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.
Hamiltonian Realizations of Nonlinear Adjoint Operators
Fujimoto, Kenji; Scherpen, Jacquelien M.A.; Gray, W. Steven
2000-01-01
This paper addresses state-space realizations for nonlinear adjoint operators. In particular the relationship among nonlinear Hilbert adjoint operators, Hamiltonian extensions and port-controlled Hamiltonian systems are clarified. The characterization of controllability, observability and Hankel
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)
Some experiences with the Eigensystem Realization Algorithm
Pappa, Richard S.; Juang, Jer-Nan
1988-01-01
The Eigensystem Realization Algorithm (ERA) is a multiinput/multioutput time-domain algorithm for minimum-order system realization and modal parameter identification. It has been used for structural dynamics data analysis at the Langley Research Center for several years. Some of the practical experiences encountered in these projects are discussed in this paper. Three examples are used: the Galileo spacecraft, the Solar Array Flight Experiment, and a laboratory space-truss model. Several techniques for assessing identification accuracy are illustrated.
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
Gradient realization of nonlinear control systems
Cortes monforte, J.; Cortés, J.; Crouch, P.E.; Astolfi, A.; van der Schaft, Arjan; Gordillo, F.
2003-01-01
We investigate necessary and su?cient conditions under which a nonlinear afine control system with outputs can be written as a gradient control system corresponding to some pseudo-Riemannian metric defined on the state space. The results rely on a suitable notion of compatibility of the system with
Electrodynamics: a consequence of nonlinear realizations of the Lorentz group
International Nuclear Information System (INIS)
Dalton, B.
1981-01-01
Extensions from the representations of the Lorentz group to include local nonlinear diagonal transformations is sufficient to generate, via the covariant derivative, the interaction of minimal coupling. These diagonal realizations are characterized by six functions phisub(i) which must satisfy a system of transformation equations. Inequivalent categories of solutions for the phisub(i) give rise to different electromagnetic fields. The Dirac monopole and Coulomb potentials follow directly from two different categories of these nonlinear realizations. Within this theory, charge becomes simply the nonlinear counterpart of intrinsic spin for a particular nonlinear realization of the Lorentz group. Charge is thus placed on equal footing with intrinsic spin in the sense that both phenomena can be described as consequences of our space-time symmetry. Other solutions for the six phisub(i) exist, including a spinor. The possibility that with these other solutions, these realizations could represent some other basic properties of elementary particles is discussed. (author)
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.
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
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
Nonlinear Gossip Algorithms for Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Chao Shi
2014-01-01
Full Text Available We study some nonlinear gossip algorithms for wireless sensor networks. Firstly, two types of nonlinear single gossip algorithms are proposed. By using Lyapunov theory, Lagrange mean value theorem, and stochastic Lasalle’s invariance principle, we prove that the nonlinear single gossip algorithms can converge to the average of initial states with probability one. Secondly, two types of nonlinear multigossip algorithms are also presented and the convergence is proved by the same methods. Finally, computer simulation is also given to show the validity of the theoretical results.
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)
Realization of structural maps drawing algorithm for petroleum deposits
International Nuclear Information System (INIS)
Begendikov, A.Zh.; Esekeev, K.B.; Kakimzhanov, E.P.; Shaporenko, D.A.
1997-01-01
One of algorithms for realization of map drawing with help of computer is considered in the paper. Essence of problem consists in recovering of field by selective measuring in few points and graphical image of iso-lines of this field. In the problem an error value has being admitted up 30 % from square limited by iso-line. Initial data of problem have been set of points with arbitrary coordinates in which field value is given. Algorithm is founded on programming of two-dimension function calculation, recovering value of field by means interpolation
Modeling of Nonlinear Systems using Genetic Algorithm
Hayashi, Kayoko; Yamamoto, Toru; Kawada, Kazuo
In this paper, a newly modeling system by using Genetic Algorithm (GA) is proposed. The GA is an evolutionary computational method that simulates the mechanisms of heredity or evolution of living things, and it is utilized in optimization and in searching for optimized solutions. Most process systems have nonlinearities, so it is necessary to anticipate exactly such systems. However, it is difficult to make a suitable model for nonlinear systems, because most nonlinear systems have a complex structure. Therefore the newly proposed method of modeling for nonlinear systems uses GA. Then, according to the newly proposed scheme, the optimal structure and parameters of the nonlinear model are automatically generated.
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.
Realization of non-linear coherent states by photonic lattices
Energy Technology Data Exchange (ETDEWEB)
Dehdashti, Shahram, E-mail: shdehdashti@zju.edu.cn; Li, Rujiang; Chen, Hongsheng, E-mail: hansomchen@zju.edu.cn [State Key Laboratory of Modern Optical Instrumentations, Zhejiang University, Hangzhou 310027 (China); The Electromagnetics Academy at Zhejiang University, Zhejiang University, Hangzhou 310027 (China); Liu, Jiarui, E-mail: jrliu@zju.edu.cn; Yu, Faxin [School of Aeronautics and Astronautics, Zhejiang University, Hangzhou 310027 (China)
2015-06-15
In this paper, first, by introducing Holstein-Primakoff representation of α-deformed algebra, we achieve the associated non-linear coherent states, including su(2) and su(1, 1) coherent states. Second, by using waveguide lattices with specific coupling coefficients between neighbouring channels, we generate these non-linear coherent states. In the case of positive values of α, we indicate that the Hilbert size space is finite; therefore, we construct this coherent state with finite channels of waveguide lattices. Finally, we study the field distribution behaviours of these coherent states, by using Mandel Q parameter.
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.
Non-linear realization of supersymmetry in de Sitter space
Zumino, B
1977-01-01
The author derives the non-linear transformation law and the non- linear Lagrangian for a Goldstone spinor corresponding to spontaneous breaking of global supersymmetry in a de Sitter space with O(3,2) invariance (anti de Sitter space). With a suitable choice of the Goldstone spinor field the Lagrangian agrees with the form suggested by the coupling to supergravity. The construction is also valid for the case of extended supersymmetry. (21 refs).
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.)
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
Single qudit realization of the Deutsch algorithm using superconducting many-level quantum circuits
Kiktenko, E. O.; Fedorov, A. K.; Strakhov, A. A.; Man'ko, V. I.
2015-07-01
Design of a large-scale quantum computer has paramount importance for science and technologies. We investigate a scheme for realization of quantum algorithms using noncomposite quantum systems, i.e., systems without subsystems. In this framework, n artificially allocated "subsystems" play a role of qubits in n-qubits quantum algorithms. With focus on two-qubit quantum algorithms, we demonstrate a realization of the universal set of gates using a d = 5 single qudit state. Manipulation with an ancillary level in the systems allows effective implementation of operators from U(4) group via operators from SU(5) group. Using a possible experimental realization of such systems through anharmonic superconducting many-level quantum circuits, we present a blueprint for a single qudit realization of the Deutsch algorithm, which generalizes previously studied realization based on the virtual spin representation (Kessel et al., 2002 [9]).
A Genetic Algorithm Approach to Nonlinear Least Squares Estimation
Olinsky, Alan D.; Quinn, John T.; Mangiameli, Paul M.; Chen, Shaw K.
2004-01-01
A common type of problem encountered in mathematics is optimizing nonlinear functions. Many popular algorithms that are currently available for finding nonlinear least squares estimators, a special class of nonlinear problems, are sometimes inadequate. They might not converge to an optimal value, or if they do, it could be to a local rather than…
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.
Robust Kernel Clustering Algorithm for Nonlinear System Identification
Directory of Open Access Journals (Sweden)
Mohamed Bouzbida
2017-01-01
Full Text Available In engineering field, it is necessary to know the model of the real nonlinear systems to ensure its control and supervision; in this context, fuzzy modeling and especially the Takagi-Sugeno fuzzy model has drawn the attention of several researchers in recent decades owing to their potential to approximate nonlinear behavior. To identify the parameters of Takagi-Sugeno fuzzy model several clustering algorithms are developed such as the Fuzzy C-Means (FCM algorithm, Possibilistic C-Means (PCM algorithm, and Possibilistic Fuzzy C-Means (PFCM algorithm. This paper presents a new clustering algorithm for Takagi-Sugeno fuzzy model identification. Our proposed algorithm called Robust Kernel Possibilistic Fuzzy C-Means (RKPFCM algorithm is an extension of the PFCM algorithm based on kernel method, where the Euclidean distance used the robust hyper tangent kernel function. The proposed algorithm can solve the nonlinear separable problems found by FCM, PCM, and PFCM algorithms. Then an optimization method using the Particle Swarm Optimization (PSO method combined with the RKPFCM algorithm is presented to overcome the convergence to a local minimum of the objective function. Finally, validation results of examples are given to demonstrate the effectiveness, practicality, and robustness of our proposed algorithm in stochastic environment.
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...
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
Directory of Open Access Journals (Sweden)
U. A. Sychou
2014-01-01
Full Text Available In this article, the problem of the practical realization of nonlinear systems with chaotic dynam-ics for targeted generation of chaotic sequences in digital devices is considered. The possible applica-tion in this task with using fixed-point arithmetic to ensure the identity of the obtained results on dif-ferent hardware and software platforms is studied. The implementation of logistic mapping is described; carry out the analysis of the results. This article proposes using the obtained results for the various tasks of the field of mobile robotics.
Experimental realization of Deutsch's algorithm in a one-way quantum computer.
Tame, M S; Prevedel, R; Paternostro, M; Böhi, P; Kim, M S; Zeilinger, A
2007-04-06
We report the first experimental demonstration of an all-optical one-way implementation of Deutsch's quantum algorithm on a four-qubit cluster state. All the possible configurations of a balanced or constant function acting on a two-qubit register are realized within the measurement-based model for quantum computation. The experimental results are in excellent agreement with the theoretical model, therefore demonstrating the successful performance of the algorithm.
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.
Comparative efficiencies of three parallel algorithms for nonlinear ...
Indian Academy of Sciences (India)
R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22
overall organisation and data structures of the program. Many researchers have devised algorithms for nonlinear dynamic analysis exploiting parallelism in both explicit and implicit time integration techniques. The explicit time integration algorithms like central difference method can easily be moved on to parallel pro-.
Nonlinear solution algorithms for reinforced concrete plates
International Nuclear Information System (INIS)
Hinton, E.; Abdel Rahman, H.H.
1981-01-01
The mertis of using the Quasi-Newton method in the finite element nonlinear analysis of reinforced concrete plates are investigated. Comparisons are made between Quasi-Newton methods and Newton-Raphson, modified Newton-Raphson and initial stress methods in terms of accuracy, limitations and efficiency.
Parallel algorithm of trigonometric collocation method in nonlinear dynamics of rotors
Directory of Open Access Journals (Sweden)
Musil T.
2007-11-01
Full Text Available A parallel algorithm of a numeric procedure based on a method of trigonometric collocation is presented for investigating an unbalance response of a rotor supported by journal bearings. After a condensation process the trigonometric collocation method results in a set of nonlinear algebraic equations which is solved by the Newton-Raphson method. The order of the set is proportional to the number of nonlinear bearing coordinates and terms of the finite Fourier series. The algorithm, realized in the MATLAB parallel computing environment (DCT/DCE, uses message passing technique for interacting among processes on nodes of a parallel computer. This technique enables portability of the source code both on parallel computers with distributed and shared memory. Tests, made on a Beowulf cluster and a symmetric multiprocessor, have revealed very good speed-up and scalability of this algorithm.
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
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)
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).
Appropriate Algorithms for Nonlinear Time Series Analysis in Psychology
Scheier, Christian; Tschacher, Wolfgang
Chaos theory has a strong appeal for psychology because it allows for the investigation of the dynamics and nonlinearity of psychological systems. Consequently, chaos-theoretic concepts and methods have recently gained increasing attention among psychologists and positive claims for chaos have been published in nearly every field of psychology. Less attention, however, has been paid to the appropriateness of chaos-theoretic algorithms for psychological time series. An appropriate algorithm can deal with short, noisy data sets and yields `objective' results. In the present paper it is argued that most of the classical nonlinear techniques don't satisfy these constraints and thus are not appropriate for psychological data. A methodological approach is introduced that is based on nonlinear forecasting and the method of surrogate data. In artificial data sets and empirical time series we can show that this methodology reliably assesses nonlinearity and chaos in time series even if they are short and contaminated by noise.
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)
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.
Nonlinear Observers for Gyro Calibration Coupled with a Nonlinear Control Algorithm
Thienel, Julie; Sanner, Robert M.
2003-01-01
Nonlinear observers for gyro calibration are presented. The first observer estimates a constant gyro bias. The second observer estimates scale factor errors. The third observer estimates the gyro alignment for three orthogonal gyros. The observers are then combined. The convergence properties of all three observers, and the combined observers, are discussed. Additionally, all three observers are coupled with a nonlinear control algorithm. The stability of each of the resulting closed loop systems is analyzed. Simulated test results are presented for each system.
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.
Juang, Jer-Nan; Cooper, J. E.; Wright, J. R.
1987-01-01
A modification to the Eigensystem Realization Algorithm (ERA) for modal parameter identification is presented in this paper. The ERA minimum order realization approach using singular value decomposition is combined with the philosophy of the Correlation Fit method in state space form such that response data correlations rather than actual response values are used for modal parameter identification. This new method, the ERA using data correlations (ERA/DC), reduces bias errors due to noise corruption significantly without the need for model overspecification. This method is tested using simulated five-degree-of-freedom system responses corrupted by measurement noise. It is found for this case that, when model overspecification is permitted and a minimum order solution obtained via singular value truncation, the results from the two methods are of similar quality.
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)
Research on fast algorithm of small UAV navigation in non-linear matrix reductionism method
Zhang, Xiao; Fang, Jiancheng; Sheng, Wei; Cao, Juanjuan
2008-10-01
The low Reynolds numbers of small UAV will result in unfavorable aerodynamic conditions to support controlled flight. And as operated near ground, the small UAV will be affected seriously by low-frequency interference caused by atmospheric disturbance. Therefore, the GNC system needs high frequency of attitude estimation and control to realize the steady of the UAV. In company with the dimensional of small UAV dwindling away, its GNC system is more and more taken embedded designing technology to reach the purpose of compactness, light weight and low power consumption. At the same time, the operational capability of GNC system also gets limit in a certain extent. Therefore, a kind of high speed navigation algorithm design becomes the imminence demand of GNC system. Aiming at such requirement, a kind of non-linearity matrix reduction approach is adopted in this paper to create a new high speed navigation algorithm which holds the radius of meridian circle and prime vertical circle as constant and linearizes the position matrix calculation formulae of navigation equation. Compared with normal navigation algorithm, this high speed navigation algorithm decreases 17.3% operand. Within small UAV"s mission radius (20km), the accuracy of position error is less than 0.13m. The results of semi-physical experiments and small UAV's auto pilot testing proved that this algorithm can realize high frequency attitude estimation and control. It will avoid low-frequency interference caused by atmospheric disturbance properly.
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.
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.
Realization of the FPGA based TDI algorithm in digital domain for CMOS cameras
Tao, Shuping; Jin, Guang; Zhang, Xuyan; Qu, Hongsong
2012-10-01
In order to make the CMOS image sensors suitable for space high resolution imaging applications, a new method realizing TDI in digital domain by FPGA is proposed in this paper, which improves the imaging mode for area array CMOS sensors. The TDI algorithm accumulates the corresponding pixels of adjoining frames in digital domain, so the gray values increase by M times, where M is for the integration number, and the image's quality in signal-to-noise ratio can be improved. In addition, the TDI optimization algorithm is discussed. Firstly, the signal storage is optimized by 2 slices of external RAM, where memory depth expanding and the table tennis operation mechanism are used. Secondly, the FIFO operation mechanism reduces the reading and writing operation on memory by M×(M-1) times, It saves so much signal transfer time as is proportional to the square of integration number M2, that the frame frequency is able to increase greatly. At last, the CMOS camera based on TDI in digital domain is developed, and the algorithm is validated by experiments on it.
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...
An Algorithm for Filtering Electrocardiograms to Improve Nonlinear Feature Extraction
Directory of Open Access Journals (Sweden)
Mohammad Bahmanyar
2007-04-01
Full Text Available This paper introduces an algorithm for removing high frequency noise components from electrocardiograms (ECGs based on Savitzky-Golay finite duration impulse response (FIR smoothing filter. The peaks of R waves and the points at which Q waves end and S waves start are detected for all beats. These points are used to separate the low amplitude parts of the ECG in each beat, which are most affected by high frequency noise. The Savitzky-Golay smoothing algorithm is then applied to these parts of the ECG and the resultant filtered signals are added back to their corresponding QRS parts. The effect of high frequency noise removal on nonlinear features such as largest Lyapunov exponent and minimum embedding dimension is also investigated. Performance of the filter has been compared with an equiripple low pass filter and wavelet de-noising.
A Prediction Error and Stepwise Regression Estimation Algorithm for Nonlinear Systems
Billings, S.A.; Voon, W.S.F.
1985-01-01
The identification of nonlinear systems based on a NARMAX (Nonlinear Autoregressive Moving Average model with exogenous inputs)model representation is considered and a combined stepwise regression/prediction error estimation algorithm is derived.
A Phase Plane Realization of a Class of Nonlinear Liquid Level ...
African Journals Online (AJOL)
... liquid level control system is presented for establishing the structure of a class of nonlinear systems with feedback loops which can be employed for liquid level control in petroleum storage tanks. The results presented here are intended for application, among others, in determining optimum operating conditions of storage ...
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.
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
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.)
A modified WTC algorithm for the Painlevé test of nonlinear variable-coefficient PDEs
Zhao, Yin-Long; Liu, Yin-Ping; Li, Zhi-Bin
2009-11-01
A modified WTC algorithm for the Painlevé test of nonlinear PDEs with variable coefficients is proposed. Compared to the Kruskal's simplification algorithm, the modified algorithm further simplifies the computation in the third step of the Painlevé test for variable-coefficient PDEs to some extent. Two examples illustrate the proposed modified algorithm.
Adaptive pinning control of deteriorated nonlinear coupling networks with circuit realization.
Jin, Xiao-Zheng; Yang, Guang-Hong; Che, Wei-Wei
2012-09-01
This paper deals with a class of complex networks with nonideal coupling networks, and addresses the problem of asymptotic synchronization of the complex network through designing adaptive pinning control and coupling adjustment strategies. A more general coupled nonlinearity is considered as perturbations of the network, while a serious faulty network named deteriorated network is also proposed to be further study. For the sake of eliminating these adverse impacts for synchronization, indirect adaptive schemes are designed to construct controllers and adjusters on pinned nodes and nonuniform couplings of un-pinned nodes, respectively. According to Lyapunov stability theory, the proposed adaptive strategies are successful in ensuring the achievement of asymptotic synchronization of the complex network even in the presence of perturbed and deteriorated networks. The proposed schemes are physically implemented by circuitries and tested by simulation on a Chua's circuit network.
Non-linear control algorithms for an unmanned surface vehicle
Sharma, SK; Sutton, R; Motwani, A; Annamalai, A
2014-01-01
Although intrinsically marine craft are known to exhibit non-linear dynamic characteristics, modern marine autopilot system designs continue to be developed based on both linear and non-linear control approaches. This article evaluates two novel non-linear autopilot designs based on non-linear local control network and non-linear model predictive control approaches to establish their effectiveness in terms of control activity expenditure, power consumption and mission duration length under si...
Non-linear formulas for the spinal cord injury ability realization measurement index.
Aidinoff, E; Benjamini, Y; Galili, T; Polliack, T; Front, L; Bluvshtein, V; Itzkovich, M; Hart, J; Catz, A
2012-04-01
The spinal cord injury ability realization measurement index (SCI-ARMI) assesses rehabilitation potential and efficacy based on the linear relationship between the Spinal Cord Independence Measure (SCIM) and the American Spinal Injury Association impairment scale (AIS) motor scores (AMS). The objective of this study is to develop new SCI-ARMI formulas using a more flexible approach that is less sensitive to the distribution of the AMS score among spinal cord lesion (SCL) patients. Loewenstein Rehabilitation Hospital, Raanana, and the Statistical Laboratory, School of Mathematics, Faculty of Exact Sciences, Tel-Aviv University, Israel. SCIM III and AMS of 226 Israeli SCL patients were monitored. Linear formulas, quadratic formulas and non-parametric formulas were estimated to express the relationship between the 95th percentile of the SCIM III values for patients with given AMS at discharge from rehabilitation (SCIM95) and the corresponding AMS value. This relationship was used to calculate SCI-ARMI values, defined as the ratio of the observed SCIM score and the respective SCIM95 for a given patient's AMS score. The estimated quadratic formula for the relationship between the 95th percentile of the SCIM III and the AMS score was found to be most appropriate, and formulas are provided for SCIM95 calculation in the various areas of function. The use of these formulas to calculate SCI-ARMI values is presented. The new formulas improve the accuracy of calculated ability realization for any AMS. The new statistical procedure will be used for the upcoming data analysis of a larger-scale international SCI-ARMI study.
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
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.
Non-linear cancer classification using a modified radial basis function classification algorithm.
Wang, Hong-Qiang; Huang, De-Shuang
2005-10-01
This paper proposes a modified radial basis function classification algorithm for non-linear cancer classification. In the algorithm, a modified simulated annealing method is developed and combined with the linear least square and gradient paradigms to optimize the structure of the radial basis function (RBF) classifier. The proposed algorithm can be adopted to perform non-linear cancer classification based on gene expression profiles and applied to two microarray data sets involving various human tumor classes: (1) Normal versus colon tumor; (2) acute myeloid leukemia (AML) versus acute lymphoblastic leukemia (ALL). Finally, accuracy and stability for the proposed algorithm are further demonstrated by comparing with the other cancer classification algorithms.
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.
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.
Comparative efficiencies of three parallel algorithms for nonlinear ...
Indian Academy of Sciences (India)
Transient dynamic analysis; parallel processing; Newmark algorithm; group implicit algorithm; domain decomposition. ... The prime aim of the research work reported here is to test the portability of the parallel algorithms and also to study and understand the comparative efﬁciencies of three parallel algorithms developed for ...
