Rostami Mohammad (68 results)

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Paperback. Condition: new. Paperback. This book discusses compressive sensing in the presence of side information. Compressive sensing is an emerging technique for efficiently acquiring and reconstructing a signal. Interesting instances of Compressive Sensing (CS) can occur when, apart from sparsity, side information is available about the source signals. The side information can be about the source structure, distribution, etc. Such cases can be viewed as extensions of the classical CS. In these cases we are interested in incorporating the side information to either improve the quality of the source reconstruction or decrease the number of samples required for accurate reconstruction. In this book we assume availability of side information about the feasible region. The main applications investigated are image deblurring for optical imaging, 3D surface reconstruction, and reconstructing spatiotemporally correlated sources. The author shows that the side information can be used to improve the quality of the reconstruction compared to the classic compressive sensing. The book will be of interest to all researchers working on compressive sensing, inverse problems, and image processing. This book discusses compressive sensing in the presence of side information. Interesting instances of Compressive Sensing (CS) can occur when, apart from sparsity, side information is available about the source signals. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Paperback. Condition: New. Mixed-matrix membranes are identified as a new type of membranes being more efficient due to the inorganic particles in their structure. In industry they can be a good substitute for old methods which consume a lot of energy. Thus, the present research scrutinizes different filling particles used in this group of membranes, applications, shortcomings and the challenges of producing these types of membranes. This book explains the key parameters in the fabrication methods through blending of polymeric and non-polymeric materials containing different components in their chemical structures. It is a complete overview of all relevant and similar references in the field of membrane technology in oil, gas and petrochemicals, by considering standards and the way of performing separation techniques and implementing projects.

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Paperback. Condition: Brand New. 2013 edition. 69 pages. 9.00x6.00x0.25 inches. In Stock.

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Taschenbuch. Condition: Neu. Neuware -Solving problems originating from real-world applications is often based on the solution of a system of linear equations whose coefficient matrix is a large sparse Jacobian matrix. Hence, there is research to exploit the sparsity structure and to decrease the amount of storage. In contrast to full Jacobian computation in which all nonzero elements are to be determined, partial Jacobian computation is looking at a subset of these elements. Partial Jacobian computation can therefore be faster and more efficient than full Jacobian computation. Since Jacobian matrix-vector products are needed in iterative solvers, these types of linear systems can be efficiently solved using automatic differentiation. Determining these nonzero elements in full or partial Jacobian computations by automatic differentiation techniques can be modeled as graph coloring in the language of graph theory. On the other hand, preconditioning techniques are used to improve the convergence of iterative solvers and typically need access to all nonzero elements of the Jacobian matrix. So, a sparsification is applied to the Jacobian matrix before computing the preconditioner. In the second part of this thesis, we introduce a collection of interactive educational modules to teach not only graph coloring, but also other concepts from combinatorial scientific computing in the classroom. These modules are designed to involve the students more thoroughly in the process of learning.Books on Demand GmbH, Überseering 33, 22297 Hamburg 104 pp. Deutsch.

Paperback. Condition: New. Mixed-matrix membranes are identified as a new type of membranes being more efficient due to the inorganic particles in their structure. In industry they can be a good substitute for old methods which consume a lot of energy. Thus, the present research scrutinizes different filling particles used in this group of membranes, applications, shortcomings and the challenges of producing these types of membranes. This book explains the key parameters in the fabrication methods through blending of polymeric and non-polymeric materials containing different components in their chemical structures. It is a complete overview of all relevant and similar references in the field of membrane technology in oil, gas and petrochemicals, by considering standards and the way of performing separation techniques and implementing projects.

Condition: New. Vahid Pirouzfar earned his PhD degree in Chemical Process Engineering, process design, simulation and control from Tarbiat Modares University. He has been working as a faculty member at the IAU since 2011, and currently he is a faculty member and associ.

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Taschenbuch. Condition: Neu. Neuware -This book discusses compressive sensing in the presence of side information. Compressive sensing is an emerging technique for efficiently acquiring and reconstructing a signal. Interesting instances of Compressive Sensing (CS) can occur when, apart from sparsity, side information is available about the source signals. The side information can be about the source structure, distribution, etc. Such cases can be viewed as extensions of the classical CS. Inthese cases we are interested in incorporating the side information to either improve the quality of the source reconstruction or decrease the number of samples required for accurate reconstruction. In this book we assume availability of side information about the feasible region. The main applications investigated are image deblurring for optical imaging, 3D surface reconstruction, and reconstructing spatiotemporally correlated sources. The author shows that the side information can be used to improve the quality of the reconstruction compared to the classic compressive sensing. The book will be of interest to all researchers working on compressive sensing, inverse problems, and image processing.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 84 pp. Englisch.

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book discusses compressive sensing in the presence of side information. Compressive sensing is an emerging technique for efficiently acquiring and reconstructing a signal. Interesting instances of Compressive Sensing (CS) can occur when, apart from sparsity, side information is available about the source signals. The side information can be about the source structure, distribution, etc. Such cases can be viewed as extensions of the classical CS. In these cases we are interested in incorporating the side information to either improve the quality of the source reconstruction or decrease the number of samples required for accurate reconstruction. In this book we assume availability of side information about the feasible region. The main applications investigated are image deblurring for optical imaging, 3D surface reconstruction, and reconstructing spatiotemporally correlated sources. The author shows that the side information can be used to improve the quality of the reconstruction compared to the classic compressive sensing. The book will be of interest to all researchers working on compressive sensing, inverse problems, and image processing.

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Condition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | This book discusses compressive sensing in the presence of side information. Compressive sensing is an emerging technique for efficiently acquiring and reconstructing a signal. Interesting instances of Compressive Sensing (CS) can occur when, apart from sparsity, side information is available about the source signals. The side information can be about the source structure, distribution, etc. Such cases can be viewed as extensions of the classical CS. In these cases we are interested in incorporating the side information to either improve the quality of the source reconstruction or decrease the number of samples required for accurate reconstruction. In this book we assume availability of side information about the feasible region. The main applications investigated are image deblurring for optical imaging, 3D surface reconstruction, and reconstructing spatiotemporally correlated sources. The author shows that the side information can be used to improve the quality of the reconstruction compared to the classic compressive sensing. The book will be of interest to all researchers working on compressive sensing, inverse problems, and image processing.

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Paperback. Condition: new. Paperback. This book discusses compressive sensing in the presence of side information. Compressive sensing is an emerging technique for efficiently acquiring and reconstructing a signal. Interesting instances of Compressive Sensing (CS) can occur when, apart from sparsity, side information is available about the source signals. The side information can be about the source structure, distribution, etc. Such cases can be viewed as extensions of the classical CS. In these cases we are interested in incorporating the side information to either improve the quality of the source reconstruction or decrease the number of samples required for accurate reconstruction. In this book we assume availability of side information about the feasible region. The main applications investigated are image deblurring for optical imaging, 3D surface reconstruction, and reconstructing spatiotemporally correlated sources. The author shows that the side information can be used to improve the quality of the reconstruction compared to the classic compressive sensing. The book will be of interest to all researchers working on compressive sensing, inverse problems, and image processing. This book discusses compressive sensing in the presence of side information. Interesting instances of Compressive Sensing (CS) can occur when, apart from sparsity, side information is available about the source signals. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

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