GSE (Ground Support Equipment for test of experiment system. By realization of the simulator, we ensure data interface skills for a manned-space data communication system.
Realized Variance and Market Microstructure Noise
DEFF Research Database (Denmark)
Hansen, Peter R.; Lunde, Asger
2006-01-01
We study market microstructure noise in high-frequency data and analyze its implications for the realized variance (RV) under a general specification for the noise. We show that kernel-based estimators can unearth important characteristics of market microstructure noise and that a simple kernel......-based estimator dominates the RV for the estimation of integrated variance (IV). An empirical analysis of the Dow Jones Industrial Average stocks reveals that market microstructure noise its time-dependent and correlated with increments in the efficient price. This has important implications for volatility...... estimation based on high-frequency data. Finally, we apply cointegration techniques to decompose transaction prices and bid-ask quotes into an estimate of the efficient price and noise. This framework enables us to study the dynamic effects on transaction prices and quotes caused by changes in the efficient...
Challenges in realizing ultraflat materials surfaces
Directory of Open Access Journals (Sweden)
Takashi Yatsui
2013-12-01
Full Text Available Ultraflat surface substrates are required to achieve an optimal performance of future optical, electronic, or optoelectronic devices for various applications, because such surfaces reduce the scattering loss of photons, electrons, or both at the surfaces and interfaces. In this paper, we review recent progress toward the realization of ultraflat materials surfaces. First, we review the development of surface-flattening techniques. Second, we briefly review the dressed photon–phonon (DPP, a nanometric quasiparticle that describes the coupled state of a photon, an electron, and a multimode-coherent phonon. Then, we review several recent developments based on DPP-photochemical etching and desorption processes, which have resulted in angstrom-scale flat surfaces. To confirm that the superior flatness of these surfaces that originated from the DPP process, we also review a simplified mathematical model that describes the scale-dependent effects of optical near-fields. Finally, we present the future outlook for these technologies.
Design and Realization of Intelligent Flow Controller
Directory of Open Access Journals (Sweden)
Jianxiong Ye
2014-09-01
Full Text Available According to accurate flow rate control requirements in large irrigation zone, a fuzzy controller with dead-band is designed on the characteristics analysis and comparison of PID and Fuzzy. The setting values of water flow for gates are determined by real-time water level detection sensors, and the realistic value of discharged water and gate opening are detected out with relative sensors, simulation manifest that the specific control strategy can adjust the gate swiftly in circumstance of huge offset, and regulate the gate slightly in time of small bias, it is realized with Siemens S315 PLC (Programmable Logical Controller and has being working steadily for 2 years, the aim of regulation is performed properly.
Realization of mechanical rotation in superfluid helium
Gordon, E. B.; Kulish, M. I.; Karabulin, A. V.; Matyushenko, V. I.; Dyatlova, E. V.; Gordienko, A. S.; Stepanov, M. E.
2017-09-01
The possibility of using miniaturized low-power electric motors submerged in superfluid helium for organization of rotation inside a cryostat has been investigated. It has been revealed that many of commercial micromotors can operate in liquid helium consuming low power. Turret with 5 sample holders, assembled on the base of stepper motor, has been successfully tested in experiments on the nanowire production in quantized vortices of superfluid helium. Application of the stepper motor made it possible in a single experiment to study the effect of various experimental parameters on the yield and quality of the nanowires. The promises for continuous fast rotation of the bath filled by superfluid helium by using high-speed brushless micromotor were outlined and tested. Being realized, this approach will open new possibility to study the guest particles interaction with the array of parallel linear vortices in He II.
On Poisson Nonlinear Transformations
Directory of Open Access Journals (Sweden)
Nasir Ganikhodjaev
2014-01-01
Full Text Available We construct the family of Poisson nonlinear transformations defined on the countable sample space of nonnegative integers and investigate their trajectory behavior. We have proved that these nonlinear transformations are regular.
Sparse electromagnetic imaging using nonlinear iterative shrinkage thresholding
Desmal, Abdulla; Bagci, Hakan
2015-01-01
A sparse nonlinear electromagnetic imaging scheme is proposed for reconstructing dielectric contrast of investigation domains from measured fields. The proposed approach constructs the optimization problem by introducing the sparsity constraint to the data misfit between the scattered fields expressed as a nonlinear function of the contrast and the measured fields and solves it using the nonlinear iterative shrinkage thresholding algorithm. The thresholding is applied to the result of every nonlinear Landweber iteration to enforce the sparsity constraint. Numerical results demonstrate the accuracy and efficiency of the proposed method in reconstructing sparse dielectric profiles.
