Loading...
Search for:
manifolds
0.007 seconds
Total 103 records
Optimal trajectory design to Halo orbits via pseudo-invariant manifolds using a nonlinear four body formulation
, Article Acta Astronautica ; Volume 110 , 2015 , Pages 115-128 ; 00945765 (ISSN) ; Pourtakdoust, S. H ; Sharif University of Technology
Elsevier Ltd
2015
Abstract
This paper investigates the problem of optimal transfer trajectory design towards the L2 centered Halo orbit of the Sun-Earth three body system, where the initial launch is to start from a low Earth parking orbit (LEO). The proposed optimal transfer trajectory consists of an active part with low-thrust propulsion and a passive coasting part with no thrust or fuel consumption. In this respect a pseudo-stable manifold (SM) is initially determined through backward time integration of the bicircular four body (BCFB) equations of motion, whose initial states are obtained via stable manifolds of the restricted three body problem (R3BP). The optimal transfer trajectories are extracted via a hybrid...
An Adaptive Algorithm for Estimating the Frequency and Damping Factor of Damped Sinusoidal Signal: Analysis and Design
, M.Sc. Thesis Sharif University of Technology ; Karimi, Masoud (Supervisor) ; Mojiri, Mohsen (Supervisor)
Abstract
Disturbance rejection is one of the most important criteria that should be considered when designing control systems. The problem has been widely investigated and studied when the parameters of disturbance signal is known. However, there are still ongoing researches in the field when the parameters of disturbance signals are uncertain and/or varying with time. In some applications the disturbance signal can be modelled by special dynamics, e.g., step type disturbances with unknown magnitude, sinusoidal disturbances with unknown magnitude and frequency, and damped sinusoidal disturbances with unknown magnitude, frequency and damping factor. In such cases, an adaptive scheme for estimating the...
Data Labelling Using Manifold-Based Semi-Supervised Learning in Multispectral Remote Sensing
, M.Sc. Thesis Sharif University of Technology ; Rabiee, Hamid Reza (Supervisor) ; Safari, Mohammad Ali (Co-Advisor)
Abstract
Classification of hyperspectral remote sensing images is a challenging problem, because of the small number of labeled pixels, high dimensionality of the data and large number of pixels. In this context, semisupervised learning can improve the classification accuracy by extracting information form the distribution of all the labeled and unlabeled data. Among semi-supervised methods, manifold-based algorithms have been frequently used in recent years. In most of the previous works, manifolds are constructed according to spectral representation of data, while spatial dependency of pixel labels is an important property of the images in remote sensing applications. In this thesis, after...
A Special Stokes’s Theorem For Some Incomplete Riemannian Manifolds
, M.Sc. Thesis Sharif University of Technology ; Bahraini, Alireza (Supervisor)
Abstract
Let (M; g) be a Riemannian manifold. Using classical Stokes’ theorem one can show that the equality (dω; η)L2 = (ω; δη)L2 holds for smooth forms ! and η with compact supports, where δ is the formal adjoint of d . There are some examples of Riemannian manifolds for which the above equality does not hold for general forms ! and η i:e: smooth square-integrable forms such taht d! and δη are also squareintegrable. In the case that the above equality holds for such general forms on a Riemannian manifold (M; g) , we say that the L2 - Stokes theorem holds for (M; g) . In 1952, Gaffney showed that the L2 - Stokes theorem holds for complete Riemannian manifolds. But at that time, there was no powerful...
, M.Sc. Thesis Sharif University of Technology ; Parnianpour, Mohammad (Supervisor) ; Narimani, Roya (Supervisor)
Abstract
Injuries of neuro-musculoskeletal system impose large costs to the modem societies. Studying the strategies of CNS in planning and control of movements can be helpful in developing diagnoSiS, prognosis and treatment procedures in clinical view and also in designing rehabilitation system and humanoid robots. Tow important features of human movements are redundancy problem and structured variability. Previous studies solved the redundancy problem mainly with optimization methods. Also optimal feedback control theory is the only method that successfully modeled structured variability in voluntary movements. Despite the appropriate outputs this methods are not based on physiological facts...