Directory of Open Access Journals (Sweden)
A. Spivakovsky
2010-06-01
Full Text Available The article presents a brief description of the features of the IDE of the course "Basis of algorithmization and programming" developed by the laboratory of integrated environments of learning RI IT in Kherson State University. As part of the disclosure of the theme "The computational experiment" are examples of solutions and analyze the efficiency of sorting algorithms for arrays of different length, is visual representation of their work means the module "Demonstration Environment", and also demonstrated several ways to determine the complexity of the execution time.
Directory of Open Access Journals (Sweden)
Yongquan Zhou
2013-01-01
Full Text Available In view of the traditional numerical method to solve the nonlinear equations exist is sensitive to initial value and the higher accuracy of defects. This paper presents an invasive weed optimization (IWO algorithm which has population diversity with the heuristic global search of differential evolution (DE algorithm. In the iterative process, the global exploration ability of invasive weed optimization algorithm provides effective search area for differential evolution; at the same time, the heuristic search ability of differential evolution algorithm provides a reliable guide for invasive weed optimization. Based on the test of several typical nonlinear equations and a circle packing problem, the results show that the differential evolution invasive weed optimization (DEIWO algorithm has a higher accuracy and speed of convergence, which is an efficient and feasible algorithm for solving nonlinear systems of equations.
A Model Predictive Algorithm for Active Control of Nonlinear Noise Processes
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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
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...
Directory of Open Access Journals (Sweden)
Wang Pidong
2016-01-01
Full Text Available Blind source separation is a hot topic in signal processing. Most existing works focus on dealing with linear combined signals, while in practice we always encounter with nonlinear mixed signals. To address the problem of nonlinear source separation, in this paper we propose a novel algorithm using radial basis function neutral network, optimized by multi-universe parallel quantum genetic algorithm. Experiments show the efficiency of the proposed method.
UNIVERSAL ALGORITHM OF NONLINEAR PROCESS NUMERICAL MODELLING OF REINFORCED CONSTRUCTION DEFORMATION
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Lizunov P.P.
2014-06-01
Full Text Available A numerical algorithm and software tools for the study of nonlinear deformation and fracture spatial concrete structures are developed. Finite element method is used. Numerical simulation of nonlinear deformation and fracture of materials is performed according to the phenomenological theories. Calculation algorithm is based on the Newton-Kantorovich method. The accuracy of the results was confirmed by comparison with experimental data and numerical calculations performed using other methods.
Non-linear squeezing of the vacuum and the one-photon states as realizations of the SU(1,1) group
Energy Technology Data Exchange (ETDEWEB)
Obada, A-S F [Department of Mathematics, Faculty of Science, Al-Azhar University, Nasr City 11884, Cairo (Egypt); Darwish, M [Department of Physics, Faculty of Education, Suez Canal University at Al-Arish (Egypt)
2005-02-01
We introduce a class of non-linear squeezed vacuum and one-photon states. Under conditions on the non-linearity function, these states are realizations of the SU(1,1) group. However, when a condition is removed, these states are defined as eigenstates of certain operators. Some of the properties of these states are investigated for the case of trapped ions. In particular, the Mandel q number, the photon number distribution, the phase properties, the Husimi-Kano Q-function and the Wigner-Moyal W-function of the non-linear squeezed one-photon states are discussed.
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.
Synthesis of nonlinear control strategies from fuzzy logic control algorithms
Langari, Reza
1993-01-01
Fuzzy control has been recognized as an alternative to conventional control techniques in situations where the plant model is not sufficiently well known to warrant the application of conventional control techniques. Precisely what fuzzy control does and how it does what it does is not quite clear, however. This important issue is discussed and in particular it is shown how a given fuzzy control scheme can resolve into a nonlinear control law and that in those situations the success of fuzzy control hinges on its ability to compensate for nonlinearities in plant dynamics.
A family of solution algorithms for nonlinear structural analysis based on relaxation equations
Park, K. C.
1981-01-01
A family of hierarchical algorithms for nonlinear structural equations are presented. The algorithms are based on the Davidenko-Branin type homotopy and shown to yield consistent hierarchical perturbation equations. The algorithms appear to be particularly suitable to problems involving bifurcation and limit point calculations. An important by-product of the algorithms is that it provides a systematic and economical means for computing the stepsize at each iteration stage when a Newton-like method is employed to solve the systems of equations. Some sample problems are provided to illustrate the characteristics of the algorithms.
Efficient algorithms for non-linear four-wave interactions
Van Vledder, G.P.
2012-01-01
This paper addresses the on-going activities in the development of efficient methods for computing the non-linear four-wave interactions in operational discrete third-generation wind-wave models. It is generally assumed that these interactions play an important role in the evolution of wind
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.
New nonlinear control algorithms for multiple robot arms
Tarn, T. J.; Bejczy, A. K.; Yun, X.
1988-01-01
Multiple coordinated robot arms are modeled by considering the arms as closed kinematic chains and as a force-constrained mechanical system working on the same object simultaneously. In both formulations, a novel dynamic control method is discussed. It is based on feedback linearization and simultaneous output decoupling technique. By applying a nonlinear feedback and a nonlinear coordinate transformation, the complicated model of the multiple robot arms in either formulation is converted into a linear and output decoupled system. The linear system control theory and optimal control theory are used to design robust controllers in the task space. The first formulation has the advantage of automatically handling the coordination and load distribution among the robot arms. In the second formulation, it was found that by choosing a general output equation it became possible simultaneously to superimpose the position and velocity error feedback with the force-torque error feedback in the task space.
Controller Parameter Optimization for Nonlinear Systems Using Enhanced Bacteria Foraging Algorithm
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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.
On a high-dimensional objective genetic algorithm and its nonlinear dynamic properties
Huang, Jun; Huang, Xiaohong; Ma, Yan; Liu, Yanbing
2011-09-01
The revival of multi-objective optimization is mainly resulted from the recent development of multi-objective evolutionary optimization that allows the generation of the overall Pareto front. This paper presents an algorithm called HOGA (High-dimensional Objective Genetic Algorithm) for high-dimensional objective optimization on the basis of evolutionary computing. It adopts the principle of Shannon entropy to calculate the weight for each object since the well-known multi-objective evolutionary algorithms work poorly on the high-dimensional optimization problem. To further discuss the nonlinear dynamic property of HOGA, a martingale analysis approach is then employed; some mathematical derivations of the convergent theorems are obtained. The obtained results indicate that this new algorithm is indeed capable of achieving convergence and the suggested martingale analysis approach provides a new methodology for nonlinear dynamic analysis of evolutionary algorithms.
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Šaponjić Đorđe
2009-01-01
Full Text Available By applying the well known dualism: mean count rate - mean time between successive pulses - the equivalence between an IIR digital filter and a preset count digital rate meter has been demonstrated. By using a bank of four second order IIR filters and an optimized automated algorithm for filter selection, a practical realization of a preset count rate meter giving good tradeoff between statistical fluctuations and speed of response, particularly at low count rates such as background monitoring, is presented. The presented solution is suitable for designing portable count rate meters. The designed prototype is capable of operating up to 3600 pulses per second with an accuracy of over 4% in steady-state and response times of 1 second for the rising edge and 2 seconds for the falling edge of the mean count rate step-change.
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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.
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.
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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.
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.
Comparative analysis of algorithms for compensation of nonlinear distortions in fibre-optic links
Burdin, V. A.; Bourdine, A. V.; Grigorov, I. V.
2017-12-01
We report the results of numerical modelling and comparative analysis of two algorithms for digital signal processing intended for signal demodulation in fibre-optic links (FOLs) operating in a nonlinear mode. The first algorithm is based on the use of nonlinear Schrödinger filters and the second one utilises the ‘reception in general with bit-by-bit decision making’ technique. It is found that the latter algorithm is more noiseproof, compared to the first one (with a SNR gain of about 0.5 dB), in single-channel fibre-optic links, and its operation does not require knowledge of the link parameters; therefore, the second algorithm can also be constructed for wavelength-division multiplexing systems.
An Archived firefly Algorithm; A mathematical software to solve univariate nonlinear equations
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M.K.A. Ariyaratne
2016-06-01
Full Text Available In this article, we are presenting a software solution that proposes some modifications to the existing firefly algorithm. The modification; archived firefly algorithm [AFFA] exhibits the ability of finding almost all complex roots of a given nonlinear equation within a reasonable range. The software implementation includes two main properties; an archive to collect the better fireflies and a flag to determine poor performance in firefly generations. The new modification is tested over genetic algorithms (GA, a phenomenal success in the field of nature inspired algorithms and also with a modified GA embedded with same properties that the AFFA has. A simple graphical user interface (GUI is developed using MATLAB GUIDE to present the findings. Computer simulations show that the AFFA performs well in solving nonlinear equations with real as well as complex roots within a specified region.
A hybrid algorithm and its applications to fuzzy logic modeling of nonlinear systems
Wang, Zhongjun
System models allow us to simulate and analyze system dynamics efficiently. Most importantly, system models allow us to make prediction about system behaviors and to perform system parametric variation analysis without having to build the actual systems. The fuzzy logic modeling technique has been successfully applied in complex nonlinear system modeling such as unsteady aerodynamics modeling etc. recently. However, the current forward search algorithm to identify fuzzy logic model structures is very time-consuming. It is not unusual to spend several days or even a few weeks in computer CPU time to obtain better nonlinear system model structures by this forward search. Moreover, how to speed up the fuzzy logic model parameter identification process is also challenging when the number of influencing variables of nonlinear systems is large. To solve these problems, a hybrid algorithm for the nonlinear system modeling is proposed, formalized, implemented, and evaluated in this dissertation. By combining the fuzzy logic modeling technique with genetic algorithms, the developed hybrid algorithm is applied to both fuzzy logic model structure identification and model parameter identification. In the model structure identification process, the hybrid algorithm has the ability to find feasible structures more efficiently and effectively than the forward search. In the model parameter identification process (by using Newton gradient descent algorithm), the proposed hybrid algorithm incorporates genetic search algorithm to dynamically select convergence factors. It has the advantages of quick search yet maintains the monotonically convergent properties of the Newton gradient descent algorithm. To evaluate the properties of the developed hybrid algorithm, a nonlinear, unsteady aerodynamic normal force model with a complex system involving fourteen influencing variables is established from flight data. The results show that this hybrid algorithm can identify the aerodynamic
A general-purpose contact detection algorithm for nonlinear structural analysis codes
Energy Technology Data Exchange (ETDEWEB)
Heinstein, M.W.; Attaway, S.W.; Swegle, J.W.; Mello, F.J.
1993-05-01
A new contact detection algorithm has been developed to address difficulties associated with the numerical simulation of contact in nonlinear finite element structural analysis codes. Problems including accurate and efficient detection of contact for self-contacting surfaces, tearing and eroding surfaces, and multi-body impact are addressed. The proposed algorithm is portable between dynamic and quasi-static codes and can efficiently model contact between a variety of finite element types including shells, bricks, beams and particles. The algorithm is composed of (1) a location strategy that uses a global search to decide which slave nodes are in proximity to a master surface and (2) an accurate detailed contact check that uses the projected motions of both master surface and slave node. In this report, currently used contact detection algorithms and their associated difficulties are discussed. Then the proposed algorithm and how it addresses these problems is described. Finally, the capability of the new algorithm is illustrated with several example problems.
A nonlinear active noise control algorithm for virtual microphones controlling chaotic noise.
Das, Debi Prasad; Moreau, Danielle J; Cazzolato, Ben S
2012-08-01
In active noise control (ANC) systems, virtual microphones provide a means of projecting the zone of quiet away from the physical microphone to a remote location. To date, linear ANC algorithms, such as the filtered-x least mean square (FXLMS) algorithm, have been used with virtual sensing techniques. In this paper, a nonlinear ANC algorithm is developed for a virtual microphone by integrating the remote microphone technique with the filtered-s least mean square (FSLMS) algorithm. The proposed algorithm is evaluated experimentally in the cancellation of chaotic noise in a one-dimensional duct. The secondary paths evaluated experimentally exhibit non-minimum phase response and hence poor performance is obtained with the conventional FXLMS algorithm compared to the proposed FSLMS based algorithm. This is because the latter is capable of predicting the chaotic signal found in many physical processes responsible for noise. In addition, the proposed algorithm is shown to outperform the FXLMS based remote microphone technique under the causality constraint (when the propagation delay of the secondary path is greater than the primary path). A number of experimental results are presented in this paper to compare the performance of the FSLMS algorithm based virtual ANC algorithm with the FXLMS based virtual ANC algorithm.
Indian Academy of Sciences (India)
In the previous articles, we have discussed various common data-structures such as arrays, lists, queues and trees and illustrated the widely used algorithm design paradigm referred to as 'divide-and-conquer'. Although there has been a large effort in realizing efficient algorithms, there are not many universally accepted ...
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.
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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.
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
An efficient algorithm for some highly nonlinear fractional PDEs in mathematical physics.
Ahmad, Jamshad; Mohyud-Din, Syed Tauseef
2014-01-01
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.
An efficient algorithm for some highly nonlinear fractional PDEs in mathematical physics.
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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 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
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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.
Data loss for PLC of nonlinear systems Iterative Learning Control Algorithm
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Zhang Yinjun
2016-01-01
Full Text Available When we use power line as data carrier, due to the complexity of the PLC network environment, data packet loss frequently, so the paper deal with the iterative learning control for a class of nonlinear systems with measurement dropouts in the PLC, and studies the P-type iterative learning control algorithm convergence issues, the data packet loss is described as a stochastic Bernoulli process, on this basis we given convergence conditions for the P-type iterative learning control algorithm. The theoretically analysis is supported by the simulation of a numerical example; the convergence of ILC can be guaranteed when some output measurements are missing.
Rafique, Danish; Mussolin, Marco; Forzati, Marco; Mårtensson, Jonas; Chugtai, Mohsan N; Ellis, Andrew D
2011-05-09
We investigate a digital back-propagation simplification method to enable computationally-efficient digital nonlinearity compensation for a coherently-detected 112 Gb/s polarization multiplexed quadrature phase shifted keying transmission over a 1,600 km link (20 x 80 km) with no inline compensation. Through numerical simulation, we report up to 80% reduction in required back-propagation steps to perform nonlinear compensation, in comparison to the standard back-propagation algorithm. This method takes into account the correlation between adjacent symbols at a given instant using a weighted-average approach, and optimization of the position of nonlinear compensator stage to enable practical digital back-propagation. © 2011 Optical Society of America
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Aijia Ouyang
2015-01-01
Full Text Available Nonlinear Muskingum models are important tools in hydrological forecasting. In this paper, we have come up with a class of new discretization schemes including a parameter θ to approximate the nonlinear Muskingum model based on general trapezoid formulas. The accuracy of these schemes is second order, if θ≠1/3, but interestingly when θ=1/3, the accuracy of the presented scheme gets improved to third order. Then, the present schemes are transformed into an unconstrained optimization problem which can be solved by a hybrid invasive weed optimization (HIWO algorithm. Finally, a numerical example is provided to illustrate the effectiveness of the present methods. The numerical results substantiate the fact that the presented methods have better precision in estimating the parameters of nonlinear Muskingum models.
Continuous Genetic Algorithm as a Novel Solver for Stokes and Nonlinear Navier Stokes Problems
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Z. S. Abo-Hammour
2014-01-01
Full Text Available The one-dimensional continuous genetic algorithm (CGA previously developed by the principal author is extended and enhanced to deal with two-dimensional spaces in this paper. The enhanced CGA converts the partial differential equations into algebraic equations by replacing the derivatives appearing in the differential equation with their proper finite difference formula in 2D spaces. This optimization methodology is then applied for the solution of steady-state two-dimensional Stokes and nonlinear Navier Stokes problems. The main advantage of using CGA for the solution of partial differential equations is that the algorithm can be applied to linear and nonlinear equations without any modification in its structure. A comparison between the results obtained using the 2D CGA and the known Galerkin finite element method using COMSOL is presented in this paper. The results showed that CGA has an excellent accuracy as compared to other numerical solvers.
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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.
Acikmese, Ahmet Behcet; Carson, John M., III
2006-01-01
A robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems is developed that guarantees resolvability. With resolvability, initial feasibility of the finite-horizon optimal control problem implies future feasibility in a receding-horizon framework. The control consists of two components; (i) feed-forward, and (ii) feedback part. Feed-forward control is obtained by online solution of a finite-horizon optimal control problem for the nominal system dynamics. The feedback control policy is designed off-line based on a bound on the uncertainty in the system model. The entire controller is shown to be robustly stabilizing with a region of attraction composed of initial states for which the finite-horizon optimal control problem is feasible. The controller design for this algorithm is demonstrated on a class of systems with uncertain nonlinear terms that have norm-bounded derivatives and derivatives in polytopes. An illustrative numerical example is also provided.
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
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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
A novel control algorithm of dual flyback inverter suitable for dynamic and nonlinear loads
Energy Technology Data Exchange (ETDEWEB)
Cernan, P. [Clayton Power Research and Development, Trencin (Slovakia); Sul, R.; Dobrucky, B. [Zilina Univ., Zilina (Slovakia)
2010-08-13
The dual flyback inverter (DFBI) is one of the preferred topologies for isolated low power low cost photovoltaic (PV) inverters. It can be employed for grid connected power systems or for island operation power systems. Island operation necessitates a high performance output voltage control algorithm which will ensure that output alternating current voltage will stay quasi harmonic and within operating limits under the different load and input voltage conditions. This paper introduced a unique control algorithm of DFBI suitable for dynamic and nonlinear loads. Functionality of control loop was verified by computer simulation with different loads on the output of DFBI. Specifically, the paper presented a circuit diagram of DFBI with an active clamp circuit as well as the novel control algorithm. The dimensioning of power stage components for DFBI simulation was also discussed. The results achieved by Simetrix simulation were presented. It was concluded that the algorithm could be utilized for dynamic or nonlinear loads without significant deformation of output voltage. 13 refs., 1 tab., 10 figs.
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.
A parallel nonlinear adaptive enhancement algorithm for low- or high-intensity color images
Zhou, Zhigang; Sang, Nong; Hu, Xinrong
2014-12-01
This article addresses the problem of color image enhancement for images with low or high intensity and poor contrast (LIPC or HIPC). A parallel nonlinear adaptive enhancement (PNAE) algorithm using information from local neighborhood is presented to resolve the problem in parallel. The PNAE algorithm consists of three steps. First, a red-green-blue (RGB) color image is converted to an intensity image, then an adaptive intensity adjustment with local contrast enhancement is parallelly performed, and finally, colors are restored. The PNAE algorithm can be adjusted to control the level of enhancement on the overall lightness and the contrast achieved at the output separately. Most of the parameters used in PNAE are robust for LIPC and HIPC color image enhancement. Experimental results show that PNAE outperforms two popular methods in both computational efficiency and overall content preservation of image while improving local contrast for LIPC and HIPC image enhancement.
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
Xiaoyan Lei; Shenhua Wu; Bin Zhang
2016-01-01
A model for dynamic analysis of the vehicle-track nonlinear coupling system is established by the finite element method. The whole system is divided into two subsystems: the vehicle subsystem and the track subsystem. Coupling of the two subsystems is achieved by equilibrium conditions for wheel-to-rail nonlinear contact forces and geometrical compatibility conditions. To solve the nonlinear dynamics equations for the vehicle-track coupling system, a cross iteration algorithm and a relaxation ...
Memetic Algorithms to Solve a Global Nonlinear Optimization Problem. A Review
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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
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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.
On resource-efficient algorithm for non-linear systems approximate reachability set construction
Parshikov, G. V.; Matviychuk, A. R.
2017-10-01
The research considers the numerical solution method of the reachability set construction problem for non-linear dynamical system in n-dimensional Euclidean space. The study deals with the dynamical system on the finite time interval, which is described by differential equation satisfying a set of defined conditions. The existing step-by-step pixel methods are based on the time interval sampling and applying the step-by-step reachability set constructing procedure to every time moment in partition. These methods allow us to solve the approximate reachability set constructing problem for the complex non-linear systems, which do not have analytical solutions. However, applying these methods causes a sharp increase of number of points used for reachability set constructing on the next step of time partition. This results in increase of calculation time as well as lack of computing device memory. To reduce the calculation time and satisfy the existing constraints of used device memory, we developed the set filtration algorithm based on some way of picking the points, which are used on the next step of reachability set constructing algorithm. Moreover, the computations are moved from CPU to the CUDA based on GPU, which allows us to run computations with the hundreds of parallel threads. In this research, we provide the description of the algorithm and give some information about its efficiency.
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
Fuzzy rule base design using tabu search algorithm for nonlinear system modeling.
Bagis, Aytekin
2008-01-01
This paper presents an approach to fuzzy rule base design using tabu search algorithm (TSA) for nonlinear system modeling. TSA is used to evolve the structure and the parameter of fuzzy rule base. The use of the TSA, in conjunction with a systematic neighbourhood structure for the determination of fuzzy rule base parameters, leads to a significant improvement in the performance of the model. To demonstrate the effectiveness of the presented method, several numerical examples given in the literature are examined. The results obtained by means of the identified fuzzy rule bases are compared with those belonging to other modeling approaches in the literature. The simulation results indicate that the method based on the use of a TSA performs an important and very effective modeling procedure in fuzzy rule base design in the modeling of the nonlinear or complex systems.
Yang, Ji Seung; Cai, Li
2014-01-01
The main purpose of this study is to improve estimation efficiency in obtaining maximum marginal likelihood estimates of contextual effects in the framework of nonlinear multilevel latent variable model by adopting the Metropolis-Hastings Robbins-Monro algorithm (MH-RM). Results indicate that the MH-RM algorithm can produce estimates and standard…
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.