Sparse electromagnetic imaging using nonlinear iterative shrinkage thresholding
Desmal, Abdulla
2015-04-13
A sparse nonlinear electromagnetic imaging scheme is proposed for reconstructing dielectric contrast of investigation domains from measured fields. The proposed approach constructs the optimization problem by introducing the sparsity constraint to the data misfit between the scattered fields expressed as a nonlinear function of the contrast and the measured fields and solves it using the nonlinear iterative shrinkage thresholding algorithm. The thresholding is applied to the result of every nonlinear Landweber iteration to enforce the sparsity constraint. Numerical results demonstrate the accuracy and efficiency of the proposed method in reconstructing sparse dielectric profiles.
Realization of Intelligent Household Appliance Wireless Monitoring Network Based on LEACH Protocol
Directory of Open Access Journals (Sweden)
Weilong ZHOU
2014-06-01
Full Text Available The intelligent household appliance wireless monitoring network can real-time monitor the apparent power and power factor of various household appliances in different indoor regions, and can realize the real-time monitoring on the household appliance working status and performance. The household appliance wireless monitoring network based on LEACH protocol is designed in the paper. Firstly, the basic idea of LEACH routing algorithm is proposed. Aiming at the node-distribution feature of intelligent home, the selection of cluster head in the routing algorithm and the data transmission method at the stable communication phase is modified. Moreover, the hardware circuit of power acquisition and power factor measurement is designed. The realization of wireless monitoring network based on CC2530 is described, each module and the whole system were conducted the on-line debugging. Finally, the system is proved to meet the practical requirement through the networking test.
Fuzzy Neuron: Method and Hardware Realization
Krasowski, Michael J.; Prokop, Norman F.
2014-01-01
This innovation represents a method by which single-to-multi-input, single-to-many-output system transfer functions can be estimated from input/output data sets. This innovation can be run in the background while a system is operating under other means (e.g., through human operator effort), or may be utilized offline using data sets created from observations of the estimated system. It utilizes a set of fuzzy membership functions spanning the input space for each input variable. Linear combiners associated with combinations of input membership functions are used to create the output(s) of the estimator. Coefficients are adjusted online through the use of learning algorithms.
Costiner, Sorin; Taasan, Shlomo
1994-01-01
This paper presents multigrid (MG) techniques for nonlinear eigenvalue problems (EP) and emphasizes an MG algorithm for a nonlinear Schrodinger EP. The algorithm overcomes the mentioned difficulties combining the following techniques: an MG projection coupled with backrotations for separation of solutions and treatment of difficulties related to clusters of close and equal eigenvalues; MG subspace continuation techniques for treatment of the nonlinearity; an MG simultaneous treatment of the eigenvectors at the same time with the nonlinearity and with the global constraints. The simultaneous MG techniques reduce the large number of self consistent iterations to only a few or one MG simultaneous iteration and keep the solutions in a right neighborhood where the algorithm converges fast.
Chen, Xianfeng; Zeng, Heping; Guo, Qi; She, Weilong
2015-01-01
This book presents an overview of the state of the art of nonlinear optics from weak light nonlinear optics, ultrafast nonlinear optics to electro-optical theory and applications. Topics range from the fundamental studies of the interaction between matter and radiation to the development of devices, components, and systems of tremendous commercial interest for widespread applications in optical telecommunications, medicine, and biotechnology.
International Nuclear Information System (INIS)
Ermolaev, P; Volynsky, M
2014-01-01
Recurrent stochastic data processing algorithms using representation of interferometric signal as output of a dynamic system, which state is described by vector of parameters, in some cases are more effective, compared with conventional algorithms. Interferometric signals depend on phase nonlinearly. Consequently it is expedient to apply algorithms of nonlinear stochastic filtering, such as Kalman type filters. An application of the second order extended Kalman filter and Markov nonlinear filter that allows to minimize estimation error is described. Experimental results of signals processing are illustrated. Comparison of the algorithms is presented and discussed.
Finding all solutions of nonlinear equations using the dual simplex method
Yamamura, Kiyotaka; Fujioka, Tsuyoshi
2003-03-01
Recently, an efficient algorithm has been proposed for finding all solutions of systems of nonlinear equations using linear programming. This algorithm is based on a simple test (termed the LP test) for nonexistence of a solution to a system of nonlinear equations using the dual simplex method. In this letter, an improved version of the LP test algorithm is proposed. By numerical examples, it is shown that the proposed algorithm could find all solutions of a system of 300 nonlinear equations in practical computation time.