The Geometry of the Group of Symplectic Diffeomorphisms
, M.Sc. Thesis Sharif University of Technology ; Eftekhary, Eiman (Supervisor) ; Esfahani Zadeh, Mostafa (Supervisor)
Abstract
In this thesis, we first define the pseudo-distance p on the group of Hamiltonian diffeomorphisms.Using the concept of displacement energy, we show that the pseudo-distance p is degenerate and if the manifold is closed, p will be zero for each p = 1; 2; 3; : : : Then, we introduce Lagrangian submanifolds and prove that if L R2n is a rational Lagrangian submanifold, we have the following inequality e(L) ≥ 1γ(L). : Finally, using the above inequality and the concept of displacement energy, for M = R2n we prove that 1 is non-degenerate. Therefore, the hypothesis for 1 to be a metric, are satisfied. This metric is called Hofer’s metric
Multi-Camera Action Recognition with Manifold Learning
, M.Sc. Thesis Sharif University of Technology ; Karbalaee Aghajan, Hamid (Supervisor)
Abstract
Human action recognition is one of the most attended topics in computer vision and robotics.One of the flavors of this problem relates to the situation in which the task of action recognition is carried out by data from several cameras. Different approaches have been proposed for combining information. Various reduction methods have been introduced to decrease the processing load. All of the methods in this particular field of study can be divided into two linear and non-linear methods. In the linear methods, we don’t pay attention to the non-linear structure of the data, and these kind of approaches are not reliable. Furthermore, combining different actions data is done before the dimension...
Image Matching Based on Manifold Learning Methods
, M.Sc. Thesis Sharif University of Technology ; Fatemizadeh, Emad (Supervisor)
Abstract
Medical imaging is of interest because of information that will provide for doctors and registration is inevitable when we need to compare two or more images, taken from a subject at different times or with different sensors or when comparing two or more subjects together. Registration methods can be categorized in two major groups; methods based on feature and methods based on intensity. Methods in first group have three steps in common: feature extraction, finding matches and transform estimation. In second group it’s important to define a similarity measure and find the transform that minimizes this measure.
Manifold learning algorithms are mostly used as a dimensionality reduction...
Manifold learning algorithms are mostly used as a dimensionality reduction...
Standardness of Einstein Solvmanifolds
, M.Sc. Thesis Sharif University of Technology ; Fanai, Hamid Reza (Supervisor)
Abstract
In this thesis, we review the proof to standardness of Einstein solvamanifolds which is based on some results from Geometric Invariant Theory and stratification of topological spaces. Standardness is a very simple and yet powerful algebraic condition on the lie algebra of a solvmanifold which yields to remarkable existence and uniqueness and obstruction results
Face Recognition in Subspaces Based on Nonlinear Dimension Reduction
, Ph.D. Dissertation Sharif University of Technology ; Kasaei, Shohreh (Supervisor)
Abstract
In many applications in human society, there is a need for identity recognition of people.Different methods have been developed for this purpose while using the biometrics is one of the major interests. The biometrics measure the unique physiological, anatomical and behavioural characteristics of people. Among them, face is an interesting biometric which have important advantages over other biometrics and face recognition is known as the most common method that people utilize to recognize each other. However, face recognition suffers from factors such as changes in head pose, illumination and face expression which influence the efficiency of recognition methods. The core of many recent...
Semi-Supervised Kernel Learning for Pattern Classification
, Ph.D. Dissertation Sharif University of Technology ; Rabiee, Hamid Reza (Supervisor)
Abstract
Supervised kernel learning has been the focus of research in recent years. Although these methods are developed based on rigorous frameworks, they fail to improve the classification accuracy in real world applications. In order to find the origin of this problem, it should be noted that the kernel function represents a prior knowledge on the labeling function. Similar to other learning problem, learning this prior knowledge needs another prior knowledge. In supervised kernel learning, only naive assumptions can be used as the prior knowledge. These include minimizing the ℓ1 and ℓ2 norms of the kernel parameters.