Directory of Open Access Journals (Sweden)
Te-Jen Su
2016-12-01
Full Text Available The objective of this article is to optimize parameters of a hybrid sliding mode controller based on fireworks algorithm for a nonlinear inverted pendulum system. The proposed controller is a combination of two modified types of the classical sliding mode controller, namely, baseline sliding mode controller and fast output sampling discrete sliding mode controller. The simulation process is carried out with MATLAB/Simulink. The results are compared with a published hybrid method using proportional–integral–derivative and linear quadratic regulator controllers. The simulation results show a better performance of the proposed controller.
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)
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Vecchio Pietro
2011-01-01
Full Text Available Abstract The Bio-inspired (Bi-i Cellular Vision System is a computing platform consisting of sensing, array sensing-processing, and digital signal processing. The platform is based on the Cellular Neural/Nonlinear Network (CNN paradigm. This article presents the implementation of a novel CNN-based segmentation algorithm onto the Bi-i system. Each part of the algorithm, along with the corresponding implementation on the hardware platform, is carefully described through the article. The experimental results, carried out for Foreman and Car-phone video sequences, highlight the feasibility of the approach, which provides a frame rate of about 26 frames/s. Comparisons with existing CNN-based methods show that the conceived approach is more accurate, thus representing a good trade-off between real-time requirements and accuracy.
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.
Overgaard, Rune V; Jonsson, Niclas; Tornøe, Christoffer W; Madsen, Henrik
2005-02-01
Pharmacokinetic/pharmacodynamic modelling is most often performed using non-linear mixed-effects models based on ordinary differential equations with uncorrelated intra-individual residuals. More sophisticated residual error models as e.g. stochastic differential equations (SDEs) with measurement noise can in many cases provide a better description of the variations, which could be useful in various aspects of modelling. This general approach enables a decomposition of the intra-individual residual variation epsilon into system noise w and measurement noise e. The present work describes implementation of SDEs in a non-linear mixed-effects model, where parameter estimation was performed by a novel approximation of the likelihood function. This approximation is constructed by combining the First-Order Conditional Estimation (FOCE) method used in non-linear mixed-effects modelling with the Extended Kalman Filter used in models with SDEs. Fundamental issues concerning the proposed model and estimation algorithm are addressed by simulation studies, concluding that system noise can successfully be separated from measurement noise and inter-individual variability.
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
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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.
DEFF Research Database (Denmark)
Rubæk, Tonny; Meaney, P. M.; Meincke, Peter
2007-01-01
Breast-cancer screening using microwave imaging is emerging as a new promising technique as a supplement to X-ray mammography. To create tomographic images from microwave measurements, it is necessary to solve a nonlinear inversion problem, for which an algorithm based on the iterative Gauss-Newton...... method has been developed at Dartmouth College. This algorithm determines the update values at each iteration by solving the set of normal equations of the problem using the Tikhonov algorithm. In this paper, a new algorithm for determining the iteration update values in the Gauss-Newton algorithm...... algorithm is compared to the Gauss-Newton algorithm with Tikhonov regularization and is shown to reconstruct images of similar quality using fewer iterations....
Numerical nonlinear complex geometrical optics algorithm for the 3D Calderón problem
DEFF Research Database (Denmark)
Delbary, Fabrice; Knudsen, Kim
2014-01-01
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...... 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...... to the simpler approximations. In addition, convergence of the numerical solution towards the exact solution of the boundary integral equation is proved....
Boi, Fabio; Semprini, Marianna; Vato, Alessandro
2016-08-01
Motor brain-machine interfaces (BMIs) transform neural activities recorded directly from the brain into motor commands to control the movements of an external object by establishing an interface between the central nervous system (CNS) and the device. Bidirectional BMIs are closed-loop systems that add a sensory channel to provide the brain with an artificial feedback signal produced by the interaction between the device and the external world. Taking inspiration from the functioning of the spinal cord in mammalians, in our previous works we designed and developed a bidirectional BMI that uses the neural signals recorded form rats' motor cortex to control the movement of an external object. We implemented a decoding interface based on the approximation of a predefined force field with a central attractor point. Now we consider a non-linear transformation that allows to design a decoder approximating force fields with arbitrary attractors. We describe here the non-linear mapping algorithm and preliminary results of its use with behaving rats.
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...
Li, Yong; Yuan, Gonglin; Wei, Zengxin
2015-01-01
In this paper, a trust-region algorithm is proposed for large-scale nonlinear equations, where the limited-memory BFGS (L-M-BFGS) update matrix is used in the trust-region subproblem to improve the effectiveness of the algorithm for large-scale problems. The global convergence of the presented method is established under suitable conditions. The numerical results of the test problems show that the method is competitive with the norm method.
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.
About the Use of the HdHr Algorithm Group in Integrating the Movement Equation with Nonlinear Terms
Directory of Open Access Journals (Sweden)
Heitor Miranda Bottura
2009-01-01
Full Text Available This work summarizes the HdHr group of Hermitian integration algorithms for dynamic structural analysis applications. It proposes a procedure for their use when nonlinear terms are present in the equilibrium equation. The simple pendulum problem is solved as a first example and the numerical results are discussed. Directions to be pursued in future research are also mentioned.
DEFF Research Database (Denmark)
Boiroux, Dimitri; Hagdrup, Morten; Mahmoudi, Zeinab
2016-01-01
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...
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
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).
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Xiaoyan Lei
2016-01-01
Full Text Available A model for dynamic analysis of the vehicle-track nonlinear coupling system is established by the finite element method. The whole system is divided into two subsystems: the vehicle subsystem and the track subsystem. Coupling of the two subsystems is achieved by equilibrium conditions for wheel-to-rail nonlinear contact forces and geometrical compatibility conditions. To solve the nonlinear dynamics equations for the vehicle-track coupling system, a cross iteration algorithm and a relaxation technique are presented. Examples of vibration analysis of the vehicle and slab track coupling system induced by China’s high speed train CRH3 are given. In the computation, the influences of linear and nonlinear wheel-to-rail contact models and different train speeds are considered. It is found that the cross iteration algorithm and the relaxation technique have the following advantages: simple programming; fast convergence; shorter computation time; and greater accuracy. The analyzed dynamic responses for the vehicle and the track with the wheel-to-rail linear contact model are greater than those with the wheel-to-rail nonlinear contact model, where the increasing range of the displacement and the acceleration is about 10%, and the increasing range of the wheel-to-rail contact force is less than 5%.
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.
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.
Designing A Nonlinear Integer Programming Model For A Cross-Dock By A Genetic Algorithm
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Bahareh Vaisi
2015-03-01
Full Text Available Abstract This paper presents a non-linear integer programming model for a cross-dock problem that considers the total transportation cost of inbound and outbound trucks from an origin to a destination and the total cost of assigning strip and stack doors to trucks based on their number of trips and the distance between doors in cross-dock. In previous studies these two cost-based problems are modeled separately however it is more realistic and practical to use both of them as an integrated cross-docking model. Additionally this model is solved for a randomly generated numerical example with three suppliers and two customers by the use of a genetic algorithm. By comparing two different parameter levels i.e. low and high numbers of populations the optimum solution is obtained considering a high level population size. A number of strip and stack doors are equal to a number of inbound and outbound trucks in the same sequence as 4 and 6 respectively. Finally the conclusion is presented.
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.
An efficient algorithm for solving nonlinear system of differential equations and applications
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Mustafa GÜLSU
2015-10-01
Full Text Available In this article, we apply Chebyshev collocation method to obtain the numerical solutions of nonlinear systems of differential equations. This method transforms the nonlinear systems of differential equation to nonlinear systems of algebraic equations. The convergence of the numerical method are given and their applicability is illustrated with some examples.
A comparison of Eulerian and Lagrangian transport and non-linear reaction algorithms
Benson, David A.; Aquino, Tomás; Bolster, Diogo; Engdahl, Nicholas; Henri, Christopher V.; Fernàndez-Garcia, Daniel
2017-01-01
When laboratory-measured chemical reaction rates are used in simulations at the field-scale, the models typically overpredict the apparent reaction rates. The discrepancy is primarily due to poorer mixing of chemically distinct waters at the larger scale. As a result, realistic field-scale predictions require accurate simulation of the degree of mixing between fluids. The Lagrangian particle-tracking (PT) method is a now-standard way to simulate the transport of conservative or sorbing solutes. The method's main advantage is the absence of numerical dispersion (and its artificial mixing) when simulating advection. New algorithms allow particles of different species to interact in nonlinear (e.g., bimolecular) reactions. Therefore, the PT methods hold a promise of more accurate field-scale simulation of reactive transport because they eliminate the masking effects of spurious mixing due to advection errors inherent in grid-based methods. A hypothetical field-scale reaction scenario is constructed and run in PT and Eulerian (finite-volume/finite-difference) simulators. Grid-based advection schemes considered here include 1st- to 3rd-order spatially accurate total-variation-diminishing flux-limiting schemes, both of which are widely used in current transport/reaction codes. A homogeneous velocity field in which the Courant number is everywhere unity, so that the chosen Eulerian methods incur no error when simulating advection, shows that both the Eulerian and PT methods can achieve convergence in the L1 (integrated concentration) norm, but neither shows stricter pointwise convergence. In this specific case with a constant dispersion coefficient and bimolecular reaction A + B → P , the correct total amount of product is 0.221MA0, where MA0 is the original mass of reactant A. When the Courant number drops, the grid-based simulations can show remarkable errors due to spurious over- and under-mixing. In a heterogeneous velocity field (keeping the same constant and
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 ...
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...
Nonlinear physical segmentation algorithm for determining the layer boundary from lidar signal.
Mao, Feiyue; Li, Jun; Li, Chen; Gong, Wei; Min, Qilong; Wang, Wei
2015-11-30
Layer boundary (base and top) detection is a basic problem in lidar data processing, the results of which are used as inputs of optical properties retrieval. However, traditional algorithms not only require manual intervention but also rely heavily on the signal-to-noise ratio. Therefore, we propose a robust and automatic algorithm for layer detection based on a novel algorithm for lidar signal segmentation and representation. Our algorithm is based on the lidar equation and avoids most of the limitations of the traditional algorithms. Testing of the simulated and real signals shows that the algorithm is able to position the base and top accurately even with a low signal to noise ratio. Furthermore, the results of the classification are accurate and satisfactory. The experimental results confirm that our algorithm can be used for automatic detection, retrieval, and analysis of lidar data sets.
Gálvez, Akemi; Iglesias, Andrés
2013-01-01
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. PMID:24376380
National Aeronautics and Space Administration — This paper presents a novel set of uncertainty measures to quantify the impact of input uncertainty on nonlinear prognosis systems. A Particle Filtering-based method...
Algorithmic Approximation of Optimal Value Differential Stability Bounds in Nonlinear Programming,
1981-08-01
NCLASSIFIED RANO/PA6659 N IN *~4 112.0.0 ~11111,.. I32 111 IIIII 111111.25 MICROCOPY RESOLUTION TESI CHART NATIOt AL BJRLAU Of SIANDARD 1964 A * LEVEL 00 o pm...Sensitivity Analysis in Parametric Nonlinear Programming, Doctoral Dissertation, School of Engineering and Applied Science, The George Washington University...Differential Stability of the Optimal Value Function in Constrained Nonlinear Programing, Doctoral Disser- tation, School of Engineering and Applied
2015-04-24
achieved by formulating the obstacle avoidance problem into an optimal control problem (OCP), which is then converted into a nonlinear programming ( NLP ...time OCP is transcribed into to a nonlinear programming ( NLP ) problem using a direct method called hp-pseudospectral method [29], [30], [31]. Second...the resulting NLP problem is solved using the interior point method [32]. The hp-pseudospectral method discretizes a continuous-time OCP into an NLP
Directory of Open Access Journals (Sweden)
Wei Zhang
2016-06-01
Full Text Available 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.
Energy Technology Data Exchange (ETDEWEB)
Bagheri, Saman; Nikkar, Ali [University of Tabriz, Tabriz (Iran, Islamic Republic of)
2014-11-15
This paper deals with the determination of approximate solutions for a model of column buckling using two efficient and powerful methods called He's variational approach and variational iteration algorithm-II. These methods are used to find analytical approximate solution of nonlinear dynamic equation of a model for the column buckling. First and second order approximate solutions of the equation of the system are achieved. To validate the solutions, the analytical results have been compared with those resulted from Runge-Kutta 4th order method. A good agreement of the approximate frequencies and periodic solutions with the numerical results and the exact solution shows that the present methods can be easily extended to other nonlinear oscillation problems in engineering. The accuracy and convenience of the proposed methods are also revealed in comparisons with the other solution techniques.
DEFF Research Database (Denmark)
Kjems, Ulrik; Storther, Stephen C.; Anderson, Jon
1999-01-01
This paper addresses the problem of neuro-anatomical registration across individuals for functional [15O]water PET activation studies. A new algorithm for 3D non-linear structural registration (warping) of MR scans is presented. The method performs a hierarchically scaled search for a displacement...... field maximizing one of several voxel similarity measures derived from the two dimensional histogram of matched image intensities, subject to a regularizer that ensures smoothness of the displacement field. The effect of the non-line ar structural registration is studied when it is computed...... on anatomical MR scans and applied to co-registered [15O] water PET scans from the same subjects; in this experiment a study of visually guided saccadic eye movements. The performance of the non-linear warp is evaluated using multivariate functional signal and noise measures. These measures prove to be useful...
Directory of Open Access Journals (Sweden)
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.
Directory of Open Access Journals (Sweden)
Malyj Wasyl
2005-08-01
Full Text Available Abstract Background Life processes are determined by the organism's genetic profile and multiple environmental variables. However the interaction between these factors is inherently non-linear 1. Microarray data is one representation of the nonlinear interactions among genes and genes and environmental factors. Still most microarray studies use linear methods for the interpretation of nonlinear data. In this study, we apply Isomap, a nonlinear method of dimensionality reduction, to analyze three independent large Affymetrix high-density oligonucleotide microarray data sets. Results Isomap discovered low-dimensional structures embedded in the Affymetrix microarray data sets. These structures correspond to and help to interpret biological phenomena present in the data. This analysis provides examples of temporal, spatial, and functional processes revealed by the Isomap algorithm. In a spinal cord injury data set, Isomap discovers the three main modalities of the experiment – location and severity of the injury and the time elapsed after the injury. In a multiple tissue data set, Isomap discovers a low-dimensional structure that corresponds to anatomical locations of the source tissues. This model is capable of describing low- and high-resolution differences in the same model, such as kidney-vs.-brain and differences between the nuclei of the amygdala, respectively. In a high-throughput drug screening data set, Isomap discovers the monocytic and granulocytic differentiation of myeloid cells and maps several chemical compounds on the two-dimensional model. Conclusion Visualization of Isomap models provides useful tools for exploratory analysis of microarray data sets. In most instances, Isomap models explain more of the variance present in the microarray data than PCA or MDS. Finally, Isomap is a promising new algorithm for class discovery and class prediction in high-density oligonucleotide data sets.
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
Bauer, Frank (Technical Monitor); Luquette, Richard J.; Sanner, Robert M.
2003-01-01
Precision Formation Flying is an enabling technology for a variety of proposed space-based observatories, including the Micro-Arcsecond X-ray Imaging Mission (MAXIM), the associated MAXIM pathfinder mission, and the Stellar Imager. An essential element of the technology is the control algorithm. This paper discusses the development of a nonlinear, six-degree of freedom (6DOF) control algorithm for maintaining the relative position and attitude of a spacecraft within a formation. The translation dynamics are based on the equations of motion for the restricted three body problem. The control law guarantees the tracking error convergences to zero, based on a Lyapunov analysis. The simulation, modelled after the MAXIM Pathfinder mission, maintains the relative position and attitude of a Follower spacecraft with respect to a Leader spacecraft, stationed near the L2 libration point in the Sun-Earth system.
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.......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...
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
Wilson, Emma D; Assaf, Tareq; Pearson, Martin J; Rossiter, Jonathan M; Anderson, Sean R; Porrill, John; Dean, Paul
2016-09-01
Electroactive polymer actuators are important for soft robotics, but can be difficult to control because of compliance, creep and nonlinearities. Because biological control mechanisms have evolved to deal with such problems, we investigated whether a control scheme based on the cerebellum would be useful for controlling a nonlinear dielectric elastomer actuator, a class of artificial muscle. The cerebellum was represented by the adaptive filter model, and acted in parallel with a brainstem, an approximate inverse plant model. The recurrent connections between the two allowed for direct use of sensory error to adjust motor commands. Accurate tracking of a displacement command in the actuator's nonlinear range was achieved by either semi-linear basis functions in the cerebellar model or semi-linear functions in the brainstem corresponding to recruitment in biological muscle. In addition, allowing transfer of training between cerebellum and brainstem as has been observed in the vestibulo-ocular reflex prevented the steady increase in cerebellar output otherwise required to deal with creep. The extensibility and relative simplicity of the cerebellar-based adaptive-inverse control scheme suggests that it is a plausible candidate for controlling this type of actuator. Moreover, its performance highlights important features of biological control, particularly nonlinear basis functions, recruitment and transfer of training. © 2016 The Authors.
Feigin, Alexander; Gavrilov, Andrey; Loskutov, Evgeny; Mukhin, Dmitry
2015-04-01
Proper decomposition of the complex system into well separated "modes" is a way to reveal and understand the mechanisms governing the system behaviour as well as discover essential feedbacks and nonlinearities. The decomposition is also natural procedure that provides to construct adequate and concurrently simplest models of both corresponding sub-systems, and of the system in whole. In recent works two new methods of decomposition of the Earth's climate system into well separated modes were discussed. The first method [1-3] is based on the MSSA (Multichannel Singular Spectral Analysis) [4] for linear expanding vector (space-distributed) time series and makes allowance delayed correlations of the processes recorded in spatially separated points. The second one [5-7] allows to construct nonlinear dynamic modes, but neglects delay of correlations. It was demonstrated [1-3] that first method provides effective separation of different time scales, but prevent from correct reduction of data dimension: slope of variance spectrum of spatio-temporal empirical orthogonal functions that are "structural material" for linear spatio-temporal modes, is too flat. The second method overcomes this problem: variance spectrum of nonlinear modes falls essentially sharply [5-7]. However neglecting time-lag correlations brings error of mode selection that is uncontrolled and increases with growth of mode time scale. In the report we combine these two methods in such a way that the developed algorithm allows constructing nonlinear spatio-temporal modes. The algorithm is applied for decomposition of (i) multi hundreds years globally distributed data generated by the INM RAS Coupled Climate Model [8], and (ii) 156 years time series of SST anomalies distributed over the globe [9]. We compare efficiency of different methods of decomposition and discuss the abilities of nonlinear spatio-temporal modes for construction of adequate and concurrently simplest ("optimal") models of climate systems
Extension of the SAEM algorithm for nonlinear mixed models with two levels of random effects
Panhard, Xavière; Samson, Adeline
2008-01-01
This article focuses on parameter estimation of multi-levels nonlinear mixed effects models (MNLMEMs). These models are used to analyze data presenting multiple hierarchical levels of grouping (cluster data, clinical trials with several observation periods,...). The variability of the individual parameters of the regression function is thus decomposed as a between-sub ject variability and higher levels of variability (for example within-sub ject variability). We propose maximum likelihood est...
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....
Ayub, Kamran; Khan, M. Yaqub; Mahmood-Ul-Hassan, Qazi; Ahmad, Jamshad
2017-09-01
Nonlinear mathematical problems and their solutions attain much attention in solitary waves. In soliton theory, an efficient tool to attain various types of soliton solutions is the \\exp (-φ (ζ ))-expansion technique. This article is devoted to find exact travelling wave solutions of Drinfeld-Sokolov equation via a reliable mathematical technique. By using the proposed technique, we attain soliton wave solution of various types. It is observed that the technique under discussion is user friendly with minimum computational work, and can be extended for physical problems of different nature in mathematical physics.
Convergent Analysis of Energy Conservative Algorithm for the Nonlinear Schrödinger Equation
Directory of Open Access Journals (Sweden)
Lv Zhong-Quan
2015-01-01
Full Text Available Using average vector field method in time and Fourier pseudospectral method in space, we obtain an energy-preserving scheme for the nonlinear Schrödinger equation. We prove that the proposed method conserves the discrete global energy exactly. A deduction argument is used to prove that the numerical solution is convergent to the exact solution in discrete L2 norm. Some numerical results are reported to illustrate the efficiency of the numerical scheme in preserving the energy conservation law.
Directory of Open Access Journals (Sweden)
P. S. Hiremath
2008-01-01
recognition in the framework of symbolic data analysis. Classical KDA extracts features, which are single-valued in nature to represent face images. These single-valued variables may not be able to capture variation of each feature in all the images of same subject; this leads to loss of information. The symbolic KDA algorithm extracts most discriminating nonlinear interval-type features which optimally discriminate among the classes represented in the training set. The proposed method has been successfully tested for face recognition using two databases, ORL database and Yale face database. The effectiveness of the proposed method is shown in terms of comparative performance against popular face recognition methods such as kernel Eigenface method and kernel Fisherface method. Experimental results show that symbolic KDA yields improved recognition rate.
CHAM: a fast algorithm of modelling non-linear matter power spectrum in the sCreened HAlo Model
Hu, Bin; Liu, Xue-Wen; Cai, Rong-Gen
2018-02-01
We present a fast numerical screened halo model algorithm (CHAM) for modeling non-linear power spectrum for the alternative models to ΛCDM. 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. Second, the least assumptions are made in the calculation. Hence, the physical picture is very easily understandable. Third, it is very predictable and does not rely on the calibration from N-body simulation. As an example, we show the case of Hu-Sawicki f(R) gravity. In this case, the typical CPU time with the current parallel Python script (8 threads) is roughly within 10 minutes. The resulting spectra are in a good agreement with N-body data within a few percentage accuracy up to k ˜ 1 h/Mpc.
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.
Fontes, Fernando A. C. C.; Paiva, Luís T.