An architecture design and realization of the industrial CT visualization system
International Nuclear Information System (INIS)
Gao Long; Li Zheng; Zhang Li; Gao Wenhuan; Kang Kejun
2003-01-01
The Industrial Computer Tomography (ICT) is an ideal and powerful technique for inspecting and evaluating the integrity of many large and complex structures. Three dimension visualization system is the main component of ICT inspection. This paper gives an architecture design and the realization of ICT visualization system on the basis of the system analysis. A new adaptive precision algorithm is brought out to solve the main problem of interactive speed. The paper also discussed the future research intention
MARKETING STRATEGY OF THE UNIVERSITY: FORMATION AND ITS EFFECTIVENESS EVALUATION REALIZATION
Natalia К. Shemetova
2015-01-01
The study is aimed at developing an algorithm of formation of university’s marketing strategy and the development of evaluating methods of its effectiveness realization. Despite the competitive expansion of the educational services market and the transition to a system of university self-financing, researchers have not paid due attention to the process of developing the marketing strategy of the university and the evaluation of its effectiveness yet. Methods. The applied methods include the m...
Realism in the Realized Popper's Experiment
Hunter, Geoffrey
2002-12-01
The realization of Karl Popper's EPR-like experiment by Shih and Kim (published 1999) produced the result that Popper hoped for: no ``action at a distance'' on one photon of an entangled pair when a measurement is made on the other photon. This experimental result is interpretable in local realistic terms: each photon has a definite position and transverse momentum most of the time; the position measurement on one photon (localization within a slit) disturbs the transverse momentum of that photon in a non-predictable way in accordance with the uncertainty principle; however, there is no effect on the other photon (the photon that is not in a slit) no action at a distance. The position measurement (localization within a slit) of the one photon destroys the coherence (entanglement) between the photons; i.e. decoherence occurs. This realistic (albeit retrodictive) interpretation of the Shih-Kim realization of what Popper called his ``crucial experiment'' is in accord with Bohr's original concept of the nature of the uncertainty principle, as being an inevitable effect of the disturbance of the measured system by the measuring apparatus. In this experiment the impact parameter of an incident photon with the centerline of the slit is an uncontrollable parameter of each individual photon scattering event; this impact parameter is variable for every incident photon, the variations being a statistical aspect of the beam of photons produced by the experimental arrangement. These experimental results are also in accord with the proposition of Einstein, Podolski and Rosen's 1935 paper: that quantum mechanics provides only a statistical, physically incomplete, theory of microscopic physical processes, for the quantum mechanical description of the experiment does not describe or explain the individual photon scattering events that are actually observed; the angle by which an individual photon is scattered is not predictable, because the photon's impact parameter with the
International Nuclear Information System (INIS)
Creutz, M.
1987-11-01
A large variety of Monte Carlo algorithms are being used for lattice gauge simulations. For purely bosonic theories, present approaches are generally adequate; nevertheless, overrelaxation techniques promise savings by a factor of about three in computer time. For fermionic fields the situation is more difficult and less clear. Algorithms which involve an extrapolation to a vanishing step size are all quite closely related. Methods which do not require such an approximation tend to require computer time which grows as the square of the volume of the system. Recent developments combining global accept/reject stages with Langevin or microcanonical updatings promise to reduce this growth to V/sup 4/3/
Hu, T C
2002-01-01
Newly enlarged, updated second edition of a valuable text presents algorithms for shortest paths, maximum flows, dynamic programming and backtracking. Also discusses binary trees, heuristic and near optimums, matrix multiplication, and NP-complete problems. 153 black-and-white illus. 23 tables.Newly enlarged, updated second edition of a valuable, widely used text presents algorithms for shortest paths, maximum flows, dynamic programming and backtracking. Also discussed are binary trees, heuristic and near optimums, matrix multiplication, and NP-complete problems. New to this edition: Chapter 9
Hanamura, Eiichi; Yamanaka, Akio
2007-01-01
This graduate-level textbook gives an introductory overview of the fundamentals of quantum nonlinear optics. Based on the quantum theory of radiation, Quantum Nonlinear Optics incorporates the exciting developments in novel nonlinear responses of materials (plus laser oscillation and superradiance) developed over the past decade. It deals with the organization of radiation field, interaction between electronic system and radiation field, statistics of light, mutual manipulation of light and matter, laser oscillation, dynamics of light, nonlinear optical response, and nonlinear spectroscopy, as well as ultrashort and ultrastrong laser pulse. Also considered are Q-switching, mode locking and pulse compression. Experimental and theoretical aspects are intertwined throughout.