As an alternative approach, in Semi-Supervised Learning (SSL), unlabeled...
As an alternative approach, in Semi-Supervised Learning (SSL), unlabeled...
Hodge Theory on Algebraic Varieties
, M.Sc. Thesis Sharif University of Technology ; Jafari, Amir (Supervisor)
Abstract
Cohomology groups of complex algebraic varieties with coefficients in ℂ, can be considered more than just a vector space and they can equipped with various and rich linear algebra structures which are functorial with respect to morphisms between them. In this thesis we first review classic Hodge theory, Hodge decomposition and Lefschetz decomposition theorems which enable us to introduce the concept of pure Hodge structure on cohomology group H^n (X,C) of a compact Kähler manifold X. Then we define Frölicher spectral sequence for a complex manifold X and show that it will degenerate at E_1 when X is compact and Kähler. For generalization of pure Hodge structures to smooth non...
Modeling the Forces Acting on NASA's Probe B Satellite, Using Space-Time Fluid Analogy
, M.Sc. Thesis Sharif University of Technology ; Taeibi Rahni, Mohamad (Supervisor)
Abstract
The purpose of this thesis is to study the analogy of space-time fluid flow around Earth and to investigate the hydrodynamic forces caused by this fluid on NASA's Probe B satellite. According to recent research, Einstein's and Navier-Stokes equations are the same. The properties of space-time fluid, including equation of state, compressibility, viscosity, flow field around Earth, and the hydrodynamic forces entering Probe B satellite, are unknown. There are two views about the viscosity of space-time fluid. Spherical mass of the three-dimensional spherical sink and the nature of the sphere located in the probe satellite without a spherical solid particle It are considered within this flow....
Dynamical Properties of Rough Delay Equations
, Ph.D. Dissertation Sharif University of Technology ; Zohuri Zangeneh, Bijan (Supervisor)
Abstract
In this monograph, we investigate the long-time behavior of stochastic delay equations. Our approach is random dynamical systems, and we solve our equation in the rough path point of view. Namely, we deal with the singular case, i.e., when the delay terms also are appearing in the diffusion part. Although we can solve the equation using the classical tools of stochastic analysis, the main obstacle is the lack of flow property. More precisely, the solution does not depend continuously on the initial value. To solve this problem, we define this property differently. We will show how we can generate a flow property on fields of Banach spaces using rough path theory. As a consequence, we prove...
Classification of Partial Hyperbolic Diffeomorphisms on 3-manifolds
, M.Sc. Thesis Sharif University of Technology ; Safdari, Mohammad (Supervisor) ; Nassiri, Meysam (Supervisor)
Abstract
In this dissertation, we will study partially hyperbolic diffeomorphisms. First, we are going to introduce partially hyperbolic diffeomorphisms and construct some examples. One of the important questions in the study of partially hyperbolic diffeomorphisms is their classification problem, which provides a deeper understanding of manifolds and also of partially hyperbolic diffeomorphisms themselves. We will go through this problem by examining Hammerlindl, Potrie’s [1]’s work. They have proved that a partially hyperbolic diffeomorphism on a 3-manifold with a virtually solvable fundamental group, that has no periodic torus tangent to contraction-center or expansion-center, is dynamically...
On-line fault detection and isolation (FDI) for the exhaust path of a turbocharged SI engine
, Article ASME 2013 Dynamic Systems and Control Conference, DSCC 2013 ; Vol. 1 , 2013 ; ISBN: 9780791856123 ; Shahbakhti M ; Alasty, A ; Vossoughi, G ; Sharif University of Technology
Abstract
Detection and isolation of faults in the exhaust gas path of a turbocharged spark ignition (SI) engine is an essential part of the engine control unit (ECU) strategies to minimize exhaust emission and ensure safe operation of a turbocharger. This paper proposes a novel physics-based strategy to detect and isolate an exhaust manifold leakage and a closed-stuck wastegate fault. The strategy is based on a globally optimal parameter estimation algorithm which detects an effective hole area in the exhaust manifold. The estimation algorithm requires prediction of the exhaust manifold's input and output flows. The input flow is predicted by a nonlinear Luenberger observer which is analytically...