2016-10-01
We address optimal control problems for nonlinear systems with pathwise state-constraints. These are challenging non-linear problems for which the number of discretization points is a major factor determining the computational time. Also, the location of these points has a major impact in the accuracy of the solutions. We propose an algorithm that iteratively finds an adequate time-grid to satisfy some predefined error estimate on the obtained trajectories, which is guided by information on the adjoint multipliers. The obtained results show a highly favorable comparison against the traditional equidistant-spaced time-grid methods, including the ones using discrete-time models. This way, continuous-time plant models can be directly used. The discretization procedure can be automated and there is no need to select a priori the adequate time step. Even if the optimization procedure is forced to stop in an early stage, as might be the case in real-time problems, we can still obtain a meaningful solution, although it might be a less accurate one. The extension of the procedure to a Model Predictive Control (MPC) context is proposed here. By defining a time-dependent accuracy threshold, we can generate solutions that are more accurate in the initial parts of the receding horizon, which are the most relevant for MPC.
Indian Academy of Sciences (India)
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 language Is called a program. From activities 1-3, we can observe that: • Each activity is a command.
Chen, Weijie; Metz, Charles E; Giger, Maryellen L; Drukker, Karen
2010-02-01
Classifier design for a given classification task needs to take into consideration both the complexity of the classifier and the size of the dataset that is available for training the classifier. With limited training data, as often is the situation in computer-aided diagnosis of medical images, a classifier with simple structure (e.g., a linear classifier) is more robust and therefore preferred. We propose a novel two-class classifier, which we call a hybrid linear/nonlinear classifier (HLNLC), that involves two stages: the input features are linearly combined to form a scalar variable in the first stage and then the likelihood ratio of the scalar variable is used as the decision variable for classification. We first develop the theory of HLNLC by assuming that the feature data follow normal distributions. We show that the commonly used Fisher's linear discriminant function is generally not the optimal linear function in the first stage of the HLNLC. We formulate an optimization problem to solve for the optimal linear function in the first stage of the HLNLC, i.e., the linear function that maximizes the area under the receiver operating characteristic (ROC) curve of the HLNLC. For practical applications, we propose a robust implementation of the HLNLC by making a loose assumption that the two-class feature data arise from a pair of latent (rather than explicit) multivariate normal distributions. The novel hybrid classifier fills a gap between linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) in the sense that both its theoretical performance and its complexity lie between those of the LDA and those of the QDA. Simulation studies show that the hybrid linear/nonlinear classifier performs better than LDA without increasing the classifier complexity accordingly. With a finite number of training samples, the HLNLC can perform better than that of the ideal observer due to its simplicity. Finally, we demonstrate the application of the HLNLC in
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.
Yang, Ji Seung; Cai, Li
2013-01-01
The main purpose of this study is to improve estimation efficiency in obtaining full-information maximum likelihood (FIML) estimates of contextual effects in the framework of a nonlinear multilevel latent variable model by adopting the Metropolis-Hastings Robbins-Monro algorithm (MH-RM; Cai, 2008, 2010a, 2010b). Results indicate that the MH-RM…
Modeling Nonlinear Systems by a Fuzzy Logic Neural Network Using Genetic Algorithms
Directory of Open Access Journals (Sweden)
Abdel-Fattah Attia
2001-01-01
Full Text Available The main aim of this work is to optimize the parameters of the constrained membership function of the Fuzzy Logic Neural Network (FLNN. The constraints may be an indirect definition of the search ranges for every membership shape forming parameter based on 2nd order fuzzy set specifications. A particular method widely applicable in solving global optimization problems is introduced. This approach uses a Linear Adapted Genetic Algorithm (LAGA to optimize the FLNN parameters. In this paper the derivation of a 2nd order fuzzy set is performed for a membership function of Gaussian shape, which is assumed for the neuro-fuzzy approach. The explanation of the optimization method is presented in detail on the basis of two examples.
Indian Academy of Sciences (India)
algorithms such as synthetic (polynomial) division have been found in Vedic Mathematics which are dated much before Euclid's algorithm. A programming language ... ·1 x:=sln(theta) x : = sm(theta) 1. ~. Idl d.t Read A.B,C. ~ lei ~ Print x.y.z. L;;;J. Figure 2 Symbols used In flowchart language to rep- resent Assignment, Read.
International Nuclear Information System (INIS)
Ghasemi, Mojtaba; Ghavidel, Sahand; Akbari, Ebrahim; Vahed, Ali Azizi
2014-01-01
Invasive Weed Optimization (IWO) algorithm is a simple but powerful algorithm which is capable of solving general multi-dimensional, linear and nonlinear optimization problems with appreciable efficiency. Recently IWO algorithm is being used in several engineering design owing to its superior performance in comparison with many other existing algorithms. This paper presents a Chaotic IWO (CIWO) algorithms based on chaos, and investigates its performance for optimal settings of Optimal Power Flow (OPF) control variables of OPF problem with non-smooth and non-convex generator fuel cost curves (non-smooth and non-convex OPF). The performance of CIWO algorithms are studied and evaluated on the standard IEEE 30-bus test system with different objective functions. The experimental results suggest that IWO algorithm holds immense promise to appear as an efficient and powerful algorithm for optimization in the power system. - Highlights: • OPF problem has been solved considering non-smooth and non-convex fuel cost curves. • CIWO algorithms have been used based on chaos for solving OPF problem. • A comparative study of the proposed algorithms has been presented comprehensively
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.
Indian Academy of Sciences (India)
guesses for the technique discussed above. The method described above for computing the approximate square root is referred to as Newton's method for finding..Ja after the famous English mathematician Isaac Newton. In Table 5, we have essentially solved the nonlinear equation. RESONANCE I March 1996 - ---- .
Roozegar, Mehdi; Mahjoob, Mohammad J.; Ayati, Moosa
2017-05-01
This paper deals with adaptive estimation of the unknown parameters and states of a pendulum-driven spherical robot (PDSR), which is a nonlinear in parameters (NLP) chaotic system with parametric uncertainties. Firstly, the mathematical model of the robot is deduced by applying the Newton-Euler methodology for a system of rigid bodies. Then, based on the speed gradient (SG) algorithm, the states and unknown parameters of the robot are estimated online for different step length gains and initial conditions. The estimated parameters are updated adaptively according to the error between estimated and true state values. Since the errors of the estimated states and parameters as well as the convergence rates depend significantly on the value of step length gain, this gain should be chosen optimally. Hence, a heuristic fuzzy logic controller is employed to adjust the gain adaptively. Simulation results indicate that the proposed approach is highly encouraging for identification of this NLP chaotic system even if the initial conditions change and the uncertainties increase; therefore, it is reliable to be implemented on a real robot.
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.
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.
Indian Academy of Sciences (India)
In the program shown in Figure 1, we have repeated the algorithm. M times and we can make the following observations. Each block is essentially a different instance of "code"; that is, the objects differ by the value to which N is initialized before the execution of the. "code" block. Thus, we can now avoid the repetition of the ...
Indian Academy of Sciences (India)
algorithms built into the computer corresponding to the logic- circuit rules that are used to .... For the purpose of carrying ou t ari thmetic or logical operations the memory is organized in terms .... In fixed point representation, one essentially uses integer arithmetic operators assuming the binary point to be at some point other ...
Asif, Rameez; Usman, Muhammad; Lin, Chien-Yu; Schmauss, Bernhard
2012-09-01
In this paper, we numerically investigate the non-linear tolerance of root-raised-cosine (RRC) pulse shaping by interpolating finite impulse response (FIR) filters in conjunction with digital backward propagation (DBP) in coherent 112 Gbit s-1 dual-polarization quadrature phase shift keying (DP-QPSK) transmission. The results depict that RRC pulses are more tolerant to intra-channel non-linearities, i.e. self-phase modulation (SPM), as compared to standard RZ-33 and NRZ pulses. The non-linear threshold point is improved by using RRC pulses by a factor of 2 dB signal input power as compared to RZ pulses and by 4 dB signal launch power as compared to NRZ pulses. The behavior of RRC pulses is also investigated with standard single mode fiber (SMF), non-zero dispersion shifted fiber (NZDSF) and next-generation large Aeff pure silica core fiber (LA-PSCF). Most importantly multi-span DBP is implemented and in the case of RRC pulses the computational efforts of the conventional DBP algorithm are reduced by 80% with a diminutive Q-penalty of 0.74 dB. The duty cycle of the RRC pulses is further optimized for efficient system performance. We have also compared the performance of single-channel transmission with the multi-channel transmission, where the performance is limited due to inter-channel non-linear effects. Furthermore, the non-linear tolerance of RRC pulses is investigated with; (a) different amplifier spacing and (b) variation in transmission link design information for the DBP algorithm.
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
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)
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.
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
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.
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-propagatio......-propagation algorithms in the framework of recurrent back-propagation and present some numerical simulations of feed-forward networks on the NetTalk problem. A discussion of implementation in analog VLSI electronics concludes the paper.......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...
Endelt, B.
2017-09-01
Forming operation are subject to external disturbances and changing operating conditions e.g. new material batch, increasing tool temperature due to plastic work, material properties and lubrication is sensitive to tool temperature. It is generally accepted that forming operations are not stable over time and it is not uncommon to adjust the process parameters during the first half hour production, indicating that process instability is gradually developing over time. Thus, in-process feedback control scheme might not-be necessary to stabilize the process and an alternative approach is to apply an iterative learning algorithm, which can learn from previously produced parts i.e. a self learning system which gradually reduces error based on historical process information. What is proposed in the paper is a simple algorithm which can be applied to a wide range of sheet-metal forming processes. The input to the algorithm is the final flange edge geometry and the basic idea is to reduce the least-square error between the current flange geometry and a reference geometry using a non-linear least square algorithm. The ILC scheme is applied to a square deep-drawing and the Numisheet’08 S-rail benchmark problem, the numerical tests shows that the proposed control scheme is able control and stabilise both processes.
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.
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.
Zhu, Hong-Ming; Yu, Yu; Pen, Ue-Li; Chen, Xuelei; Yu, Hao-Ran
2017-12-01
We present a direct approach to nonparametrically reconstruct the linear density field from an observed nonlinear map. We solve for the unique displacement potential consistent with the nonlinear density and positive definite coordinate transformation using a multigrid algorithm. We show that we recover the linear initial conditions up to the nonlinear scale (rδrδL>0.5 for k ≲1 h /Mpc ) with minimal computational cost. This reconstruction approach generalizes the linear displacement theory to fully nonlinear fields, potentially substantially expanding the baryon acoustic oscillations and redshift space distortions information content of dense large scale structure surveys, including for example SDSS main sample and 21 cm intensity mapping initiatives.
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...
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.
Directory of Open Access Journals (Sweden)
Yakup YÄ±ldÄ±rÄ±m
Full Text Available In this study, we perform the extended Kudryashov method to nonlinear SchrÃ¶dinger equation (NLSE with spatio-temporal dispersion that arises in a propagation of light in nonlinear optical fibers, planar waveguides, BoseâEinstein condensate theory. Four types of nonlinearity â Kerr law, power law, parabolic law and dual-power law â are being considered for the model. By using this scheme, the topological, singular soliton and rational solutions are obtained. In addition, some graphical simulations of solutions are provided.It is demonstrated that the proposed algorithm is effective and can be handled for many other nonlinear complex differential equations. Keywords: Solitons, Nonlinear SchrÃ¶dinger equation with spatio-temporal dispersion, Extended Kudryashovâs method
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
Directory of Open Access Journals (Sweden)
Xuefei Yu
2018-01-01
Full Text Available 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.
A nonlinearity compensation method for a matrix converter drive
DEFF Research Database (Denmark)
Lee, Kyo-Beum; Blaabjerg, Frede
2005-01-01
This paper presents a new method to compensate the nonlinearities for matrix converter drives. The nonlinearities of matrix converter drives such as commutation delay, turn-on and turn-off time of the switching devices, and on-state switching device voltage drop is corrected by a new matrix...... converter model using the direction of current. The proposed method does not need any additional hardware or complicated software and it is easy to realize by applying the algorithm to the conventional vector control. The proposed compensation method is applied for high-performance induction motor drives...
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
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...
Gomeni, Roberto; Bressolle-Gomeni, Françoise; Fava, Maurizio
2016-10-01
Model-based approach is recognized as a tool to make drug development more productive and to better support regulatory and therapeutic decisions. The objective of this study was to develop a novel model-based methodology based on the response surface analysis and a nonlinear optimizer algorithm to maximize the clinical performances of drug treatments. The treatment response was described using a drug-disease model accounting for multiple components such as the dosage regimen, the pharmacokinetic characteristics of a drug (including the mechanism and the rate of drug delivery), and the exposure-response relationship. Then, the clinical benefit of a treatment was defined as a function of the diseases and the clinical endpoints and was estimated as a function of the target pharmacodynamic endpoints used to evaluate the treatment effect. A case study is presented to illustrate how the treatment performances of paliperidone extended release (ER) and paliperidone long-acting injectable (LAI) can be improved. A convolution-based approach was used to characterize the pharmacokinetics of ER and LAI paliperidone. The drug delivery properties and the dosage regimen maximizing the clinical benefit (defined as the target level of D2 receptor occupancy) were estimated using a nonlinear optimizer. The results of the analysis indicated that a substantial improvement in clinical benefit (from 15% to 27% for the optimization of the in vivo release and from ∼30% to ∼70% for the optimization of dosage regimen) was obtained when optimal strategies were deployed either for optimizing the in vivo drug delivery properties of ER formulations or for optimizing the dosage regimen of LAI formulations. © 2016, The American College of Clinical Pharmacology.
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...
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.
parametric nonlinear quasivariational inequalities
Directory of Open Access Journals (Sweden)
Zeqing Liu
2005-01-01
uniqueness results and sensitivity analysis of solutions are also established for the system of generalized nonlinear parametric quasivariational inequalities and some convergence results of iterative sequence generated by the algorithm with errors are proved.
Rushton, Simon
2016-01-01
In their hypothesis published in IJHPM, Lisa Forman and colleagues examined the prominence of the right to health and sexual and reproductive health rights (as well as related language) in four of the key reports that fed into the process of negotiating the Sustainable Development Goals (SDGs). Now that the SDGs have been formally adopted, this comment builds on some of the insights of Forman and colleagues to examine the extent to which those rights have been incorporated in SDGs 3 and 5. I argue that sexual and reproductive health rights are relatively well-covered within the SDGs. In terms of the right to health, however, the picture is much less clear. Some of the elements that make up that right are present and correct, but the SDGs have delivered no coherent vision of how a ‘right to health’ might actually be realized. An important task facing global health and human rights advocates is to continue pushing human rights framings so that progress is made both on meeting the SDGs and on realizing the right to health. PMID:27239886
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.
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)
Computing weakly reversible realizations of chemical reaction networks
Szederkenyi, Gabor; Hangos, Katalin M.; Tuza, Zsolt
2011-01-01
An algorithm is given in this paper for the computation of dynamically equivalent weakly reversible realizations with the maximal number of reactions, for chemical reaction networks (CRNs) with mass action kinetics.
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
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 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)
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.
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.
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
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.
Realizations of the canonical representation
Indian Academy of Sciences (India)
A characterisation of the maximal abelian subalgebras of the bounded operators on Hilbert space that are normalised by the canonical representation of the Heisenberg group is given. This is used to classify the perfect realizations of the canonical representation.
String theory realizations of the nilpotent goldstino
Energy Technology Data Exchange (ETDEWEB)
Kallosh, Renata [Department of Physics and SITP, Stanford University, Stanford, CA 94305 (United States); Quevedo, Fernando [ICTP, Strada Costiera 11, 34151 Trieste (Italy); DAMTP, CMS, University of Cambridge, Wilberforce Road, Cambridge, CB3 0WA (United Kingdom); Uranga, Angel M. [Instituto de Física Teórica UAM-CSIC, c/ Nicolás Cabrera 13-15, 28049 Madrid (Spain)
2015-12-09
We describe in detail how the spectrum of a single anti-D3-brane in four-dimensional orientifolded IIB string models reproduces precisely the field content of a nilpotent chiral superfield with the only physical component corresponding to the fermionic goldstino. In particular we explicitly consider a single anti-D3-brane on top of an O3-plane in warped throats, induced by (2,1) fluxes. More general systems including several anti-branes and other orientifold planes are also discussed. This provides further evidence to the claim that non-linearly realized supersymmetry due to the presence of antibranes in string theory can be described by supersymmetric theories including nilpotent superfields. Implications to the KKLT and related scenarios of de Sitter moduli stabilization, to cosmology and to the structure of soft SUSY-breaking terms are briefly discussed.
String theory realizations of the nilpotent goldstino
Kallosh, Renata; Quevedo, Fernando; Uranga, Angel M.
2015-12-01
We describe in detail how the spectrum of a single anti-D3-brane in four-dimensional orientifolded IIB string models reproduces precisely the field content of a nilpotent chiral superfield with the only physical component corresponding to the fermionic goldstino. In particular we explicitly consider a single anti-D3-brane on top of an O3-plane in warped throats, induced by (2, 1) fluxes. More general systems including several anti-branes and other orientifold planes are also discussed. This provides further evidence to the claim that non-linearly realized supersymmetry due to the presence of antibranes in string theory can be described by supersymmetric theories including nilpotent superfields. Implications to the KKLT and related scenarios of de Sitter moduli stabilization, to cosmology and to the structure of soft SUSY-breaking terms are briefly discussed.
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.
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...... ability to produce efficient search algorithms. Such algorithms may be completely problem-independent (which is the case for the so-called 'meta-heuristics' or 'blind-search' algorithms), or they may be designed with the structure of the concrete problem in mind. We show that pure meta...
Bauer, Rebecca; Mentré, France; Kaddouri, Halima; Le Bras, Jacques; Le Nagard, Hervé
2014-12-01
Malaria is one of the world׳s most widespread parasitic diseases. The parasitic protozoans of the genus Plasmodium have developed resistance to several antimalarial drugs. Some patients are therefore infected by two or more strains with different levels of antimalarial drug sensitivity. We previously developed a model to estimate the drug concentration (IC50) that inhibits 50% of the growth of the parasite isolated from a patient infected with one strain. We propose here a new Two-Slopes model for patients infected by two strains. This model involves four parameters: the proportion of each strain and their IC50, and the sigmoidicity parameter. To estimate the parameters of this model, we have developed a new algorithm called PGBO (Population Genetics-Based Optimizer). It is based on the Metropolis-Hasting algorithm and is implemented in the statistical software R. We performed a simulation study and defined three evaluation criteria to evaluate its properties and compare it with three other algorithms (Gauss-Newton, Levenberg-Marquardt, and a simulated annealing). We also evaluated it using in vitro data and three ex vivo datasets from the French Malaria Reference Center. Our evaluation criteria in the simulation show that PGBO gives good estimates of the parameters even if the concentration design is poor. Moreover, our algorithm is less sensitive than Gauss-Newton algorithms to initial values. Although parameter estimation is good, interpretation of the results can be difficult if the proportion of the second strain is close to 0 or 1. For these reasons, this approach cannot yet be implemented routinely. Copyright © 2014 Elsevier Ltd. All rights reserved.
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
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......-link spectral inversion and in-line non-linear compensation methods are also analyzed. This gives us enhanced system performance and DBP step-size of 400 km in WDM 224 Gbit/s DP-16QAM system, significantly reducing the complexity of digital backward propagation....
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....
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.
Social network analysis realization and exploitation
Davenport, Jack H.; Nolan, James J.
2015-05-01
Intelligence analysts demand rapid information fusion capabilities to develop and maintain accurate situational awareness and understanding of dynamic enemy threats in asymmetric military operations. The ability to extract meaning in relationships between people, objects, and locations from a variety of unstructured text datasets is critical to proactive decision making. Additionally, the ability to automatically cluster text documents about entities and discover connections between those documents allows the analyst to navigate an extremely large collection of documents. Analysts also demand a temporal understanding of the extracted relationships between entities and connections between documents. We describe approaches to automatically realize the social networks via concept extraction, relationship extraction, and document connection algorithms; we also describe approaches to exploit the network by visualizing the results to the analyst such that changes over time are evident.
Bongers, Malte N; Bier, Georg; Marcus, Roy; Ditt, Hendrik; Kloth, Christopher; Schabel, Christoph; Nikolaou, Konstantin; Horger, Marius
2016-10-01
Aim of this ex vivo phantom study was to evaluate the contrast enhancement applying a new frequency split nonlinear blending algorithm (best contrast [BC]) and to compare it with standard 120-kV single-energy computed tomography (SECT) images, as well as with low-kiloelectron volt monoenergetic extrapolations (Mono+40-100keV) from dual-energy CT (DECT) and with low-kilovolt (70-100 kV) SECT acquisitions. A dilution series of iodinated contrast material-filled syringes was centered in an attenuation phantom and was scanned with SECT70-120kV and DECT80-100/Sn150. Monoenergetic images (40-100 keV) were reconstructed, and a new manual frequency split nonlinear blending algorithm (BC) was applied to SECT70kV and SECT120kV images. Manual BC settings were set to simulate a reading situation with fixed overall best values (FVBC120kV) as well as to achieve best possible values for each syringe (BVBC120kV) for maximum contrast enhancement. Contrast-to-noise ratios (CNRs) were used as an objective region of interest-based image analysis parameter. Two radiologists evaluated the detectability of hyperdense and hypodense syringes (Likert). Results were compared between SECT70-100kV, Mono+40-100keV, and DECT80-100/Sn150kV, as well as FVBC120kV, BVBC120kV, and BC70kV. Highest CNR without BC was detected at SECT70kV (5.04 ± 0.12) and Mono+40keV (4.40 ± 0.11). FVBC and BVBC images allow a significant increase of CNR compared with SECT120kV (CNRBVBC, 5.21 ± 0.15; CNRFVBC, 5.12 ± 0.16; CNRSECT120kV, 2.5 ± 0.08; all P ≤ 0.01). There was no significant difference in CNR between BVBC and FVBC. Averaged CNR in BVBC and FVBC was significantly higher compared with Mono+40-100keV (all P ≤ 0.01). Compared with SECT70kV, averaged CNR in BVBC and FVBC show no significant differences. BVBC70kV (7.67 ± 0.17) significantly increases CNR in SECT70kV up to 213%.Subjective image analysis showed an interobserver agreement of 0.63 to 0.83 (κ), confirming the superiority of BC in detecting
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.