Nonlinear dynamics and complexity
Luo, Albert; Fu, Xilin
2014-01-01
This important collection presents recent advances in nonlinear dynamics including analytical solutions, chaos in Hamiltonian systems, time-delay, uncertainty, and bio-network dynamics. Nonlinear Dynamics and Complexity equips readers to appreciate this increasingly main-stream approach to understanding complex phenomena in nonlinear systems as they are examined in a broad array of disciplines. The book facilitates a better understanding of the mechanisms and phenomena in nonlinear dynamics and develops the corresponding mathematical theory to apply nonlinear design to practical engineering.
Distributed nonlinear optical response
DEFF Research Database (Denmark)
Nikolov, Nikola Ivanov
2005-01-01
of bound states of out of phase bright solitons and dark solitons. Also, the newly introduced analogy between the nonlocal cubic nonlinear and the quadratic nonlinear media, presented in paper B and Chapter 3 is discussed. In particular it supplies intuitive physical meaning of the formation of solitons...... in quadratic nonlinear media. In the second part of the report (Chapter 4), the possibility to obtain light with ultrabroad spectrum due to the interplay of many nonlinear effects based on cubic nonlinearity is investigated thoroughly. The contribution of stimulated Raman scattering, a delayed nonlinear...... a modified nonlinear Schroedinger model equation. Chapter 4 and papers D and E are dedicated to this part of the research....
Identification of a Class of Non-linear State Space Models using RPE Techniques
DEFF Research Database (Denmark)
Zhou, Wei-Wu; Blanke, Mogens
1989-01-01
The RPE (recursive prediction error) method in state-space form is developed in the nonlinear systems and extended to include the exact form of a nonlinearity, thus enabling structure preservation for certain classes of nonlinear systems. Both the discrete and the continuous-discrete versions...... of the algorithm in an innovations model are investigated, and a nonlinear simulation example shows a quite convincing performance of the filter as combined parameter and state estimator...
Detrending the realized volatility in the global FX market
Schmidt, Anatoly B.
2009-05-01
There has been growing interest in realized volatility (RV) of financial assets that is calculated using intra-day returns. The choice of optimal time grid for these calculations is not trivial and generally requires analysis of RV dependence on the grid spacing (so-called RV signature). Typical RV signatures have a maximum at the finest time grid spacing available, which is attributed to the microstructure effects. This maximum decays into a plateau at lower frequencies, which implies (almost) stationary return variance. We found that the RV signatures in the modern global FX market may have no plateau or even have a maximum at lower frequencies. Simple averaging methods used to address the microstructure effects in equities have no practical effect on the FX RV signatures. We show that local detrending of the high-frequency FX rate samples yields RV signatures with a pronounced plateau. This implies that FX rates can be described with a Brownian motion having non-stationary trend and stationary variance. We point at a role of algorithmic trading as a possible cause of micro-trends in FX rates.
The Realization of Focus in Asturian Spanish
Directory of Open Access Journals (Sweden)
Covadonga Sánchez-Alvarado
2018-01-01
Full Text Available Spanish was classified as a language that only exploits syntactic mechanisms to mark focus. Recent experimental studies, nonetheless, have shown that speakers of different dialects are also able to use prosody to different degrees. This study aims to provide further understanding on the role played by prosody in the realization of focus in Spanish by looking at Asturian Spanish, a dialect in contact with another Romance language, Asturian. The data from a contextualized sentence completion task revealed that a phonological distinction between specific pitch categories (L+
Spontaneously broken realization of supersymmetry in supergravity
International Nuclear Information System (INIS)
Ferrara, S.; Trieste Univ.
1979-01-01
It is shown that if supersymmetry is relevant for the physical world it must be broken either spontaneously or explicitly. Renormalizability and simplicity are in favor of a spontaneous realization of the symmetry breaking. When supersymmetry is spontaneously broken the spinorial analogue of the Goldstone phenomenon occurs, namely massless particles arise in the spectrum of the theory which carry the same quantum numbers of the broken generators Qsup(i) they are N spin 1/2 Goldstone fermions (goldstinos). These particles may be eaten by spin 3/2 gauge particles (gravitinos) when supersymmetry is gauged. It is shown that both the Higgs effect and super Higgs effect have taken place. 8 of the spin 1/2 particles have been eaten by the spin 3/2 particles and 24 of 70 scalars have been eaten by the spin 3/2 particles and 24 of 70 scalars have been eaten by 24 of the 28 vector particles to provide them with mass. The conclusion is that the number of mass relations is, in general, equal to r-1, where r is the rank of the algebra which generates the spectrum
Realizing the potential of nuclear energy
International Nuclear Information System (INIS)
Walske, C.