Ricci-based chaos analysis for roto-translatory motion of a Kelvin-type gyrostat satellite
, Article Proceedings of the Institution of Mechanical Engineers, Part K: Journal of Multi-body Dynamics ; Vol. 228, issue. 1 , 2014 , pp. 34-46 ; ISSN: 14644193 ; Sadati, S. H ; Salarieh, H ; Sharif University of Technology
Abstract
The chaotic dynamics of roto-translatory motion of a triaxial Kelvin-type gyrostat satellite under gravity gradient perturbations is considered. The Hamiltonian approach is used for modelling of the coupled spin-orbit equations of motion. The complex Hamiltonian of the system is reduced via the extended Deprit canonical transformation using the Serret- Andoyer variables. Therefore, this reduction leads to the derivation of the perturbation form of the Hamiltonian that can be used in the Ricci curvature criterion based on the Riemannian manifold geometry for the analysis of chaos phenomenon. The results obtained from Ricci method as well as the values from the Lyapunov exponent demonstrate...
An efficient inference in meanfield approximation by adaptive manifold filtering: (Machine learning & data mining)
, Article Proceedings of the 4th International Conference on Computer and Knowledge Engineering, ICCKE 2014 ; 2014 , p. 581-585 ; Ramezanpur, S ; Kasaei, S ; Sanaei, E ; Sharif University of Technology
Abstract
A new method for speeding up the approximate maximum posterior marginal (MPM) inference in meanfield approximation of a fully connected graph is introduced. Weight of graph edges is measured by mixture of Gaussian kernels. This fully connected graph is used for segmentation of image data. The bottleneck of the inference in meanfield approximation is where the similar bilateral filtering is needed for updating the marginal in the message passing step. To speed up the inference, the adaptive manifold high dimensional Gaussian filter is used. As its time complexity is 0(ND), it leads to accelerating the marginal update in the message passing step. Its time complexity is linear and relative to...
Multiple metric learning for graph based human pose estimation
, Article Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Daegu, Korea ; Volume 8228 LNCS, Issue PART 3 , November , 2013 , Pages 200-208 ; 03029743 (ISSN) ; 9783642420504 (ISBN) ; Gozlou, M. G ; Shalmani, M. T. M ; Sharif University of Technology
2013
Abstract
In this paper, a multiple metric learning scheme for human pose estimation from a single image is proposed. Here, we focused on a big challenge of this problem which is; different 3D poses might correspond to similar inputs. To address this ambiguity, some Euclidean distance based approaches use prior knowledge or pose model that can work properly, provided that the model parameters are being estimated accurately. In the proposed method, the manifold of data is divided into several clusters and then, we learn a new metric for each partition by utilizing not only input features, but also their corresponding poses. The manifold clustering allows the decomposition of multiple manifolds into a...
On-line fault detection and isolation (FDI) for the exhaust path of a turbocharged SI engine
, Article ASME 2013 Dynamic Systems and Control Conference, DSCC 2013 ; Volume 1 , 2013 ; 9780791856123 (ISBN) ; Shahbakhti, M ; Alasty, A ; Vossoughi, G ; Sharif University of Technology
2013
Abstract
Detection and isolation of faults in the exhaust gas path of a turbocharged spark ignition (SI) engine is an essential part of the engine control unit (ECU) strategies to minimize exhaust emission and ensure safe operation of a turbocharger. This paper proposes a novel physics-based strategy to detect and isolate an exhaust manifold leakage and a closed-stuck wastegate fault. The strategy is based on a globally optimal parameter estimation algorithm which detects an effective hole area in the exhaust manifold. The estimation algorithm requires prediction of the exhaust manifold's input and output flows. The input flow is predicted by a nonlinear Luenberger observer which is analytically...