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...
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.
Realizations of the canonical representation
Indian Academy of Sciences (India)
Note that the symplectic group Sp(2n, R)acts onR2n preservinge. ... Observe that a maximal inductive algebra is weakly closed. DEFINITION 2.3 ... Let E be a perfect realization over (B, μ). Let B be a standard G-space. Suppose f : B → B is a Borel G-map. Set μ = f∗μ. Then μ is G-quasi-invariant. Sup- pose μ is σ-finite.
Realizations of the canonical representation
Indian Academy of Sciences (India)
Sup- pose μ is σ-finite. We get a G-quasi-equivariant disintegration λb of μ over μ . Set ... For the proof of existence of a disintegration, see Theorem 7.1 of [3]. DEFINITION 2.9. A perfect realization E is minimal if ... certain family of Hilbert spaces (in fact, a line bundle) over R2n/M. It is not hard to see that E is a minimal perfect ...
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.
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
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
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
Dimensional Reduction of Nonlinear Gauge Theories
Ikeda, Noriaki; Izawa, K.-I.
2004-09-01
We extend 2D nonlinear gauge theory from the Poisson sigma model based on Lie algebroid to a model with additional two-form gauge fields. Dimensional reduction of 3D nonlinear gauge theory yields an example of such a model, which provides a realization of Courant algebroid by 2D nonlinear gauge theory. We see that the reduction of the base structure generically results in a modification of the target (algebroid) structure.
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
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.
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.
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
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.
National Research Council Canada - National Science Library
Rassias, Themistocles M
1987-01-01
... known that nonlinear partial differential equations can not be treated in the same systematic way as linear ones and this volume provides, among other things, proofs of existence and uniqueness theorems for nonlinear differential equations of a global nature. However, the basic techniques which have proven to be efficient in dealing with li...
Good quality virtual realization of unit disk graphs
Directory of Open Access Journals (Sweden)
Sriram Pemmaraju
2011-08-01
Full Text Available We consider the problem of finding a realization of an n-vertex unit disk graph (UDG expressed in general form, say, as an adjacency matrix. The problem is to construct an embedding of the graph in low-dimensional Euclidean space so that the ratio of the length of the longest edge under the embedding to the length of the shortest non-edge under the embedding is as small as possible; the measure is known as the quality of the realization. Thus, an optimum quality realization has quality between 1/2 and 1. Kuhn et al. gave aO(log3.5 n (loglog n1/2} quality realization that requires solving a linear program with exponentially many constraints by using the ellipsoid algorithm. In this article, we give a combinatorial algorithm that achieves an O(log3 n quality realization of an n-vertex UDG expressed in general form. Thus, not only is our algorithm an improvement, it also bypasses the standard and costly technique of solving a linear program with exponentially many “spreading constraints.” As a side effect of our construction, we get the first constant-factor approximation to the minimum clique partition problem for UDGs expressed in general form. Such a clique partition also represents our key technical contribution. If the embedding is allowed to reside in higher dimensional space, we obtain improved results: a quality-2 embedding in constant dimensional Euclidean space.
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...
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.
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
True reference nanosensor realized with silicon nanowires.
Tarasov, A; Wipf, M; Bedner, K; Kurz, J; Fu, W; Guzenko, V A; Knopfmacher, O; Stoop, R L; Calame, M; Schönenberger, C
2012-06-26
Conventional gate oxide layers (e.g., SiO(2), Al(2)O(3), or HfO(2)) in silicon field-effect transistors (FETs) provide highly active surfaces, which can be exploited for electronic pH sensing. Recently, great progress has been achieved in pH sensing using compact integrateable nanowire FETs. However, it has turned out to be much harder to realize a true reference electrode, which--while sensing the electrostatic potential--does not respond to the proton concentration. In this work, we demonstrate a highly effective reference sensor, a so-called reference FET, whose proton sensitivity is suppressed by as much as 2 orders of magnitude. To do so, the Al(2)O(3) surface of a nanowire FET was passivated with a self-assembled monolayer of silanes with a long alkyl chain. We have found that a full passivation can be achieved only after an extended period of self-assembling lasting several days at 80 °C. We use this slow process to measure the number of active proton binding sites as a function of time by a quantitative comparison of the measured nonlinear pH-sensitivities to a theoretical model (site-binding model). Furthermore, we have found that a partially passivated surface can sense small changes in the number of active binding sites reaching a detection limit of δN(s) ≈ 170 μm(-2) Hz(-1/2) at 10 Hz and pH 3.
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
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
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.
2016-07-01
architectures , practical nonlinearities, nonlinear dynamics 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT: SAR 8. NUMBER OF PAGES...performers from Mesodynamic Architectures (MESO) and uPNT all to include devices in these runs. This cost-sharing was planned, and is necessary for...contributions to the performance of MEMS gyroscopes. In particular, we have demonstrated for the first time that Parametric Amplification can improve the
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....
Nonlinear Statistical Signal Processing: A Particle Filtering Approach
Energy Technology Data Exchange (ETDEWEB)
Candy, J
2007-09-19
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.
DEFF Research Database (Denmark)
Mahnke, Martina; Uprichard, Emma
2014-01-01
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...
Numerical treatment of a nonlinear hyperbolic equation
Directory of Open Access Journals (Sweden)
Nabiha Brik
2017-03-01
Full Text Available In this work we consider a nonlinear elliptic partial differential equation, which is derived from an application of a nonlinear Schrödinger equation. Using a variational approach on this problem leads to an optimization problem with a nonlinear constraint. A numerical solution based on finite-element method is used. We propose a new iterative algorithm to relax this problem to a quadratic version.
Nonlinear Filtering in High Dimension
2014-06-02
work of Handschin and Mayne in 1969 [30]. The idea behind the SIS algorithm is to apply the self-normalized im- portance sampling paradigm introduced...Springer, Berlin, 2003. [30] J. E. Handschin and D. Q. Mayne . Monte Carlo techniques to estimate the conditional expectation in multi-stage non-linear
Nonlinear adaptive models for speech enhancement algorithms
Czech Academy of Sciences Publication Activity Database
Koula, Ivan; Zezula, R.
2007-01-01
Roč. 42, č. 1 (2007), s. 138-145 ISSN 1738-6438 R&D Projects: GA ČR(CZ) GA102/06/1233; GA AV ČR(CZ) 1ET301710509 Institutional research plan: CEZ:AV0Z20670512 Keywords : noise measurement * speech enhancement * neural nets Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering
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 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.
DEFF Research Database (Denmark)
Schløer, Signe; Bredmose, Henrik; Bingham, Harry B.
2016-01-01
and nonlinear irregular wave realizations are calculated using the fully nonlinear potential flow wave model OceanWave3D [1]. The linear and nonlinear wave realizations are compared using both a static analysis on a fixed monopile and dynamic calculations with the aeroelastic code Flex5 [2]. The conclusion from...
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.
Control methods for localization of nonlinear waves.
Porubov, Alexey; Andrievsky, Boris
2017-03-06
A general form of a distributed feedback control algorithm based on the speed-gradient method is developed. The goal of the control is to achieve nonlinear wave localization. It is shown by example of the sine-Gordon equation that the generation and further stable propagation of a localized wave solution of a single nonlinear partial differential equation may be obtained independently of the initial conditions. The developed algorithm is extended to coupled nonlinear partial differential equations to obtain consistent localized wave solutions at rather arbitrary initial conditions.This article is part of the themed issue 'Horizons of cybernetical physics'. © 2017 The Author(s).
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.
Electronic circuit realization of the logistic map
Indian Academy of Sciences (India)
Abstract. An electronic circuit realization of the logistic difference equation is presented using analog electronics. The behaviour of the realized system is evalu- ated against computer simulations of the same. The circuit is found to exhibit the entire range of dynamics of the logistic equation: fixed points, periodicity, period.
Electronic circuit realization of the logistic map
Indian Academy of Sciences (India)
An electronic circuit realization of the logistic difference equation is presented using analog electronics. The behaviour of the realized system is evaluated against ... Author Affiliations. Madhekar Suneel1. PGAD (DRDO, Ministry of Defence, Government of India), DRDL Complex, Kanchanbagh, Hyderabad 500 058, India ...
Temperamental Prerequisites of Personality Self-Realization
Directory of Open Access Journals (Sweden)
S I Kudinov
2015-12-01
Full Text Available The article discusses the problem of individual and typological conditionality of personality self-realization. The results of an empirical research are submitted, the typological features of temperament properties with the variables of self-realization in teachers are compared.
A Robustly Stabilizing Model Predictive Control Algorithm
Ackmece, A. Behcet; Carson, John M., III
2007-01-01
A model predictive control (MPC) algorithm that differs from prior MPC algorithms has been developed for controlling an uncertain nonlinear system. This algorithm guarantees the resolvability of an associated finite-horizon optimal-control problem in a receding-horizon implementation.
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.
Kurtosis Approach to Solution of a Nonlinear ICA Problem
Duong, Vu; Stubberud, Allen
2009-01-01
An algorithm for solving a particular nonlinear independent-component-analysis (ICA) problem, that differs from prior algorithms for solving the same problem, has been devised. The problem in question of a type known in the art as a post nonlinear mixing problem is a useful approximation of the problem posed by the mixing and subsequent nonlinear distortion of sensory signals that occur in diverse scientific and engineering instrumentation systems.
Fast nonlinear susceptibility inversion with variational regularization.
Milovic, Carlos; Bilgic, Berkin; Zhao, Bo; Acosta-Cabronero, Julio; Tejos, Cristian
2018-01-10
Quantitative susceptibility mapping can be performed through the minimization of a function consisting of data fidelity and regularization terms. For data consistency, a Gaussian-phase noise distribution is often assumed, which breaks down when the signal-to-noise ratio is low. A previously proposed alternative is to use a nonlinear data fidelity term, which reduces streaking artifacts, mitigates noise amplification, and results in more accurate susceptibility estimates. We hereby present a novel algorithm that solves the nonlinear functional while achieving computation speeds comparable to those for a linear formulation. We developed a nonlinear quantitative susceptibility mapping algorithm (fast nonlinear susceptibility inversion) based on the variable splitting and alternating direction method of multipliers, in which the problem is split into simpler subproblems with closed-form solutions and a decoupled nonlinear inversion hereby solved with a Newton-Raphson iterative procedure. Fast nonlinear susceptibility inversion performance was assessed using numerical phantom and in vivo experiments, and was compared against the nonlinear morphology-enabled dipole inversion method. Fast nonlinear susceptibility inversion achieves similar accuracy to nonlinear morphology-enabled dipole inversion but with significantly improved computational efficiency. The proposed method enables accurate reconstructions in a fraction of the time required by state-of-the-art quantitative susceptibility mapping methods. Magn Reson Med, 2018. © 2018 International Society for Magnetic Resonance in Medicine. © 2018 International Society for Magnetic Resonance in Medicine.
Nonlinear Multigrid for Reservoir Simulation
DEFF Research Database (Denmark)
Christensen, Max la Cour; Eskildsen, Klaus Langgren; Engsig-Karup, Allan Peter
2016-01-01
modeled after local linearization, leading to a nonlinear multigrid method in the form of the full-approximation scheme (FAS). It is demonstrated through numerical experiments that, without loss of robustness, the FAS method can outperform the conventional techniques in terms of algorithmic and numerical...... efficiency for a black-oil model. Furthermore, the use of the FAS method enables a significant reduction in memory usage compared with conventional techniques, which suggests new possibilities for improved large-scale reservoir simulation and numerical efficiency. Last, nonlinear multilevel preconditioning...
Zhang, Yajun; Chai, Tianyou; Wang, Hong; Wang, Dianhui; Chen, Xinkai
2017-04-24
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.
Realized Volatility in Seoul Foreign Exchange Market
Directory of Open Access Journals (Sweden)
Chae-Shick Chung
2003-12-01
Full Text Available This paper constructs model-free estimates of daily KRW/USD's volatility, termed realized volatility, using two minutes frequency and compares the volatility with two major currencies of JPY/USD and EURO/USD. We confirm that the empirical properties of KRW/USD's realized volatility are very similar to early findings major currencies as argued by Andersen et. al(2003. Noteworthy results include the distribution of realized volatility are leptokurtic, but the distributions of logarithmic standard deviations are nearly Gaussian. We also find that the correlation between KRW/USD and major currency, JPY/USD and EURO/USD, are positive and increase with volatility.
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
International Nuclear Information System (INIS)
Baniassadi, Majid; Garmestani, Hamid; Li, Dongsheng; Ahzi, Said; Khaleel, Mohammad A.; Sun, Xin
2011-01-01
A Monte Carlo methodology is developed as a means for three-dimensional (3D) reconstruction of the microstructure of a three-phase anode used in solid oxide fuel cells, based on two-point statistical functions. The salient feature of the presented reconstruction methodology is the ability to realize the 3D microstructure from its 2D SEM image for a three-phase medium extendable to n-phase media. In the realization procedure, different phases of the heterogeneous medium are represented by different cells which are allowed to grow. The growth of cells, however, are controlled via several optimization parameters related to rotation, shrinkage, translation, distribution and growth rates of the cells. Indeed, the proposed realization algorithm can be categorized as a member of dynamic programming methods and is designed so comprehensive that can realize any desired microstructure. To be more specific, at first the initial 2D image is successfully reconstructed and then the final optimization parameters are used as the initial values for the initiation of the 3D reconstruction algorithm. This paper presents a novel hybrid stochastic methodology based on the colony and kinetic algorithm for the simulation of the virtual microstructure. The simulation procedure involves repeated realizations where each realization in turn consists of nucleation and growth of cells. For each of the subsequent realizations, the controlling parameters get updated by minimization of an objective function at the end of the preceding realization. Here, the objective function is defined based on the two-point correlation functions from the simulated and real microstructures. The kinetic growth algorithm is established on the cellular automata approach which facilitates the simulation procedure. Comparison of the two-point correlation functions from different sections of the final 3D reconstructed microstructure with the initial real microstructure shows a satisfactory agreement which confirms the
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 · ...
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.
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 Projects: 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 problems * partially separable problems * 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
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 ...
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
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)
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.
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 is b...... is based on a state space transformation, with which the unknown signals are decoupled. For the illustration purposes the method is applied on the model of a small satellite....
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 ...
Dynamic Consensus Algorithm based Distributed Voltage Harmonic Compensation in Islanded Microgrids
DEFF Research Database (Denmark)
Meng, Lexuan; Tang, Fen; Firoozabadi, Mehdi Savaghebi
2015-01-01
control to realize voltage harmonic compensation and accurate current sharing in multi-bus islanded microgrids. Low order harmonic components are considered as examples in this paper. Harmonic current sharing is also realized among distributed generators by applying the proposed methods. Plug......In islanded microgrids, the existence of nonlinear electric loads may cause voltage distortion and affect the performance of power quality sensitive equipment. Thanks to the prevalent utilization of interfacing power electronic devices and information/communication technologies, distributed...... generators can be employed as compensators to enhance the power quality on consumer side. However, conventional centralized control is facing obstacles because of the distributed fashion of generation and consumption. Accordingly, this paper proposes a consensus algorithm based distributed hierarchical...
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
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.
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
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.
An efficient algorithm for function optimization: modified stem cells algorithm
Taherdangkoo, Mohammad; Paziresh, Mahsa; Yazdi, Mehran; Bagheri, Mohammad
2013-03-01
In this paper, we propose an optimization algorithm based on the intelligent behavior of stem cell swarms in reproduction and self-organization. Optimization algorithms, such as the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Ant Colony Optimization (ACO) algorithm and Artificial Bee Colony (ABC) algorithm, can give solutions to linear and non-linear problems near to the optimum for many applications; however, in some case, they can suffer from becoming trapped in local optima. The Stem Cells Algorithm (SCA) is an optimization algorithm inspired by the natural behavior of stem cells in evolving themselves into new and improved cells. The SCA avoids the local optima problem successfully. In this paper, we have made small changes in the implementation of this algorithm to obtain improved performance over previous versions. Using a series of benchmark functions, we assess the performance of the proposed algorithm and compare it with that of the other aforementioned optimization algorithms. The obtained results prove the superiority of the Modified Stem Cells Algorithm (MSCA).
Identification of Hammerstein models with cubic spline nonlinearities.
Dempsey, Erika J; Westwick, David T
2004-02-01
This paper considers the use of cubic splines, instead of polynomials, to represent the static nonlinearities in block structured models. It introduces a system identification algorithm for the Hammerstein structure, a static nonlinearity followed by a linear filter, where cubic splines represent the static nonlinearity and the linear dynamics are modeled using a finite impulse response filter. The algorithm uses a separable least squares Levenberg-Marquardt optimization to identify Hammerstein cascades whose nonlinearities are modeled by either cubic splines or polynomials. These algorithms are compared in simulation, where the effects of variations in the input spectrum and distribution, and those of the measurement noise are examined. The two algorithms are used to fit Hammerstein models to stretch reflex electromyogram (EMG) data recorded from a spinal cord injured patient. The model with the cubic spline nonlinearity provides more accurate predictions of the reflex EMG than the polynomial based model, even in novel data.
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...
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.
A hybrid strategy to control uncertain nonlinear chaotic system
International Nuclear Information System (INIS)
Sui Yongbo; He Yigang; Yu Wenxin; Li Yan
2017-01-01
In this paper, a new method, based on firefly algorithm (FA) and extreme learning machine (ELM), is proposed to control chaos in nonlinear system. ELM is an efficient predicted and classified tool, and can match and fit nonlinear systems efficiently. Hence, mathematical model of uncertain nonlinear system is obtained indirectly. For higher fitting accuracy, a novel swarm intelligence algorithm FA is drawn in our proposed way. The main advantage is that our proposed method can remove the limitation that mathematical model must be known clearly and can be applied to unknown nonlinear chaotic system. (paper)
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.
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.
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).
A direct method for nonlinear ill-posed problems
Lakhal, A.
2018-02-01
We propose a direct method for solving nonlinear ill-posed problems in Banach-spaces. The method is based on a stable inversion formula we explicitly compute by applying techniques for analytic functions. Furthermore, we investigate the convergence and stability of the method and prove that the derived noniterative algorithm is a regularization. The inversion formula provides a systematic sensitivity analysis. The approach is applicable to a wide range of nonlinear ill-posed problems. We test the algorithm on a nonlinear problem of travel-time inversion in seismic tomography. Numerical results illustrate the robustness and efficiency of the algorithm.
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
Banach spaces that realize minimal fillings
Energy Technology Data Exchange (ETDEWEB)
Bednov, B. B.; Borodin, P. A., E-mail: noriiii@inbox.ru, E-mail: pborodin@inbox.ru [Faculty of Mechanics and Mathematics, Moscow State University (Russian Federation)
2014-04-30
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{sub 1}. The spaces L{sub 1} are characterized in terms of Steiner points (medians). Bibliography: 25 titles. (paper)
TECHNOLOGY EDUCATION: THE MEANS TO THE REALIZATION ...
African Journals Online (AJOL)
4. a land of bright and full opportunities, and. 5. a free and democratic society. The realization of the vision and the missions depend to a large extent on technology education. The minimum GNI per capital of the high income economies which Nigeria intends to join is at least USD 10,680 in the current rating. (Adebayo ...
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...
IMPEDIMENTS AGAINST THE REALIZATION OF FOOD SECURITY ...
African Journals Online (AJOL)
Is corruption of public officials responsible for food security policy problems in the state? •. Is the high rate ... food security fails. Uzoh, A. B. – Impediments Against The Realization of Food Security Policy in Imo State, Nigeria. .... power between men and women and between leaders are evident in agricultural credit scheme.
New Realization of Periodic Cycled Separation
DEFF Research Database (Denmark)
Toftegard, Bjarne; Clausen, Charlotte H.; Jørgensen, Sten B.
2016-01-01
A new realization of periodic cycled gas/liquid separation is presented. Separation factors and column efficiencies are compared for a column stripping ammonia from water with air, using three different sets of internals: conventional sieve trays, Sulzer BX gauze packings, and periodically cycled...... for columns with sieve trays....
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 ...
Measuring volatility with the realized range
M.P.E. Martens (Martin); D.J.C. van Dijk (Dick)
2006-01-01
textabstractRealized variance, being the summation of squared intra-day returns, has quickly gained popularity as a measure of daily volatility. Following Parkinson (1980) we replace each squared intra-day return by the high-low range for that period to create a novel and more efficient estimator
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)
Linear and Nonlinear Oblivious Data Hiding
Directory of Open Access Journals (Sweden)
Akansu Ali N
2004-01-01
Full Text Available The majority of the existing data hiding schemes are based on the direct-sequence (DS modulation where a low-power random sequence is embedded into the original cover signal to represent hidden information. In this paper, we investigate linear and nonlinear modulation approaches in digital data hiding. One typical DS modulation algorithm is explored and its optimal oblivious detector is derived. The results expose its poor cover noise suppression as the hiding signature signal always has much lower energy than the cover signal. A simple nonlinear algorithm, called set partitioning, is proposed and its performance is analyzed. Analysis and simulation studies further demonstrate improvements over the existing schemes.
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
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.
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)
Realization of Multi-Delay Filter Using Fermat Number Transforms
Alaeddine, Hamzé Haidar; Baghious, El Houssaïn; Madre, Guillaume; Burel, Gilles
This paper is about an efficient implementation of adaptive filtering for echo cancelers. The first objective of this paper is to propose a simplified method of the flexible block Multi-Delay Filter (MDF) algorithm in the time-domain. Then, we will derive a new method for the step-size adaptation coefficient. The second objective is about the realization of a Block Proportionate Normalized Least Mean Squares (BPNLMS++) with the simplified MDF (SMDF) implementation. Using the new step-size method and the smaller block dimension proposed by SMDF, we achieve a faster convergence of the adaptive process with a limited computational cost. Then, an efficient implementation of the new procedure (SMDF-BPNLMS++) block filtering is proposed using Fermat Number Transform, which can significantly reduce the computation complexity of filter implantation on Digital Signal Processor.