1982-01-01
The future of nuclear power, just as the future of America, can be viewed with optimism. There is hope in America's record of overcoming obstacles, but growth is essential for that hope to be realized. Despite the downturn in energy demand made possible by conservation, we will need a 35% growth in total energy for new workers and production. Electricity generated by nuclear or coal can make US production more cost-competitive, and it can power mass-transit systems, electric heat pumps, and communications and information systems. Changes in electricity and gross national product (GNP) have been more closely in step since 1973 than have total energy and GNP. The nuclear power units now under construction will add 80,000 megawatts to the 56,000 now on line. It is important to note that, while utilities are cancelling plans for nuclear plants, they aren't ordering new coal plants, which shows the impact of the high cost of money. Interest rates must come down and public-relations efforts to sell electricity must improve to change the situation. Although capital shortages are real, waste disposal is a problem of perception that was politically induced because the government failed to provide a demonstration of safety as the French are doing. Streamlined regulatory and insurance procedures can help to justify optimism in the nuclear option. 4 figures
On the efficiency of chaos optimization algorithms for global optimization
International Nuclear Information System (INIS)
Yang Dixiong; Li Gang; Cheng Gengdong
2007-01-01
Chaos optimization algorithms as a novel method of global optimization have attracted much attention, which were all based on Logistic map. However, we have noticed that the probability density function of the chaotic sequences derived from Logistic map is a Chebyshev-type one, which may affect the global searching capacity and computational efficiency of chaos optimization algorithms considerably. Considering the statistical property of the chaotic sequences of Logistic map and Kent map, the improved hybrid chaos-BFGS optimization algorithm and the Kent map based hybrid chaos-BFGS algorithm are proposed. Five typical nonlinear functions with multimodal characteristic are tested to compare the performance of five hybrid optimization algorithms, which are the conventional Logistic map based chaos-BFGS algorithm, improved Logistic map based chaos-BFGS algorithm, Kent map based chaos-BFGS algorithm, Monte Carlo-BFGS algorithm, mesh-BFGS algorithm. The computational performance of the five algorithms is compared, and the numerical results make us question the high efficiency of the chaos optimization algorithms claimed in some references. It is concluded that the efficiency of the hybrid optimization algorithms is influenced by the statistical property of chaotic/stochastic sequences generated from chaotic/stochastic algorithms, and the location of the global optimum of nonlinear functions. In addition, it is inappropriate to advocate the high efficiency of the global optimization algorithms only depending on several numerical examples of low-dimensional functions
Nonlinear H-infinity control, Hamiltonian systems and Hamilton-Jacobi equations
Aliyu, MDS
2011-01-01
A comprehensive overview of nonlinear Haeu control theory for both continuous-time and discrete-time systems, Nonlinear Haeu-Control, Hamiltonian Systems and Hamilton-Jacobi Equations covers topics as diverse as singular nonlinear Haeu-control, nonlinear Haeu -filtering, mixed H2/ Haeu-nonlinear control and filtering, nonlinear Haeu-almost-disturbance-decoupling, and algorithms for solving the ubiquitous Hamilton-Jacobi-Isaacs equations. The link between the subject and analytical mechanics as well as the theory of partial differential equations is also elegantly summarized in a single chapter
Design, realization and structural testing of a compliant adaptable wing
International Nuclear Information System (INIS)
Molinari, G; Arrieta, A F; Ermanni, P; Quack, M; Morari, M
2015-01-01
This paper presents the design, optimization, realization and testing of a novel wing morphing concept, based on distributed compliance structures, and actuated by piezoelectric elements. The adaptive wing features ribs with a selectively compliant inner structure, numerically optimized to achieve aerodynamically efficient shape changes while simultaneously withstanding aeroelastic loads. The static and dynamic aeroelastic behavior of the wing, and the effect of activating the actuators, is assessed by means of coupled 3D aerodynamic and structural simulations. To demonstrate the capabilities of the proposed morphing concept and optimization procedure, the wings of a model airplane are designed and manufactured according to the presented approach. The goal is to replace conventional ailerons, thus to achieve controllability in roll purely by morphing. The mechanical properties of the manufactured components are characterized experimentally, and used to create a refined and correlated finite element model. The overall stiffness, strength, and actuation capabilities are experimentally tested and successfully compared with the numerical prediction. To counteract the nonlinear hysteretic behavior of the piezoelectric actuators, a closed-loop controller is implemented, and its capability of accurately achieving the desired shape adaptation is evaluated experimentally. Using the correlated finite element model, the aeroelastic behavior of the manufactured wing is simulated, showing that the morphing concept can provide sufficient roll authority to allow controllability of the flight. The additional degrees of freedom offered by morphing can be also used to vary the plane lift coefficient, similarly to conventional flaps. The efficiency improvements offered by this technique are evaluated numerically, and compared to the performance of a rigid wing. (paper)
