790 research outputs found
Software Engineering and Complexity in Effective Algebraic Geometry
We introduce the notion of a robust parameterized arithmetic circuit for the
evaluation of algebraic families of multivariate polynomials. Based on this
notion, we present a computation model, adapted to Scientific Computing, which
captures all known branching parsimonious symbolic algorithms in effective
Algebraic Geometry. We justify this model by arguments from Software
Engineering. Finally we exhibit a class of simple elimination problems of
effective Algebraic Geometry which require exponential time to be solved by
branching parsimonious algorithms of our computation model.Comment: 70 pages. arXiv admin note: substantial text overlap with
arXiv:1201.434
Information Extraction and Modeling from Remote Sensing Images: Application to the Enhancement of Digital Elevation Models
To deal with high complexity data such as remote sensing images presenting metric resolution over large areas, an innovative, fast and robust image processing system is presented.
The modeling of increasing level of information is used to extract, represent and link image features to semantic content.
The potential of the proposed techniques is demonstrated with an application to enhance and regularize digital elevation models based on information collected from RS images
Degree-Driven Design of Geometric Algorithms for Point Location, Proximity, and Volume Calculation
Correct implementation of published geometric algorithms is surprisingly difficult. Geometric algorithms are often designed for Real-RAM, a computational model that provides arbitrary precision arithmetic operations at unit cost. Actual commodity hardware provides only finite precision and may result in arithmetic errors. While the errors may seem small, if ignored, they may cause incorrect branching, which may cause an implementation to reach an undefined state, produce erroneous output, or crash. In 1999 Liotta, Preparata and Tamassia proposed that in addition to considering the resources of time and space, an algorithm designer should also consider the arithmetic precision necessary to guarantee a correct implementation. They called this design technique degree-driven algorithm design. Designers who consider the time, space, and precision for a problem up-front arrive at new solutions, gain further insight, and find simpler representations. In this thesis, I show that degree-driven design supports the development of new and robust geometric algorithms. I demonstrate this claim via several new algorithms. For n point sites on a UxU grid I consider three problems. First, I show how to compute the nearest neighbor transform in O(U^2) expected time, O(U^2) space, and double precision. Second, I show how to create a data structure in O(n log Un) expected time, O(n) expected space, and triple precision that supports O(log n) time and double precision post-office queries. Third, I show how to compute the Gabriel graph in O(n^2) time, O(n^2) space and double precision. For computing volumes of CSG models, I describe a framework that uses a minimal set of predicates that use at most five-fold precision. The framework is over 500x faster and two orders of magnitude more accurate than a Monte Carlo volume calculation algorithm.Doctor of Philosoph
Theoretical Engineering and Satellite Comlink of a PTVD-SHAM System
This paper focuses on super helical memory system's design, 'Engineering,
Architectural and Satellite Communications' as a theoretical approach of an
invention-model to 'store time-data'. The current release entails three
concepts: 1- an in-depth theoretical physics engineering of the chip including
its, 2- architectural concept based on VLSI methods, and 3- the time-data
versus data-time algorithm. The 'Parallel Time Varying & Data Super-helical
Access Memory' (PTVD-SHAM), possesses a waterfall effect in its architecture
dealing with the process of voltage output-switch into diverse logic and
quantum states described as 'Boolean logic & image-logic', respectively.
Quantum dot computational methods are explained by utilizing coiled carbon
nanotubes (CCNTs) and CNT field effect transistors (CNFETs) in the chip's
architecture. Quantum confinement, categorized quantum well substrate, and
B-field flux involvements are discussed in theory. Multi-access of coherent
sequences of 'qubit addressing' in any magnitude, gained as pre-defined, here
e.g., the 'big O notation' asymptotically confined into singularity while
possessing a magnitude of 'infinity' for the orientation of array displacement.
Gaussian curvature of k(k<0) is debated in aim of specifying the
2D electron gas characteristics, data storage system for defining short and
long time cycles for different CCNT diameters where space-time continuum is
folded by chance for the particle. Precise pre/post data timing for, e.g.,
seismic waves before earthquake mantle-reach event occurrence, including time
varying self-clocking devices in diverse geographic locations for radar systems
is illustrated in the Subsections of the paper. The theoretical fabrication
process, electromigration between chip's components is discussed as well.Comment: 50 pages, 10 figures (3 multi-figures), 2 tables. v.1: 1 postulate
entailing hypothetical ideas, design and model on future technological
advances of PTVD-SHAM. The results of the previous paper [arXiv:0707.1151v6],
are extended in order to prove some introductory conjectures in theoretical
engineering advanced to architectural analysi
Exact Symbolic-Numeric Computation of Planar Algebraic Curves
We present a novel certified and complete algorithm to compute arrangements
of real planar algebraic curves. It provides a geometric-topological analysis
of the decomposition of the plane induced by a finite number of algebraic
curves in terms of a cylindrical algebraic decomposition. From a high-level
perspective, the overall method splits into two main subroutines, namely an
algorithm denoted Bisolve to isolate the real solutions of a zero-dimensional
bivariate system, and an algorithm denoted GeoTop to analyze a single algebraic
curve.
Compared to existing approaches based on elimination techniques, we
considerably improve the corresponding lifting steps in both subroutines. As a
result, generic position of the input system is never assumed, and thus our
algorithm never demands for any change of coordinates. In addition, we
significantly limit the types of involved exact operations, that is, we only
use resultant and gcd computations as purely symbolic operations. The latter
results are achieved by combining techniques from different fields such as
(modular) symbolic computation, numerical analysis and algebraic geometry.
We have implemented our algorithms as prototypical contributions to the
C++-project CGAL. They exploit graphics hardware to expedite the symbolic
computations. We have also compared our implementation with the current
reference implementations, that is, LGP and Maple's Isolate for polynomial
system solving, and CGAL's bivariate algebraic kernel for analyses and
arrangement computations of algebraic curves. For various series of challenging
instances, our exhaustive experiments show that the new implementations
outperform the existing ones.Comment: 46 pages, 4 figures, submitted to Special Issue of TCS on SNC 2011.
arXiv admin note: substantial text overlap with arXiv:1010.1386 and
arXiv:1103.469
Exact polynomial system solving for robust geometric computation
I describe an exact method for computing roots of a system of multivariate
polynomials with rational coefficients, called the rational univariate reduction. This
method enables performance of exact algebraic computation of coordinates of the
roots of polynomials. In computational geometry, curves, surfaces and points are described
as polynomials and their intersections. Thus, exact computation of the roots
of polynomials allows the development and implementation of robust geometric algorithms.
I describe applications in robust geometric modeling. In particular, I show
a new method, called numerical perturbation scheme, that can be used successfully
to detect and handle degenerate configurations appearing in boundary evaluation
problems. I develop a derandomized version of the algorithm for computing the rational
univariate reduction for a square system of multivariate polynomials and a
new algorithm for a non-square system. I show how to perform exact computation
over algebraic points obtained by the rational univariate reduction. I give a formal
description of numerical perturbation scheme and its implementation
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