[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
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
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.
Nonlinear Frequency Compression
Scollie, Susan; Glista, Danielle; Seelisch, Andreas
2013-01-01
Frequency lowering technologies offer an alternative amplification solution for severe to profound high frequency hearing losses. While frequency lowering technologies may improve audibility of high frequency sounds, the very nature of this processing can affect the perceived sound quality. This article reports the results from two studies that investigated the impact of a nonlinear frequency compression (NFC) algorithm on perceived sound quality. In the first study, the cutoff frequency and compression ratio parameters of the NFC algorithm were varied, and their effect on the speech quality was measured subjectively with 12 normal hearing adults, 12 normal hearing children, 13 hearing impaired adults, and 9 hearing impaired children. In the second study, 12 normal hearing and 8 hearing impaired adult listeners rated the quality of speech in quiet, speech in noise, and music after processing with a different set of NFC parameters. Results showed that the cutoff frequency parameter had more impact on sound quality ratings than the compression ratio, and that the hearing impaired adults were more tolerant to increased frequency compression than normal hearing adults. No statistically significant differences were found in the sound quality ratings of speech-in-noise and music stimuli processed through various NFC settings by hearing impaired listeners. These findings suggest that there may be an acceptable range of NFC settings for hearing impaired individuals where sound quality is not adversely affected. These results may assist an Audiologist in clinical NFC hearing aid fittings for achieving a balance between high frequency audibility and sound quality. PMID:23539261
The nursing discipline and self-realization.
Kristoffersen, Margareth; Friberg, Febe
2015-09-01
It is obvious from literature within the nursing discipline that nursing is related to moral or moral-philosophical related ideas which are other-oriented. The socio-cultural process of change in modern society implies that more self-oriented ideas have been found to be significant. The overall aim of this article is to highlight self-oriented moral or moral-philosophical related ideas as an important part of the nursing discipline. This is achieved by (a) exploring self-realization as a significant self-oriented moral or moral-philosophical related idea based on a philosophical anthropological perspective, (b) demonstrating how moral or moral-philosophical related ideas are expressed by nurses, (c) discussing the relevance of self-realization for the nursing discipline, and (d) pointing out possible consequences for the future development of the discipline of nursing. This theoretical study draws empirical examples from interviews. Data consisted of interviews with 13 nurses with varying work experience within the primary and secondary somatic and psychiatric health service, from inside as well as outside institutions. The empirical study was approved by the Norwegian Social Science Data Services. Information was given and consent was obtained from the study participants. Findings are presented in two themes: (a) other-oriented ideas and (b) self-oriented ideas. More concretely, the findings show that nurses hope to make life as good as possible for the patient and they have a wish to improve themselves as human beings, to become better persons. The relevance of self-realization for the nursing discipline is discussed along two lines, first, by connecting nurses' self-understanding to a horizon of identity and second, by considering what self-realization could offer. It is of ultimate concern for the nursing discipline to highlight self-realization connected to the positive view of freedom understood as an exercise-concept. Further identifying and articulating the
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
Zhang, Kejian; Wang, Huan; Yuan, Bo; Wang, Liqiang
2017-01-01
This paper studies the realization of image processing algorithm of multispectral endoscope. The research contents include: local brightness enhancement and adaptive contrast enhancement. Firstly, this paper transforms the image from the RGB space to the HSV space, and then carries on the image enhancement processing to the V space, finally transforms to the RGB space. Local brightness enhancement algorithm divides V space image into smaller windows, and then calculates the nonlinear transfer function of each window, which enhances the pixels in the window, and finally the contrast of brightness enhanced image is restored. The adaptive contrast enhancement adopts the unsharp mask technique based on the guided filter. First of all, this paper uses guided filter to the RGB channel of the original image and gets the unsharp mask of each channel, then plus a scaled image which is the result of the original image subtracts the unsharp mask. So the enhancement of the image is achieved. This paper uses subjective evaluation criteria and enhance factor α to evaluate the effect of enhancement. And this paper compares the enhancement effect of the proposed image enhancement algorithm and the traditional algorithm. The results show that the α of histogram equalization is smallest and AINDANE method is better than histogram equalization. The proposed method has the best α. The subjective evaluation also shows that the effect of HE is not satisfactory and the proposed method enhances the detail information tremendously. The subjective and objective criteria shows that the proposed method produces better enhancement effect.
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.)
Acoustic wave science realized by metamaterials.
Lee, Dongwoo; Nguyen, Duc Minh; Rho, Junsuk
2017-01-01
Artificially structured materials with unit cells at sub-wavelength scale, known as metamaterials, have been widely used to precisely control and manipulate waves thanks to their unconventional properties which cannot be found in nature. In fact, the field of acoustic metamaterials has been much developed over the past 15 years and still keeps developing. Here, we present a topical review of metamaterials in acoustic wave science. Particular attention is given to fundamental principles of acoustic metamaterials for realizing the extraordinary acoustic properties such as negative, near-zero and approaching-infinity parameters. Realization of acoustic cloaking phenomenon which is invisible from incident sound waves is also introduced by various approaches. Finally, acoustic lenses are discussed not only for sub-diffraction imaging but also for applications based on gradient index (GRIN) lens.
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.
Realizing Mobile Web Services for Dynamic Applications
Zaplata, Sonja; Dreiling, Viktor; Lamersdorf, Winfried
Use of web services also on mobile devices becomes increasingly relevant. However, realizing such mobile web services based on the standard protocol stack is often inappropriate for resource-restricted mobile devices in dynamic networks. On the other hand, using specialized alternative protocols restricts compatibility with traditional service applications. Thus, existing approaches often do not allow to integrate heterogeneous service instances dynamically, as it is, e.g., required for executing mobile service-based business processes.
Realization of Thermal Inertia in Frequency Domain
Hong, Boe-Shong; Chou, Chia-Yu
2014-01-01
To realize the lagging behavior in heat conduction observed in these two decades, this paper firstly theoretically excludes the possibility that the underlying thermal inertia is a result of the time delay in heat diffusion. Instead, we verify in experiments the electro-thermal analogy, wherein the thermal inertial is parameterized by thermal inductance that formulates hyperbolic heat-conduction. The thermal hyperbolicity exhibits a special frequency response in Bode plot, wherein the amplitu...
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.
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
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
Design and realization of a quantum Controlled NOT gate using optical implementation
Biswas, K. K.; Sajeed, Shihan
2012-06-01
In this work an optical implementation technique of a Controlled-NOT (CNOT) gate has been designed, realized and simulated. The polarization state of a photon is used as qubit. The interaction required between two qubits for realizing the CNOT operation was achieved by converting the qubits from polarization encoding to spatial encoding with the help of a Polarizing Beam Splitter (PBS) and half wave plate (HWP) oriented at 45 Degree.After the nonlinear interference was achieved the spatially encoded qubits were converted back into polarization encoding and thus the CNOT operation was realized. The whole design methodology was simulated using the simulation software OptiSystem and the results were verified using the built-in instruments polarization analyzer, polarization meter, optical spectrum analyzer, power meters etc.
Directory of Open Access Journals (Sweden)
Jie-Sheng Wang
2015-02-01
Full Text Available In order to realize the fault diagnosis of the polyvinyl chloride (PVC polymerization kettle reactor, a rough set (RS–probabilistic neural networks (PNN fault diagnosis strategy is proposed. Firstly, through analysing the technique of the PVC polymerization reactor, the mapping between the polymerization process data and the fault modes is established. Then, the rough set theory is used to tackle the input vector of PNN so as to reduce the network dimensionality and improve the training speed of PNN. Shuffled frog leaping algorithm (SFLA is adopted to optimize the smoothing factor of PNN. The fault pattern classification of polymerization kettle equipment is to realize the nonlinear mapping from symptom set to fault set according to the given symptom set. Finally, the fault diagnosis simulation experiments are conducted by combining with the industrial on-site historical datum of polymerization kettle, and the results show that the RS–PNN fault diagnosis strategy is effective.
Investigation on Evolutionary Computation Techniques of a Nonlinear System
Directory of Open Access Journals (Sweden)
Tran Trong Dao
2011-01-01
Full Text Available The main aim of this work is to show that such a powerful optimizing tool like evolutionary algorithms (EAs can be in reality used for the simulation and optimization of a nonlinear system. A nonlinear mathematical model is required to describe the dynamic behaviour of batch process; this justifies the use of evolutionary method of the EAs to deal with this process. Four algorithms from the field of artificial intelligent—differential evolution (DE, self-organizing migrating algorithm (SOMA, genetic algorithm (GA, and simulated annealing (SA—are used in this investigation. The results show that EAs are used successfully in the process optimization.
Edge detection algorithms implemented on Bi-i cellular vision system
Karabiber, Fethullah; Arik, Sabri
2009-02-01
Bi-i (Bio-inspired) Cellular Vision system is built mainly on Cellular Neural /Nonlinear Networks (CNNs) type (ACE16k) and Digital Signal Processing (DSP) type microprocessors. CNN theory proposed by Chua has advanced properties for image processing applications. In this study, the edge detection algorithms are implemented on the Bi-i Cellular Vision System. Extracting the edge of an image to be processed correctly and fast is of crucial importance for image processing applications. Threshold Gradient based edge detection algorithm is implemented using ACE16k microprocessor. In addition, pre-processing operation is realized by using an image enhancement technique based on Laplacian operator. Finally, morphologic operations are performed as post processing operations. Sobel edge detection algorithm is performed by convolving sobel operators with the image in the DSP. The performances of the edge detection algorithms are compared using visual inspection and timing analysis. Experimental results show that the ACE16k has great computational power and Bi-i Cellular Vision System is very qualified to apply image processing algorithms in real time.
Modified kernel-based nonlinear feature extraction.
Energy Technology Data Exchange (ETDEWEB)
Ma, J. (Junshui); Perkins, S. J. (Simon J.); Theiler, J. P. (James P.); Ahalt, S. (Stanley)
2002-01-01
Feature Extraction (FE) techniques are widely used in many applications to pre-process data in order to reduce the complexity of subsequent processes. A group of Kernel-based nonlinear FE ( H E ) algorithms has attracted much attention due to their high performance. However, a serious limitation that is inherent in these algorithms -- the maximal number of features extracted by them is limited by the number of classes involved -- dramatically degrades their flexibility. Here we propose a modified version of those KFE algorithms (MKFE), This algorithm is developed from a special form of scatter-matrix, whose rank is not determined by the number of classes involved, and thus breaks the inherent limitation in those KFE algorithms. Experimental results suggest that MKFE algorithm is .especially useful when the training set is small.
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
Luo, Biao; Liu, Derong; Wu, Huai-Ning
2017-10-03
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 Q(0)(x,a)≽ 0. 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.
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.
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
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.
A Prediction Error Estimator for Nonlinear Stochastic Systems
Leontaritis, I.J.; Billings, S.A.
1986-01-01
A prediction error estimation algorithm incorporating model selection and validation techniques is developed for a class of multivariable discrete time stochastic nonlinear systems which can be represented by the NARMAX (Nonlinear AutoRegressive Moving Average Model with eXogenous inputs)
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...
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)
Invariant metric for nonlinear symplectic maps
Indian Academy of Sciences (India)
a function of system parameters, we demonstrate that the performance of a nonlinear Hamiltonian system is enhanced. Keywords. Invariant metric; symplectic maps; performance optimization. PACS Nos 05.45. ...... [7] A Nijenhuis and H S Wilf, Computational algorithms for computers and calculators (Academic. Press, New ...
Controller Reconfiguration for non-linear systems
Kanev, S.K.; Verhaegen, M.H.G.
2000-01-01
This paper outlines an algorithm for controller reconfiguration for non-linear systems, based on a combination of a multiple model estimator and a generalized predictive controller. A set of models is constructed, each corresponding to a different operating condition of the system. The interacting
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
An inductorless CMOS realization of Chua's circuit
Radwan, A G; El-Sedeek, A L
2003-01-01
In this paper, an inductorless CMOS realization of Chua's circuit [IEEE Trans. Circ. Syst.--I 1985;32:798] is presented. The circuit is derived from the dimensionless form of Chua's circuit and can generate Rossler or double-scroll attractors by changing a single capacitor's value. Variables are represented in the current domain to facilitate adding or subtracting variables. New G sub m -C representation of the Chua diode as well as the Chua circuit are presented. The circuit can operate from supply voltage as low as +-1.5 V. Transistor-level simulation results using PSpice in 0.5 mu m Mietec process are presented.
Realized Variance and Market Microstructure Noise
DEFF Research Database (Denmark)
Hansen, Peter R.; Lunde, Asger
2006-01-01
-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......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...
FPGA Realization of Memory 10 Viterbi Decoder
DEFF Research Database (Denmark)
Paaske, Erik; Bach, Thomas Bo; Andersen, Jakob Dahl
1997-01-01
A feasibility study for a low cost, iterative, serially concatenated coding system is performed. The system uses outer (255,223) Reed-Solomon codes and convolutional inner codes with memory 10 and rates 1/4 or 1/6. The corresponding inner decoder is a Viterbi decoder, which can operate in a forced...... 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...
Developing communications requirements for Agile Product Realization
Energy Technology Data Exchange (ETDEWEB)
Forsythe, C.; Ashby, M.R.
1994-03-01
Sandia National Laboratories has undertaken the Agile Product Realization for Innovative electroMEchanical Devices (A-PRIMED) pilot project to develop and implement technologies for agile design and manufacturing of electrochemical components. Emphasis on information-driven processes, concurrent engineering and multi-functional team communications makes computer-supported cooperative work critical to achieving significantly faster product development cycles. This report describes analyses conducted in developing communications requirements and a communications plan that addresses the unique communications demands of an agile enterprise.
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
Realization of Environmental Targets. Progress Report 2008
International Nuclear Information System (INIS)
Hoen, A.; Kruitwagen, S.
2008-01-01
35 indicators that link up to the articles from the VROM budget are used to describe current developments in the field of the environment. It is also indicated whether the Netherlands will meet the national and European obligatory environmental objectives. This report shows that the trends in environmental stress and environmental quality are positive. Some exceptions are the trend of the energy saving pace and the CO2 emission of traffic and transport. Contrary to the generally favorable trends there is also much uncertainty for many environmental dossiers whether the established objectives can be realized in time. [mk] [nl
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...... 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...
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.
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)
Estimating quadratic variation using realized variance
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole Eiler; Shephard, N.
2002-01-01
This paper looks at some recent work on estimating quadratic variation using realized variance (RV) - that is, sums of M squared returns. This econometrics has been motivated by the advent of the common availability of high-frequency financial return data. When the underlying process is a semimar......This paper looks at some recent work on estimating quadratic variation using realized variance (RV) - that is, sums of M squared returns. This econometrics has been motivated by the advent of the common availability of high-frequency financial return data. When the underlying process...... is a semimartingale we recall the fundamental result that RV is a consistent (as M ) estimator of quadratic variation (QV). We express concern that without additional assumptions it seems difficult to give any measure of uncertainty of the RV in this context. The position dramatically changes when we work...... with a rather general SV model - which is a special case of the semimartingale model. Then QV is integrated variance and we can derive the asymptotic distribution of the RV and its rate of convergence. These results do not require us to specify a model for either the drift or volatility functions, although we...
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.
Atom lasers and nonlinear atom optics
International Nuclear Information System (INIS)
Deng Lu
2000-01-01
Two recent experimental breakthroughs in the field of atomic physics are reported: the realization of a well-collimated, widely tunable, quasi-continuous wave atom laser, and the generation of matter waves via coherent multi-wave mixing. The former is a critical step towards a continuous wave, high brightness atom laser while the latter has opened a new field of research: nonlinear atom optics
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...... consideration are applied for position tracking control of a hydraulic valve-cylinder drive exhibiting strong variations in inertia- and gravitational loads, and furthermore suffer from profound valve dynamics. Results demonstrate that both the twisting- and super twisting algorithms may be successfully applied...... dynamic effects of hydraulic valves such as slew rate limitations and time delays arising in the electrical and mechanical amplification stages limits the applicability of such methods, and may lead to partial losses of robustness and limit cycles/oscillations in the outputs, internal states and the valve...
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.
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.
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
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.
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.
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.
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.
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.
ANDRomeda: adaptive nonlinear dimensionality reduction
Marchette, David J.; Priebe, Carey E.
2000-03-01
Standard approaches for the classification of high dimensional data require the selection of features, the projection of the features to a lower dimensional space, and the construction of the classifier in the lower dimensional space. Two fundamental issues arise in determining an appropriate projection to a lower dimensional space: the target dimensionality for the projection must be determined, and a particular projection must be selected from a specified family. We present an algorithm which is designed specifically for classification task and addresses both these issues. The family of nonlinear projections considered is based on interpoint distances - in particular, we consider point-to-subset distances. Our algorithm selects both the number of subsets to use and the subsets themselves. The methodology is applied to an artificial nose odorant classification task.
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.
Nonlinear elliptic differential equations with multivalued nonlinearities
Indian Academy of Sciences (India)
Springer Verlag Heidelberg #4 2048 1996 Dec 15 10:16:45
Nonlinear elliptic differential equations with multivalued ... has a solution. Finally in the last part we consider an eigenvalue problem with a nonmonotone multivalued nonlinearity. Using the critical point theory for nonsmooth .... A is upper semicontinuous (as a set-valued map) from every finite dimensional subspace of X into ...
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
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....
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.
The (G /G )-expansion method for a discrete nonlinear Schrödinger ...
Indian Academy of Sciences (India)
Abstract. An improved algorithm is devised for using the (G /G)-expansion method to solve nonlinear differential-difference equations. With the aid of symbolic computation, we choose a discrete nonlinear Schrödinger equation to illustrate the validity and advan- tages of the improved algorithm. As a result, hyperbolic ...
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.
DEFF Research Database (Denmark)
Chon, K H; Cohen, R J; Holstein-Rathlou, N H
1997-01-01
A linear and nonlinear autoregressive moving average (ARMA) identification algorithm is developed for modeling time series data. The algorithm uses Laguerre expansion of kernals (LEK) to estimate Volterra-Wiener kernals. However, instead of estimating linear and nonlinear system dynamics via movi...
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
Incremental nonlinear dimensionality reduction by manifold learning.
Law, Martin H C; Jain, Anil K
2006-03-01
Understanding the structure of multidimensional patterns, especially in unsupervised cases, is of fundamental importance in data mining, pattern recognition, and machine learning. Several algorithms have been proposed to analyze the structure of high-dimensional data based on the notion of manifold learning. These algorithms have been used to extract the intrinsic characteristics of different types of high-dimensional data by performing nonlinear dimensionality reduction. Most of these algorithms operate in a "batch" mode and cannot be efficiently applied when data are collected sequentially. In this paper, we describe an incremental version of ISOMAP, one of the key manifold learning algorithms. Our experiments on synthetic data as well as real world images demonstrate that our modified algorithm can maintain an accurate low-dimensional representation of the data in an efficient manner.
Quantum Nonlinear Optics in Optomechanical Nanoscale Waveguides.
Zoubi, Hashem; Hammerer, Klemens
2017-09-22
We show that strong nonlinearities at the few photon level can be achieved in optomechanical nanoscale waveguides. We consider the propagation of photons in cm-scale one-dimensional nanophotonic structures where stimulated Brillouin scattering (SBS) is strongly enhanced by radiation pressure coupling. We introduce a configuration that allows slowing down photons by several orders of magnitude via SBS from sound waves using two pump fields. Slowly propagating photons can then experience strong nonlinear interactions through virtual off-resonant exchange of dispersionless phonons. As a benchmark we identify requirements for achieving a large cross-phase modulation among two counterpropagating photons applicable for photonic quantum gates. Our results indicate that strongly nonlinear quantum optics is possible in continuum optomechanical systems realized in nanophotonic structures.
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)
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.
Realization of Thermal Inertia in Frequency Domain
Directory of Open Access Journals (Sweden)
Boe-Shong Hong
2014-02-01
Full Text Available To realize the lagging behavior in heat conduction observed in these two decades, this paper firstly theoretically excludes the possibility that the underlying thermal inertia is a result of the time delay in heat diffusion. Instead, we verify in experiments the electro-thermal analogy, wherein the thermal inertial is parameterized by thermal inductance that formulates hyperbolic heat-conduction. The thermal hyperbolicity exhibits a special frequency response in Bode plot, wherein the amplitude ratios is kept flat after crossing some certain frequency, as opposed to Fourier heat-conduction. We apply this specialty to design an instrument that reliably identifies thermal inductances of some materials in frequency domain. The instrument is embedded with a DSP-based frequency synthesizer capable of modulating frequencies in utmost high-resolution. Thermal inertia implies a new possibility for energy storage in analogy to inductive energy storage in electricity or mechanics.
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 the chess mate solver application
Directory of Open Access Journals (Sweden)
Vučković Vladan V.
2004-01-01
Full Text Available This paper presents details of the chess mate solver application, which is a part of the author’s Geniss general chess application. The problem chess is an important domain connected with solving of the chess problems. The Geniss Mate Solver (G.M.S. application solves Mate-in-N-move problems. Main techniques used for the implementation of the application are full-width searching with Alpha-Beta pruning technique and zero evaluation function. The application is written in Delphi for Windows programming environment and the searching engine is completely coded in assembly language (about 10000 lines. This hybrid software structure enables efficient program development by using high-level programming environment and the realization of a very fast searching engine at the same time. The machine code is manually coded and could achieve above 7 million generated positions per second on the 1Ghz Celeron PC.
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.
Cavity control as a new quantum algorithms implementation treatment
AbuGhanem, M.; Homid, A. H.; Abdel-Aty, M.