Directory of Open Access Journals (Sweden)
Anna Bourmistrova
2011-02-01
Full Text Available The autodriver algorithm is an intelligent method to eliminate the need of steering by a driver on a well-defined road. The proposed method performs best on a four-wheel steering (4WS vehicle, though it is also applicable to two-wheel-steering (TWS vehicles. The algorithm is based on coinciding the actual vehicle center of rotation and road center of curvature, by adjusting the kinematic center of rotation. The road center of curvature is assumed prior information for a given road, while the dynamic center of rotation is the output of dynamic equations of motion of the vehicle using steering angle and velocity measurements as inputs. We use kinematic condition of steering to set the steering angles in such a way that the kinematic center of rotation of the vehicle sits at a desired point. At low speeds the ideal and actual paths of the vehicle are very close. With increase of forward speed the road and tire characteristics, along with the motion dynamics of the vehicle cause the vehicle to turn about time-varying points. By adjusting the steering angles, our algorithm controls the dynamic turning center of the vehicle so that it coincides with the road curvature center, hence keeping the vehicle on a given road autonomously. The position and orientation errors are used as feedback signals in a closed loop control to adjust the steering angles. The application of the presented autodriver algorithm demonstrates reliable performance under different driving conditions.
Explicit Nonlinear Model Predictive Control Theory and Applications
Grancharova, Alexandra
2012-01-01
Nonlinear Model Predictive Control (NMPC) has become the accepted methodology to solve complex control problems related to process industries. The main motivation behind explicit NMPC is that an explicit state feedback law avoids the need for executing a numerical optimization algorithm in real time. The benefits of an explicit solution, in addition to the efficient on-line computations, include also verifiability of the implementation and the possibility to design embedded control systems with low software and hardware complexity. This book considers the multi-parametric Nonlinear Programming (mp-NLP) approaches to explicit approximate NMPC of constrained nonlinear systems, developed by the authors, as well as their applications to various NMPC problem formulations and several case studies. The following types of nonlinear systems are considered, resulting in different NMPC problem formulations: Ø Nonlinear systems described by first-principles models and nonlinear systems described by black-box models; �...
Nonlinear Fuzzy Model Predictive Control for a PWR Nuclear Power Plant
Directory of Open Access Journals (Sweden)
Xiangjie Liu
2014-01-01
Full Text Available Reliable power and temperature control in pressurized water reactor (PWR nuclear power plant is necessary to guarantee high efficiency and plant safety. Since the nuclear plants are quite nonlinear, the paper presents nonlinear fuzzy model predictive control (MPC, by incorporating the realistic constraints, to realize the plant optimization. T-S fuzzy modeling on nuclear power plant is utilized to approximate the nonlinear plant, based on which the nonlinear MPC controller is devised via parallel distributed compensation (PDC scheme in order to solve the nonlinear constraint optimization problem. Improved performance compared to the traditional PID controller for a TMI-type PWR is obtained in the simulation.
Bootstrapping realized volatility and realized beta under a local Gaussianity assumption
DEFF Research Database (Denmark)
Hounyo, Ulrich
The main contribution of this paper is to propose a new bootstrap method for statistics based on high frequency returns. The new method exploits the local Gaussianity and the local constancy of volatility of high frequency returns, two assumptions that can simplify inference in the high frequency...... context, as recently explained by Mykland and Zhang (2009). Our main contributions are as follows. First, we show that the local Gaussian bootstrap is firstorder consistent when used to estimate the distributions of realized volatility and ealized betas. Second, we show that the local Gaussian bootstrap...... matches accurately the first four cumulants of realized volatility, implying that this method provides third-order refinements. This is in contrast with the wild bootstrap of Gonçalves and Meddahi (2009), which is only second-order correct. Third, we show that the local Gaussian bootstrap is able...
Polynomially decaying transmission for the nonlinear schrodinger equation in a random medium
International Nuclear Information System (INIS)
Devillard, P.; Sovillard, B.
1986-01-01
This is the first study of one the transmission problems associate to the nonlinear Schrodinger equation with a random potential. We show that for almost every realization of the medium the rate of transmission vanishes when increasing the size of the medium; however, whereas it decays exponentially in the linear regime, it decays polynomially in the nonlinear one
Preparation and realization of HPP Zilina
International Nuclear Information System (INIS)
Cizik, F.