2018-02-01
Based on recent experiments [ Nature 449, 438 (2007) and Nature Physics 6, 777 (2010)], a new approach for realizing quantum gates for the design of quantum algorithms was developed. Accordingly, the operation times of such gates while functioning in algorithm applications depend on the number of photons present in their resonant cavities. Multi-qubit algorithms can be realized in systems in which the photon number is increased slightly over the qubit number. In addition, the time required for operation is considerably less than the dephasing and relaxation times of the systems. The contextual use of the photon number as a main control in the realization of any algorithm was demonstrated. The results indicate the possibility of a full integration into the realization of multi-qubit multiphoton states and its application in algorithm designs. Furthermore, this approach will lead to a successful implementation of these designs in future experiments.
Robust discrete-time nonlinear sliding mode controller with plant ...
African Journals Online (AJOL)
This paper addresses the new control algorithm, by designing the asymptotically stable nonlinear sliding surface with investigation of the states. This proposed algorithm leads to solve the problem of unstable systems, by proving the asymptotic stability of a class of uncertain discrete-time systems. A particular linear ...
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.
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.
Existence and attractivity results for nonlinear first order random differential equations
Directory of Open Access Journals (Sweden)
Bapurao C. Dhage
2010-01-01
Full Text Available In this paper, the existence and attractivity results are proved for nonlinear first order ordinary random differential equations. Two examples are provided to demonstrate the realization of the abstract developed theory.
Study and Realization of Image Segmentation on the Cotton Foreign Fibers
Zheng, Wenxiu; Wang, Jinxing; Liu, Shuangxi; Wei, Xinhua
A method of foreign fibers image segmentation based on Mean shift, dilation and filtering algorithm is presented. For the representative gray images of hair, chicken feather and mixed foreign fibers, the Mean shift algorithm is used to carry on image segmentation; then dilation and filtering process is carried on to the divided image element. In this way the precise image segmentation of foreign fibers is realized. It's proved by experiments that the image segmentation method proposed by this article can suppress the noise well, and the segmentation results are satisfied for all kinds of foreign fibers image.
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.
State space realization of fractional order systems
International Nuclear Information System (INIS)
Djamah, T.; Mansouri, R.; Djennoune, S.; Bettayeb, M.
2009-01-01
In the past few years, fractional calculus appeared to be a useful tool for the modeling and control of dynamic systems. Although, some methods of the control theory have been developed for the commensurate case, the difficulties of the non commensurate called generalized fractional systems still remain unsolved. In this paper, a method is presented for obtaining the state space model of a generalized fractional system starting from its transfer function. The method remains valid for the particular cases of commensurate and integer systems. An application to some examples illustrates the algorithm.
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.
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
Linear Bregman algorithm implemented in parallel GPU
Li, Pengyan; Ke, Jue; Sui, Dong; Wei, Ping
2015-08-01
At present, most compressed sensing (CS) algorithms have poor converging speed, thus are difficult to run on PC. To deal with this issue, we use a parallel GPU, to implement a broadly used compressed sensing algorithm, the Linear Bregman algorithm. Linear iterative Bregman algorithm is a reconstruction algorithm proposed by Osher and Cai. Compared with other CS reconstruction algorithms, the linear Bregman algorithm only involves the vector and matrix multiplication and thresholding operation, and is simpler and more efficient for programming. We use C as a development language and adopt CUDA (Compute Unified Device Architecture) as parallel computing architectures. In this paper, we compared the parallel Bregman algorithm with traditional CPU realized Bregaman algorithm. In addition, we also compared the parallel Bregman algorithm with other CS reconstruction algorithms, such as OMP and TwIST algorithms. Compared with these two algorithms, the result of this paper shows that, the parallel Bregman algorithm needs shorter time, and thus is more convenient for real-time object reconstruction, which is important to people's fast growing demand to information technology.
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
Terahertz semiconductor nonlinear optics
DEFF Research Database (Denmark)
Turchinovich, Dmitry; Hvam, Jørn Märcher; Hoffmann, Matthias
2013-01-01
In this proceedings we describe our recent results on semiconductor nonlinear optics, investigated using single-cycle THz pulses. We demonstrate the nonlinear absorption and self-phase modulation of strong-field THz pulses in doped semiconductors, using n-GaAs as a model system. The THz nonlinear...
Nonlinear Microwave Optomechanics
Shevchuk, O.
2017-01-01
The nonlinearity is essential for creation of non-classical states of the cavity or mechanical resonator such as squeezed or cat states. A microwave cavity can be made nonlinear by, for instance, adding Josephson junctions. The mechanical resonator is inherently nonlinear. The radiation pressure
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.
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
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...
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.
Directory of Open Access Journals (Sweden)
Fernanda de Castilhos Corazza
2008-01-01
Full Text Available A subdivision algorithm is presented and applied to solving commonlyfound chemical engineering problems described by nonlinear algebraic systems. For this purpose, a web-based library available in the literature was used as the main source to select a wide class of one- and multidimensional problems, comprising phase and chemicalequilibrium, conversion in tubular and continuous stirred tank reactors, material and energy balances, etc. The problems are classified according to the literature as low, intermediate and of high degree of numerical difficulty based on specific characteristics, like discontinuities in the functions, multiple solutions with the occurrence of false and unfeasible roots, and the presence of null derivative values. It is shown that the algorithm isefficient and robust, even for multidimensional problems of high numerical difficulty, allowing to find simultaneously all the feasible roots of nonlinear algebraic systems, naturally excluding false and unfeasible solutions, with a relatively low CPU time. Thesefeatures make the algorithm an interesting alternative to deal with chemical engineering problems in contrast to some methods currently in the literature.Um algoritmo de subdivisão é apresentado e aplicado à solução de problemas descritos por sistemas de equações algébricas não-linearescomumente encontrados na engenharia química. Uma biblioteca disponível, na literatura, foi utilizada como fonte principal para a seleção dos problemas a serem resolvidos com uma ou várias dimensões, compreendendo problemas de equilíbrio químico e de fases, conversãoem reatores tubulares e contínuos, balanços material e energético, entre outros. Os problemas foram classificados pela literatura com grau de dificuldade numérica baixa, intermediária e alta, com base em características específicas como a existência de descontinuidades nas funções, múltiplas soluções com raízes falsas. O algoritmo mostrou
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
Kulic, Filip; Jankovic, Veroslav; Oros, Djura; Vasic, Veran
2009-01-01
One of the specific functions of the energy management system is the prediction of energy consumption for the purpose of the timely reaction to and prevention of undesirable situations. Moreover, the energy consumption prediction enables better planning of the energy production and contributes to the reduction of all production costs. This paper shows a new original algorithm for energy consumption forecasting based on support vector machines. The developed energy management system is realize...
Digital Hardware Realization of Forward and Inverse Kinematics for a Five-Axis Articulated Robot Arm
Hai Linh, Bui Thi; Kung, Ying-Shieh
2015-01-01
When robot arm performs a motion control, it needs to calculate a complicated algorithm of forward and inverse kinematics which consumes much CPU time and certainty slows down the motion speed of robot arm. Therefore, to solve this issue, the development of a hardware realization of forward and inverse kinematics for an articulated robot arm is investigated. In this paper, the formulation of the forward and inverse kinematics for a five-axis articulated robot arm is derived firstly. Then, the...
Tabu search algorithms for water network optimization
Cunha, Maria da Conceição; Ribeiro, Luísa
2004-01-01
In this paper we propose a tabu search algorithm to find the least-cost design of looped water distribution networks. The mathematical nature of this optimization problem, a nonlinear mixed integer problem, is at the origin of a multitude of contributions to the literature in the last 25 years. In fact, exact optimization methods have not been found for this type of problem, and, in the past, classical optimization methods, like linear and nonlinear programming, were tried at the cost of dras...
Active noise cancellation algorithms for impulsive noise.
Li, Peng; Yu, Xun
2013-04-01
Impulsive noise is an important challenge for the practical implementation of active noise control (ANC) systems. The advantages and disadvantages of popular filtered- X least mean square (FXLMS) ANC algorithm and nonlinear filtered-X least mean M-estimate (FXLMM) algorithm are discussed in this paper. A new modified FXLMM algorithm is also proposed to achieve better performance in controlling impulsive noise. Computer simulations and experiments are carried out for all three algorithms and the results are presented and analyzed. The results show that the FXLMM and modified FXLMM algorithms are more robust in suppressing the adverse effect of sudden large amplitude impulses than FXLMS algorithm, and in particular, the proposed modified FXLMM algorithm can achieve better stability without sacrificing the performance of residual noise when encountering impulses.
Wu, Zong-Sheng; Fu, Wei-Ping; Xue, Ru
2015-01-01
Teaching-learning-based optimization (TLBO) algorithm is proposed in recent years that simulates the teaching-learning phenomenon of a classroom to effectively solve global optimization of multidimensional, linear, and nonlinear problems over continuous spaces. In this paper, an improved teaching-learning-based optimization algorithm is presented, which is called nonlinear inertia weighted teaching-learning-based optimization (NIWTLBO) algorithm. This algorithm introduces a nonlinear inertia weighted factor into the basic TLBO to control the memory rate of learners and uses a dynamic inertia weighted factor to replace the original random number in teacher phase and learner phase. The proposed algorithm is tested on a number of benchmark functions, and its performance comparisons are provided against the basic TLBO and some other well-known optimization algorithms. The experiment results show that the proposed algorithm has a faster convergence rate and better performance than the basic TLBO and some other algorithms as well.
A search for integrable four-dimensional nonlinear accelerator lattices
Energy Technology Data Exchange (ETDEWEB)
Nagaitsev, S.; /Fermilab; Danilov, V.; /SNS Project, Oak Ridge
2010-05-01
Integrable nonlinear motion in accelerators has the potential to introduce a large betatron tune spread to suppress instabilities and to mitigate the effects of space charge and magnetic field errors. To create such an accelerator lattice one has to find magnetic and/or electric field combinations leading to a stable integrable motion. This paper presents families of lattices with one invariant where bounded motion can be easily created in large volumes of the phase space. In addition, it presents two examples of integrable nonlinear accelerator lattices, realizable with longitudinal-coordinate-dependent magnetic or electric fields with the stable nonlinear motion, which can be solved in terms of separable variables.
Solutions manual to accompany Nonlinear programming
Bazaraa, Mokhtar S; Shetty, C M
2014-01-01
As the Solutions Manual, this book is meant to accompany the main title, Nonlinear Programming: Theory and Algorithms, Third Edition. This book presents recent developments of key topics in nonlinear programming (NLP) using a logical and self-contained format. The volume is divided into three sections: convex analysis, optimality conditions, and dual computational techniques. Precise statements of algortihms are given along with convergence analysis. Each chapter contains detailed numerical examples, graphical illustrations, and numerous exercises to aid readers in understanding the concepts a
Worldsheet Realization of the Refined Topological String
Antoniadis, I; Hohenegger, S; Narain, K S; Assi, A Zein
2013-01-01
A worldsheet realization of the refined topological string is proposed in terms of physical string amplitudes that compute generalized N=2 F-terms of the form F_{g,n} W^{2g}Y^{2n} in the effective supergravity action. These terms involve the chiral Weyl superfield W and a superfield Y defined as an N=2 chiral projection of a particular anti-chiral T-bar vector multiplet. In Heterotic and Type I theories, obtained upon compactification on the six-dimensional manifold K3xT2, T is the usual K\\"ahler modulus of the T2 torus. These amplitudes are computed exactly at the one-loop level in string theory. They are shown to reproduce the correct perturbative part of the Nekrasov partition function in the field theory limit when expanded around an SU(2) enhancement point of the string moduli space. The two deformation parameters epsilon_- and epsilon_+ of the Omega-supergravity background are then identified with the constant field-strength backgrounds for the anti-self-dual graviphoton and self-dual gauge field of the...
Realizing the promise of breast cancer vaccines
Directory of Open Access Journals (Sweden)
Jackson E
2012-08-01
Full Text Available Erica Jackson, Hatem SolimanUniversity of South Florida/Moffitt Cancer Center and Research Institute, Tampa, FL, USAAbstract: Breast cancer vaccines are being developed to stimulate adaptive antitumor immune responses in patients. These vaccines have the potential to treat breast cancer with minimal side effects and toxicity. However, many obstacles still need to be overcome to fully realize the vaccines' clinical benefit. A review of the literature was conducted to assess the use of vaccines in targeting transformed cells. Four vaccines currently under study were discussed, each summarizing the different vaccine platforms used to introduce target antigen to the patient's immune system. The advantages and disadvantages of each method were discussed, although no one method was found to be superior. Additional issues addressed included overcoming tumor-induced immunosuppression, immune evasion of transformed cells, the use of vaccines in combination therapy, and the challenges of using these vaccines in various clinical settings. Vaccines may be most effective in patients with minimal residual disease, as opposed to using them in the metastatic setting. Also, specific clinical trial design considerations for the use of vaccines in cancer patients, such as time-to-failure end points, were discussed. Understanding these various elements will be important to the translation of breast cancer vaccine therapy into routine clinical practice.Keywords: breast cancer, vaccine, immunotherapy, immune tolerance, peptide vaccine, dendritic cell vaccine
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
Realization of an optimized 3D USCT
Ruiter, Nicole V.; Göbel, Georg; Berger, Lutz; Zapf, Michael; Gemmeke, Hartmut
2011-03-01
A promising candidate for improved imaging of breast cancer is ultrasound computer tomography (USCT). Current experimental USCT systems are still focused in elevation dimension resulting in a large slice thickness, limited depth of field, loss of out-of-plane reflections, and a large number of movement steps to acquire a stack of images. 3DUSCT emitting and receiving spherical wave fronts overcomes these limitations. We built an optimized 3DUSCT with nearly isotropic 3D point spread function, realizing for the first time the full benefits of a 3D system. The 3DUSCT II is based on a semi-ellipsoidal transducer holder cut from polyoxymethylene. The aperture is implemented together with water supply, disinfection unit, temperature control, and movement mechanics in a patient bed. 2041 transducers are mounted in the aperture holder grouped into transducer array systems with embedded amplifiers and emitter electronics. The data acquisition is carried out with 480 parallel channels at 20MHz and with 12 bit resolution. 3.5 million A-Scans with 20 GByte of raw data are acquired for one breast volume. With data acquisition time of less than two minutes for one breast volume, the new system enables the next step of our research: a first clinical study.
Next-generation LWRs development toward realization
International Nuclear Information System (INIS)
Mitsumata, Hiroki; Kasai, S.; Ohga, Y.; Kurosaki, T.
2010-01-01
This special article introduced the round-table talk of 'next-generation LWRs development toward realization' at the issue of an intermediate evaluation report about technology development of next-generation LWRs in 2010. 'Recent trends around nuclear energy and next-generation LWRs development' and 'summary of the report' were also included. After a 2-year feasibility study on development of next-generation LWRs, the vision of this development has been established as follows; the new designs of HP-BWR and HP-PWR, based on ABWR and APWR, are to lead to a large reduction in construction and generation costs and a 30% reduction of spent fuel quantity with improved safety, 30-month construction and a design life of 80 years with 24-month operating cycle. In 2008 the project was established within the Institute of Applied Energy to pursue this vision, involving three manufacturers. Over eight years, the project is to develop designs of BWR and PWR with 1700-1800 MWe. Basic designs are to be finished by 2015, with significant deployment as new alternative reactors in Japan or internationally by 2030. (T. Tanaka)
Solving Nonlinear Euler Equations with Arbitrary Accuracy
Dyson, Rodger W.
2005-01-01
A computer program that efficiently solves the time-dependent, nonlinear Euler equations in two dimensions to an arbitrarily high order of accuracy has been developed. The program implements a modified form of a prior arbitrary- accuracy simulation algorithm that is a member of the class of algorithms known in the art as modified expansion solution approximation (MESA) schemes. Whereas millions of lines of code were needed to implement the prior MESA algorithm, it is possible to implement the present MESA algorithm by use of one or a few pages of Fortran code, the exact amount depending on the specific application. The ability to solve the Euler equations to arbitrarily high accuracy is especially beneficial in simulations of aeroacoustic effects in settings in which fully nonlinear behavior is expected - for example, at stagnation points of fan blades, where linearizing assumptions break down. At these locations, it is necessary to solve the full nonlinear Euler equations, and inasmuch as the acoustical energy is of the order of 4 to 5 orders of magnitude below that of the mean flow, it is necessary to achieve an overall fractional error of less than 10-6 in order to faithfully simulate entropy, vortical, and acoustical waves.
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 quantum realization of Arnold and Fibonacci image scrambling
Jiang, Nan; Wu, Wen-Ya; Wang, Luo
2014-05-01
The quantum Fourier transform, the quantum wavelet transform, etc., have been shown to be a powerful tool in developing quantum algorithms. However, in classical computing, there is another kind of transforms, image scrambling, which are as useful as Fourier transform, wavelet transform, etc. The main aim of image scrambling, which is generally used as the preprocessing or postprocessing in the confidentiality storage and transmission, and image information hiding, was to transform a meaningful image into a meaningless or disordered image in order to enhance the image security. In classical image processing, Arnold and Fibonacci image scrambling are often used. In order to realize these two image scrambling in quantum computers, this paper proposes the scrambling quantum circuits based on the flexible representation for quantum images. The circuits take advantage of the plain adder and adder modulo to factor the classical transformations into basic unitary operators such as Control-NOT gates and Toffoli gates. Theoretical analysis indicates that the network complexity grows linearly with the size of the number to be operated.
ALGORITHM OF OBJECT RECOGNITION
Directory of Open Access Journals (Sweden)
Loktev Alexey Alexeevich
2012-10-01
Full Text Available The second important problem to be resolved to the algorithm and its software, that comprises an automatic design of a complex closed circuit television system, represents object recognition, by virtue of which an image is transmitted by the video camera. Since imaging of almost any object is dependent on many factors, including its orientation in respect of the camera, lighting conditions, parameters of the registering system, static and dynamic parameters of the object itself, it is quite difficult to formalize the image and represent it in the form of a certain mathematical model. Therefore, methods of computer-aided visualization depend substantially on the problems to be solved. They can be rarely generalized. The majority of these methods are non-linear; therefore, there is a need to increase the computing power and complexity of algorithms to be able to process the image. This paper covers the research of visual object recognition and implementation of the algorithm in the view of the software application that operates in the real-time mode
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)
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...
Realizing e-government benefits with minimal capabilities
DEFF Research Database (Denmark)
Pedersen, Keld
2017-01-01
Abstract Purpose — The purpose is to increase our understanding of the requirements for public sector organizations to implement benefits realization practices. The research compares benefits realization practices as suggested by the literature with actual practice with the goal of identifying bo...... the research studies benefits realization from an organizational process perspective, and not from the perspective of IT projects. Keywords — Benefits realization, E-government, Local government, Challenges. Paper type — Research paper....
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.
Directory of Open Access Journals (Sweden)
Bazhenov V.А.
2011-11-01
Full Text Available The realization order and the numerical research results for two-mass vibroimpact systems with two degrees of freedom are examined in this article. These systems are under periodic external loading. The numerical researches are fulfilled by continuation after parameter method. The solutions of movement equations are obtained depending of external loading amplitude, the loading curves and the contact force graphes are constructed. The impact is simulated by the nonlinear contact interaction force describing by Hertz law. Reliability of the received results is controlled.
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
Wang, Jie-sheng; Li, Shu-xia; Gao, Jie
2014-01-01
For meeting the real-time fault diagnosis and the optimization monitoring requirements of the polymerization kettle in the polyvinyl chloride resin (PVC) production process, a fault diagnosis strategy based on the self-organizing map (SOM) neural network is proposed. Firstly, a mapping between the polymerization process data and the fault pattern is established by analyzing the production technology of polymerization kettle equipment. The particle swarm optimization (PSO) algorithm with a new dynamical adjustment method of inertial weights is adopted to optimize the structural parameters of SOM neural network. The fault pattern classification of the polymerization kettle equipment is to realize the nonlinear mapping from symptom set to fault set according to the given symptom set. Finally, the simulation experiments of fault diagnosis are conducted by combining with the industrial on-site historical data of the polymerization kettle and the simulation results show that the proposed PSO-SOM fault diagnosis strategy is effective.
Directory of Open Access Journals (Sweden)
Jie-sheng Wang
2014-01-01
Full Text Available For meeting the real-time fault diagnosis and the optimization monitoring requirements of the polymerization kettle in the polyvinyl chloride resin (PVC production process, a fault diagnosis strategy based on the self-organizing map (SOM neural network is proposed. Firstly, a mapping between the polymerization process data and the fault pattern is established by analyzing the production technology of polymerization kettle equipment. The particle swarm optimization (PSO algorithm with a new dynamical adjustment method of inertial weights is adopted to optimize the structural parameters of SOM neural network. The fault pattern classification of the polymerization kettle equipment is to realize the nonlinear mapping from symptom set to fault set according to the given symptom set. Finally, the simulation experiments of fault diagnosis are conducted by combining with the industrial on-site historical data of the polymerization kettle and the simulation results show that the proposed PSO-SOM fault diagnosis strategy is effective.
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; �...
Genetic Algorithm Tuned Fuzzy Logic for Gliding Return Trajectories
Burchett, Bradley T.
2003-01-01
The problem of designing and flying a trajectory for successful recovery of a reusable launch vehicle is tackled using fuzzy logic control with genetic algorithm optimization. The plant is approximated by a simplified three degree of freedom non-linear model. A baseline trajectory design and guidance algorithm consisting of several Mamdani type fuzzy controllers is tuned using a simple genetic algorithm. Preliminary results show that the performance of the overall system is shown to improve with genetic algorithm tuning.
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...
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.
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
NLINEAR - NONLINEAR CURVE FITTING PROGRAM
Everhart, J. L.
1994-01-01
A common method for fitting data is a least-squares fit. In the least-squares method, a user-specified fitting function is utilized in such a way as to minimize the sum of the squares of distances between the data points and the fitting curve. The Nonlinear Curve Fitting Program, NLINEAR, is an interactive curve fitting routine based on a description of the quadratic expansion of the chi-squared statistic. NLINEAR utilizes a nonlinear optimization algorithm that calculates the best statistically weighted values of the parameters of the fitting function and the chi-square that is to be minimized. The inputs to the program are the mathematical form of the fitting function and the initial values of the parameters to be estimated. This approach provides the user with statistical information such as goodness of fit and estimated values of parameters that produce the highest degree of correlation between the experimental data and the mathematical model. In the mathematical formulation of the algorithm, the Taylor expansion of chi-square is first introduced, and justification for retaining only the first term are presented. From the expansion, a set of n simultaneous linear equations are derived, which are solved by matrix algebra. To achieve convergence, the algorithm requires meaningful initial estimates for the parameters of the fitting function. NLINEAR is written in Fortran 77 for execution on a CDC Cyber 750 under NOS 2.3. It has a central memory requirement of 5K 60 bit words. Optionally, graphical output of the fitting function can be plotted. Tektronix PLOT-10 routines are required for graphics. NLINEAR was developed in 1987.
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
A multistable cellular nonlinear network for quality control by visual inspection
Nofiele, B.; Morfu, S.; Marquié, P.
2007-01-01
We propose a Cellular Nonlinear Network (CNN) ruled by reaction-diffusion equations for quality control by artificial visual inspection. We show that, using a specific nonlinearity allows to extract regions of interest in a noisy and weakly contrasted image without any processing time setting. We finally present the electronic realization of an elementary cell of the CNN for a possible electronic integration.
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.
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
Nonlinear electrical properties of Si three-terminal junction devices
DEFF Research Database (Denmark)
Fantao, Meng; Jie, Sun; Graczyk, Mariusz
2010-01-01
This letter reports on the realization and characterization of silicon three-terminal junction devices made in a silicon-on-insulator wafer. Room temperature electrical measurements show that the fabricated devices exhibit pronounced nonlinear electrical properties inherent to ballistic electron...
Optoelectronic and nonlinear optical processes in low dimensional ...
Indian Academy of Sciences (India)
optical response and high luminescence quantum yield expected in these systems is a consequence of huge en- hancement of transition probabilities ensuing ... compression and storage, can all be realized by nonlinear dynamical systems as these exhibit self .... or a very slow recovery. However, since the effect is com-.
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.
Breathers and rogue waves: Demonstration with coupled nonlinear ...
Indian Academy of Sciences (India)
Abstract. Different types of breathers and rogue waves (RWs) are some of the important coher- ent structures which have been recently realized in several physical phenomena in hydrodynamics, nonlinear optics, Bose–Einstein condensates, etc. Mathematically, they have been deduced in non- linear Schrödinger (NLS) ...
Optical computation based on nonlinear total reflectional optical ...
Indian Academy of Sciences (India)
A new scheme of binary half adder and full adder is proposed. It realizes a kind of all-optical computation which is based on the polarization coding technique and the nonlinear total reflectional optical switches. Author Affiliations. Jianqi Zhang1 Huan Xu2. Laboratory of Photonic Information Technology, School of ...
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
District Heating Network Design and Configuration Optimization with Genetic Algorithm
DEFF Research Database (Denmark)
Li, Hongwei; Svendsen, Svend
2013-01-01
and the pipe friction and heat loss formulations are non-linear. In order to find the optimal district heating network configuration, genetic algorithm which handles the mixed integer nonlinear programming problem is chosen. The network configuration is represented with binary and integer encoding...
Yang, Yun; Zhang, Weigang; Guo, Pan
2010-07-01
The proposed approach in this paper is divided into three steps namely the location of plate, the segmentation of the characters and the recognition of the characters. The location algorithm is firstly consisted of two video captures to get high quality images, and estimates the size of vehicle plate in these images via parallel binocular stereo vision algorithm. Then the segmentation method extracts the edge of vehicle plate based on second generation non-orthogonal Haar wavelet transformation, and locates the vehicle plate according to the estimated result in the first step. Finally, the recognition algorithm is realized based on the Radial Basis Function Fuzzy Neural Network. Experiments have been conducted for real images. The results show this method can decrease the error recognition rate of Chinese license plate recognition.
Noise in nonlinear nanoelectromechanical resonators
Guerra Vidal, Diego N.
Nano-Electro-Mechanical Systems (NEMS), due to their nanometer scale size, possess a number of desirable attributes: high sensitivity to applied forces, fast response times, high resonance frequencies and low power consumption. However, ultra small size and low power handling result in unwanted consequences: smaller signal size and higher dissipation, making the NEMS devices more susceptible to external and intrinsic noise. The simplest version of a NEMS, a suspended nanomechanical structure with two distinct excitation states, can be used as an archetypal two state system to study a plethora of fundamental phenomena such as Duffing nonlinearity, stochastic resonance, and macroscopic quantum tunneling at low temperatures. From a technical perspective, there are numerous applications such nanomechanical memory elements, microwave switches and nanomechanical computation. The control and manipulation of the mechanical response of these two state systems can be realized by exploiting a (seemingly) counterintuitive physical phenomenon, Stochastic Resonance: in a noisy nonlinear mechanical system, the presence of noise can enhance the system response to an external stimulus. This Thesis is mainly dedicated to study possible applications of Stochastic Resonance in two-state nanomechanical systems. First, on chip signal amplification by 1/falpha is observed. The effectiveness of the noise assisted amplification is observed to decrease with increasing a. Experimental evidence shows an increase in asymmetry between the two states with increasing noise color. Considering the prevalence of 1/f alpha noise in the materials in integrated circuits, the signal enhancement demonstrated here, suggests beneficial use of the otherwise detrimental noise. Finally, a nanomechanical device, operating as a reprogrammable logic gate, and performing fundamental logic functions such as AND/OR and NAND/NOR is presented. The logic function can be programmed (from AND to OR) dynamically, by
Nonlinear-Based MEMS Sensors and Active Switches for Gas and Acceleration Applications
Younis, Mohammad I.
2016-11-25
In this talk, we demonstrate the realization of smart sensors and actuators through the exploitation of principles of nonlinear dynamics at the micro scale. Specifically, we demonstrate combining sensing and actuation into a single device through what is called smart switches triggered by the detection of a desirable physical quantity. The concept aims to reduce the complexity of systems that rely on controllers and complex algorithms to realize on-demand trigger actions. In the first part of the talk, we discuss the category of switches triggered by the detection of gas. Toward this, electrostatically microbeams resonators are fabricated, then coated with highly absorbent polymers (MOFs), and afterward are exposed to gases. Such devices can be useful for instant alarming of toxic gases. In the second part, we demonstrate switches triggered by shock and acceleration. The concept is demonstrated on a millimeter-scale capacitive sensor. The sensor is tested using acceleration generated from shakers. Such devices can be used for the deployment of airbags in automobiles.
Ooi, Kelvin J. A.; Tan, Dawn T. H.
2017-10-01
The rapid development of graphene has opened up exciting new fields in graphene plasmonics and nonlinear optics. Graphene's unique two-dimensional band structure provides extraordinary linear and nonlinear optical properties, which have led to extreme optical confinement in graphene plasmonics and ultrahigh nonlinear optical coefficients, respectively. The synergy between graphene's linear and nonlinear optical properties gave rise to nonlinear graphene plasmonics, which greatly augments graphene-based nonlinear device performance beyond a billion-fold. This nascent field of research will eventually find far-reaching revolutionary technological applications that require device miniaturization, low power consumption and a broad range of operating wavelengths approaching the far-infrared, such as optical computing, medical instrumentation and security applications.
Directory of Open Access Journals (Sweden)
Wei Khim Ng
2009-02-01
Full Text Available We construct nonlinear extensions of Dirac's relativistic electron equation that preserve its other desirable properties such as locality, separability, conservation of probability and Poincaré invariance. We determine the constraints that the nonlinear term must obey and classify the resultant non-polynomial nonlinearities in a double expansion in the degree of nonlinearity and number of derivatives. We give explicit examples of such nonlinear equations, studying their discrete symmetries and other properties. Motivated by some previously suggested applications we then consider nonlinear terms that simultaneously violate Lorentz covariance and again study various explicit examples. We contrast our equations and construction procedure with others in the literature and also show that our equations are not gauge equivalent to the linear Dirac equation. Finally we outline various physical applications for these equations.
Fermat's principle and nonlinear traveltime tomography
International Nuclear Information System (INIS)
Berryman, J.G.; Courant Institute of Mathematical Sciences, New York University, 251 Mercer Street, New York, New York 10012)
1989-01-01
Fermat's principle shows that a definite convex set of feasible slowness models, depending only on the traveltime data, exists for the fully nonlinear traveltime inversion problem. In a new iterative reconstruction algorithm, the minimum number of nonfeasible ray paths is used as a figure of merit to determine the optimum size of the model correction at each step. The numerical results show that the new algorithm is robust, stable, and produces very good reconstructions even for high contrast materials where standard methods tend to diverge
Nonlinear Motion Tracking by Deep Learning Architecture
Verma, Arnav; Samaiya, Devesh; Gupta, Karunesh K.
2018-03-01
In the world of Artificial Intelligence, object motion tracking is one of the major problems. The extensive research is being carried out to track people in crowd. This paper presents a unique technique for nonlinear motion tracking in the absence of prior knowledge of nature of nonlinear path that the object being tracked may follow. We achieve this by first obtaining the centroid of the object and then using the centroid as the current example for a recurrent neural network trained using real-time recurrent learning. We have tweaked the standard algorithm slightly and have accumulated the gradient for few previous iterations instead of using just the current iteration as is the norm. We show that for a single object, such a recurrent neural network is highly capable of approximating the nonlinearity of its path.
Nonlinear principal component analysis and its applications
Mori, Yuichi; Makino, Naomichi
2016-01-01
This book expounds the principle and related applications of nonlinear principal component analysis (PCA), which is useful method to analyze mixed measurement levels data. In the part dealing with the principle, after a brief introduction of ordinary PCA, a PCA for categorical data (nominal and ordinal) is introduced as nonlinear PCA, in which an optimal scaling technique is used to quantify the categorical variables. The alternating least squares (ALS) is the main algorithm in the method. Multiple correspondence analysis (MCA), a special case of nonlinear PCA, is also introduced. All formulations in these methods are integrated in the same manner as matrix operations. Because any measurement levels data can be treated consistently as numerical data and ALS is a very powerful tool for estimations, the methods can be utilized in a variety of fields such as biometrics, econometrics, psychometrics, and sociology. In the applications part of the book, four applications are introduced: variable selection for mixed...
Numerical study of propagation properties of surface plasmon polaritons in nonlinear media
Sagor, Rakibul Hasan
2016-03-29
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 as ultrafast nonlinear materials. We have used the finite difference time domain (FDTD) method to develop the simulation algorithm for the current analysis. We have modeled the frequency dependent dispersion properties and third order nonlinearity property of chalcogenide glass utilizing the general polarization algorithm merged in the auxiliary differential equation (ADE) method. The propagation dynamics of the whole structure with and without third order nonlinearity property of chalcogenide glass have been simulated and the effect of nonlinearity on the propagation properties of SPP has been investigated. © 2016 EDP Sciences, SIF, Springer-Verlag Berlin Heidelberg.
DEFF Research Database (Denmark)
Markham, Annette
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...
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.
Energy Technology Data Exchange (ETDEWEB)
Grefenstette, J.J.
1994-12-31
Genetic algorithms solve problems by using principles inspired by natural population genetics: They maintain a population of knowledge structures that represent candidate solutions, and then let that population evolve over time through competition and controlled variation. GAs are being applied to a wide range of optimization and learning problems in many domains.
Nonlinear Talbot Effect and Its Applications
Yang, Zhening
2018-03-01
Talbot effect, a lenless self-imaging phenomenon, was first discovered in 1836 by H.F. Talbot. The conventional Talbott effect has been studied for over a hundred years. Recently, the rapid development of optical superlattices has brought a great breakthrough in Talbot effect research. A nonlinear self-imaging phenomenon was found in the periodically poled LiTaO3 (PPLT) crystals. [1][2][3] This nonlinear Talbot effect has applications not only in optics but also in many other fields. For example, the phenomenon is realized by frequency-doubled beams, which offers people a new way to enhance the spatial resolution of the self-images of periodic objects. And by observing the self-image of the second harmonic (SH) field on the sample surface, people can detect the domain structure in the crystal without damaging the sample. Throughout this review paper, an overview of nonlinear Talbot effect and two applications of this phenomenon is presented. Breakthroughs like achieving a super-focused spot and realizing an acousto-optic tunable SH Talbot illuminator will be introduced as well.
Stationary nonlinear Airy beams
International Nuclear Information System (INIS)
Lotti, A.; Faccio, D.; Couairon, A.; Papazoglou, D. G.; Panagiotopoulos, P.; Tzortzakis, S.; Abdollahpour, D.
2011-01-01
We demonstrate the existence of an additional class of stationary accelerating Airy wave forms that exist in the presence of third-order (Kerr) nonlinearity and nonlinear losses. Numerical simulations and experiments, in agreement with the analytical model, highlight how these stationary solutions sustain the nonlinear evolution of Airy beams. The generic nature of the Airy solution allows extension of these results to other settings, and a variety of applications are suggested.
Solving Large Scale Nonlinear Eigenvalue Problem in Next-Generation Accelerator Design
Energy Technology Data Exchange (ETDEWEB)
Liao, Ben-Shan; Bai, Zhaojun; /UC, Davis; Lee, Lie-Quan; Ko, Kwok; /SLAC
2006-09-28
A number of numerical methods, including inverse iteration, method of successive linear problem and nonlinear Arnoldi algorithm, are studied in this paper to solve a large scale nonlinear eigenvalue problem arising from finite element analysis of resonant frequencies and external Q{sub e} values of a waveguide loaded cavity in the next-generation accelerator design. They present a nonlinear Rayleigh-Ritz iterative projection algorithm, NRRIT in short and demonstrate that it is the most promising approach for a model scale cavity design. The NRRIT algorithm is an extension of the nonlinear Arnoldi algorithm due to Voss. Computational challenges of solving such a nonlinear eigenvalue problem for a full scale cavity design are outlined.
Ying, Hao
1993-01-01
The fuzzy controllers studied in this paper are the ones that employ N trapezoidal-shaped members for input fuzzy sets, Zadeh fuzzy logic and a centroid defuzzification algorithm for output fuzzy set. The author analytically proves that the structure of the fuzzy controllers is the sum of a global nonlinear controller and a local nonlinear proportional-integral-like controller. If N approaches infinity, the global controller becomes a nonlinear controller while the local controller disappears. If linear control rules are used, the global controller becomes a global two-dimensional multilevel relay which approaches a global linear proportional-integral (PI) controller as N approaches infinity.
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
Uraltseva, N N
1995-01-01
This collection focuses on nonlinear problems in partial differential equations. Most of the papers are based on lectures presented at the seminar on partial differential equations and mathematical physics at St. Petersburg University. Among the topics explored are the existence and properties of solutions of various classes of nonlinear evolution equations, nonlinear imbedding theorems, bifurcations of solutions, and equations of mathematical physics (Navier-Stokes type equations and the nonlinear Schrödinger equation). The book will be useful to researchers and graduate students working in p
Kono, Mitsuo
2010-01-01
A nonlinearity is one of the most important notions in modern physics. A plasma is rich in nonlinearities and provides a variety of behaviors inherent to instabilities, coherent wave structures and turbulence. The book covers the basic concepts and mathematical methods, necessary to comprehend nonlinear problems widely encountered in contemporary plasmas, but also in other fields of physics and current research on self-organized structures and magnetized plasma turbulence. The analyses make use of strongly nonlinear models solved by analytical techniques backed by extensive simulations and available experiments. The text is written for senior undergraduates, graduate students, lecturers and researchers in laboratory, space and fusion plasmas.
Nonlinear optics at interfaces
International Nuclear Information System (INIS)
Chen, C.K.
1980-12-01
Two aspects of surface nonlinear optics are explored in this thesis. The first part is a theoretical and experimental study of nonlinear intraction of surface plasmons and bulk photons at metal-dielectric interfaces. The second part is a demonstration and study of surface enhanced second harmonic generation at rough metal surfaces. A general formulation for nonlinear interaction of surface plasmons at metal-dielectric interfaces is presented and applied to both second and third order nonlinear processes. Experimental results for coherent second and third harmonic generation by surface plasmons and surface coherent antiStokes Raman spectroscopy (CARS) are shown to be in good agreement with the theory
International Nuclear Information System (INIS)
Zelenyj, L.M.; Kuznetsova, M.M.
1989-01-01
Nonlinear study of magnetic perturbation development under single-mode conditions in collision-free plasma in configurations with the magnetic field shear is investigated. Results are obtained with regard of transverse component of electrical field and its effect on ion dynamics within wide range of ion Larmor radius value and values of magnetic field shear. Increments of nonlinear drift tearing mode are obtained and it is shown that excitation drastic conditions of even linearly stable modes are possible. Mechanism of instability nonlinear stabilization is considered and the value of magnetic island at the saturation threshold is estimeted. Energy of nonlinear drift tearing mode is discussed
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
Foundations of Coupled Nonlinear Dimensionality Reduction
Mohri, Mehryar; Rostamizadeh, Afshin; Storcheus, Dmitry
2015-01-01
In this paper we introduce and analyze the learning scenario of \\emph{coupled nonlinear dimensionality reduction}, which combines two major steps of machine learning pipeline: projection onto a manifold and subsequent supervised learning. First, we present new generalization bounds for this scenario and, second, we introduce an algorithm that follows from these bounds. The generalization error bound is based on a careful analysis of the empirical Rademacher complexity of the relevant hypothes...
Artificial Flora (AF Optimization Algorithm
Directory of Open Access Journals (Sweden)
Long Cheng
2018-02-01
Full Text Available Inspired by the process of migration and reproduction of flora, this paper proposes a novel artificial flora (AF algorithm. This algorithm can be used to solve some complex, non-linear, discrete optimization problems. Although a plant cannot move, it can spread seeds within a certain range to let offspring to find the most suitable environment. The stochastic process is easy to copy, and the spreading space is vast; therefore, it is suitable for applying in intelligent optimization algorithm. First, the algorithm randomly generates the original plant, including its position and the propagation distance. Then, the position and the propagation distance of the original plant as parameters are substituted in the propagation function to generate offspring plants. Finally, the optimal offspring is selected as a new original plant through the selection function. The previous original plant becomes the former plant. The iteration continues until we find out optimal solution. In this paper, six classical evaluation functions are used as the benchmark functions. The simulation results show that proposed algorithm has high accuracy and stability compared with the classical particle swarm optimization and artificial bee colony algorithm.
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.
DEFF Research Database (Denmark)
Hansen, Peter Reinhard; Lunde, Asger; Voev, Valeri
the model to market returns in conjunction with an individual asset yields a model for the conditional regression coefficient, known as the beta. We apply the model to a set of highly liquid stocks and find that conditional betas are much more variable than usually observed with rolling-window OLS...... regressions with dailty data. In the empirical part of the paper we examine the cross-sectional as well as the time variation of the conditional beta series. The model links the conditional and realized second moment measures in a self-contained system of equations, making it amenable to extensions and easy...
Nonlinear regularization path for quadratic loss support vector machines.
Karasuyama, Masayuki; Takeuchi, Ichiro
2011-10-01
Regularization path algorithms have been proposed to deal with model selection problem in several machine learning approaches. These algorithms allow computation of the entire path of solutions for every value of regularization parameter using the fact that their solution paths have piecewise linear form. In this paper, we extend the applicability of regularization path algorithm to a class of learning machines that have quadratic loss and quadratic penalty term. This class contains several important learning machines such as squared hinge loss support vector machine (SVM) and modified Huber loss SVM. We first show that the solution paths of this class of learning machines have piecewise nonlinear form, and piecewise segments between two breakpoints are characterized by a class of rational functions. Then we develop an algorithm that can efficiently follow the piecewise nonlinear path by solving these rational equations. To solve these rational equations, we use rational approximation technique with quadratic convergence rate, and thus, our algorithm can follow the nonlinear path much more precisely than existing approaches such as predictor-corrector type nonlinear-path approximation. We show the algorithm performance on some artificial and real data sets. © 2011 IEEE
Continuous nonlinear optimization for engineering applications in GAMS technology
Andrei, Neculai
2017-01-01
This book presents the theoretical details and computational performances of algorithms used for solving continuous nonlinear optimization applications imbedded in GAMS. Aimed toward scientists and graduate students who utilize optimization methods to model and solve problems in mathematical programming, operations research, business, engineering, and industry, this book enables readers with a background in nonlinear optimization and linear algebra to use GAMS technology to understand and utilize its important capabilities to optimize algorithms for modeling and solving complex, large-scale, continuous nonlinear optimization problems or applications. Beginning with an overview of constrained nonlinear optimization methods, this book moves on to illustrate key aspects of mathematical modeling through modeling technologies based on algebraically oriented modeling languages. Next, the main feature of GAMS, an algebraically oriented language that allows for high-level algebraic representation of mathematical opti...
Directory of Open Access Journals (Sweden)
Jun Xie
2018-03-01
Full Text Available The increasing penetration of distributed energy resources in distribution systems has brought a number of network management and operational challenges; reactive power variation has been identified as one of the dominant effects. Enormous growth in a variety of controllable devices that have complex control requirements are integrated in distribution networks. The operation modes of traditional centralized control are difficult to tackle these problems with central controller. When considering the non-linear multi-objective functions with discrete and continuous optimization variables, the proposed random gradient-free algorithm is employed to the optimal operation of controllable devices for reactive power optimization. This paper presents a distributed reactive power optimization algorithm that can obtain the global optimum solution based on random gradient-free algorithm for distribution network without requiring a central coordinator. By utilizing local measurements and local communications among capacitor banks and distributed generators (DGs, the proposed reactive power control strategy can realize the overall network voltage optimization and power loss minimization simultaneously. Simulation studies on the modified IEEE-69 bus distribution systems demonstrate the effectiveness and superiority of the proposed reactive power optimization strategy.