1997-01-01
The results achieved in finishing of the preparation and in realization of the Hydro Power Project (HPP) Zilina proved advantageousness of such approach even if an increasing presence of eccentric competing interests should be mentioned. Integration of mutual interest within the established company limited by shares means to create equal conditions for all of the partners and not a power liquidation of specificities and not a power liquidation of specificities, specialties and individualities, both of value and legal ones. HPPs with power utilization must be built in such places in which there are suitable conditions for their operation created by the nature on a stream. Their power contribution is, as a rule, a contribution for the whole electric system. The part beneficial to the public is a contribution for the region affected by the construction. During the construction, they offer jobs not only, but especially, for the residents of the region affected by the construction but also for workers in cement works, brick works, steels works, and other kinds of industries providing supplies for the construction, industry of services. Changes in legislation supporting construction of HPPs with power utilization, purchasing system and electric energy prices remain still unsolved. Energy prices are distorted compared to relations in western in western market economies and do not allow either reproduction of a production base or gain and pay back the credits and compound interest. An additional idea of the state about financing the part of HPPs with power utilization beneficial to the public from resources gained in operation of the built objects without any form of easement of taxation and changes shifts a return of invested resources behind a border of an entrepreneurial interest
The Semantic Web: From Representation to Realization
Thórisson, Kristinn R.; Spivack, Nova; Wissner, James M.
A semantically-linked web of electronic information - the Semantic Web - promises numerous benefits including increased precision in automated information sorting, searching, organizing and summarizing. Realizing this requires significantly more reliable meta-information than is readily available today. It also requires a better way to represent information that supports unified management of diverse data and diverse Manipulation methods: from basic keywords to various types of artificial intelligence, to the highest level of intelligent manipulation - the human mind. How this is best done is far from obvious. Relying solely on hand-crafted annotation and ontologies, or solely on artificial intelligence techniques, seems less likely for success than a combination of the two. In this paper describe an integrated, complete solution to these challenges that has already been implemented and tested with hundreds of thousands of users. It is based on an ontological representational level we call SemCards that combines ontological rigour with flexible user interface constructs. SemCards are machine- and human-readable digital entities that allow non-experts to create and use semantic content, while empowering machines to better assist and participate in the process. SemCards enable users to easily create semantically-grounded data that in turn acts as examples for automation processes, creating a positive iterative feedback loop of metadata creation and refinement between user and machine. They provide a holistic solution to the Semantic Web, supporting powerful management of the full lifecycle of data, including its creation, retrieval, classification, sorting and sharing. We have implemented the SemCard technology on the semantic Web site Twine.com, showing that the technology is indeed versatile and scalable. Here we present the key ideas behind SemCards and describe the initial implementation of the technology.
Universal algorithm of time sharing
International Nuclear Information System (INIS)
Silin, I.N.; Fedyun'kin, E.D.
1979-01-01
Timesharing system algorithm is proposed for the wide class of one- and multiprocessor computer configurations. Dynamical priority is the piece constant function of the channel characteristic and system time quantum. The interactive job quantum has variable length. Characteristic recurrent formula is received. The concept of the background job is introduced. Background job loads processor if high priority jobs are inactive. Background quality function is given on the base of the statistical data received in the timesharing process. Algorithm includes optimal trashing off procedure for the jobs replacements in the memory. Sharing of the system time in proportion to the external priorities is guaranteed for the all active enough computing channels (back-ground too). The fast answer is guaranteed for the interactive jobs, which use small time and memory. The external priority control is saved for the high level scheduler. The experience of the algorithm realization on the BESM-6 computer in JINR is discussed
Gkillas (Gillas), Konstantinos; Vortelinos, Dimitrios I.; Saha, Shrabani
2018-02-01
This paper investigates the properties of realized volatility and correlation series in the Indian stock market by employing daily data converting to monthly frequency of five different stock indices from January 2, 2006 to November 30, 2014. Using non-parametric estimation technique the properties examined include normality, long-memory, asymmetries, jumps, and heterogeneity. The realized volatility is a useful technique which provides a relatively accurate measure of volatility based on the actual variance which is beneficial for asset management in particular for non-speculative funds. The results show that realized volatility and correlation series are not normally distributed, with some evidence of persistence. Asymmetries are also evident in both volatilities and correlations. Both jumps and heterogeneity properties are significant; whereas, the former is more significant than the latter. The findings show that properties of volatilities and correlations in Indian stock market have similarities as that show in the stock markets in developed countries such as the stock market in the United States which is more prevalent for speculative business traders.
A new chaotic algorithm for image encryption
International Nuclear Information System (INIS)
Gao Haojiang; Zhang Yisheng; Liang Shuyun; Li Dequn
2006-01-01
Recent researches of image encryption algorithms have been increasingly based on chaotic systems, but the drawbacks of small key space and weak security in one-dimensional chaotic cryptosystems are obvious. This paper presents a new nonlinear chaotic algorithm (NCA) which uses power function and tangent function instead of linear function. Its structural parameters are obtained by experimental analysis. And an image encryption algorithm in a one-time-one-password system is designed. The experimental results demonstrate that the image encryption algorithm based on NCA shows advantages of large key space and high-level security, while maintaining acceptable efficiency. Compared with some general encryption algorithms such as DES, the encryption algorithm is more secure
Quantum Nanoantennas for Making Nonlinear and Self-Modulatable Metasurface
Chen, Pai Yen
2015-01-01
We investigate the plasmonic nanodipole antenna with sub-microscopic nanogap. Relevant quantum conductivities, including linear and nonlinear components, are observed due to the photon-assisted quantum tunneling, realizing optical nano-radiators with enhanced amplitude and frequency modulations. © 2015 OSA.
On Similarity Invariance of Balancing for Nonlinear Systems
Scherpen, Jacquelien M.A.
1995-01-01
A previously obtained balancing method for nonlinear systems is investigated on similarity in variance by generalization of the observations on the similarity invariance of the linear balanced realization theory. For linear systems it is well known that the Hankel singular values are similarity
Two New PRP Conjugate Gradient Algorithms for Minimization Optimization Models.
Directory of Open Access Journals (Sweden)
Gonglin Yuan
Full Text Available Two new PRP conjugate Algorithms are proposed in this paper based on two modified PRP conjugate gradient methods: the first algorithm is proposed for solving unconstrained optimization problems, and the second algorithm is proposed for solving nonlinear equations. The first method contains two aspects of information: function value and gradient value. The two methods both possess some good properties, as follows: 1 βk ≥ 0 2 the search direction has the trust region property without the use of any line search method 3 the search direction has sufficient descent property without the use of any line search method. Under some suitable conditions, we establish the global convergence of the two algorithms. We conduct numerical experiments to evaluate our algorithms. The numerical results indicate that the first algorithm is effective and competitive for solving unconstrained optimization problems and that the second algorithm is effective for solving large-scale nonlinear equations.
Two New PRP Conjugate Gradient Algorithms for Minimization Optimization Models.
Yuan, Gonglin; Duan, Xiabin; Liu, Wenjie; Wang, Xiaoliang; Cui, Zengru; Sheng, Zhou
2015-01-01
Two new PRP conjugate Algorithms are proposed in this paper based on two modified PRP conjugate gradient methods: the first algorithm is proposed for solving unconstrained optimization problems, and the second algorithm is proposed for solving nonlinear equations. The first method contains two aspects of information: function value and gradient value. The two methods both possess some good properties, as follows: 1) βk ≥ 0 2) the search direction has the trust region property without the use of any line search method 3) the search direction has sufficient descent property without the use of any line search method. Under some suitable conditions, we establish the global convergence of the two algorithms. We conduct numerical experiments to evaluate our algorithms. The numerical results indicate that the first algorithm is effective and competitive for solving unconstrained optimization problems and that the second algorithm is effective for solving large-scale nonlinear equations.
Exponential GARCH Modeling with Realized Measures of Volatility
DEFF Research Database (Denmark)
Hansen, Peter Reinhard; Huang, Zhuo
returns and volatility. We apply the model to DJIA stocks and an exchange traded fund that tracks the S&P 500 index and find that specifications with multiple realized measures dominate those that rely on a single realized measure. The empirical analysis suggests some convenient simplifications......We introduce the Realized Exponential GARCH model that can utilize multiple realized volatility measures for the modeling of a return series. The model specifies the dynamic properties of both returns and realized measures, and is characterized by a flexible modeling of the dependence between...
DEFF Research Database (Denmark)
Markham, Annette
This paper takes an actor network theory approach to explore some of the ways that algorithms co-construct identity and relational meaning in contemporary use of social media. Based on intensive interviews with participants as well as activity logging and data tracking, the author presents a richly...... layered set of accounts to help build our understanding of how individuals relate to their devices, search systems, and social network sites. This work extends critical analyses of the power of algorithms in implicating the social self by offering narrative accounts from multiple perspectives. It also...... contributes an innovative method for blending actor network theory with symbolic interaction to grapple with the complexity of everyday sensemaking practices within networked global information flows....