7,178 research outputs found
Multidimensional Binary Vector Assignment problem: standard, structural and above guarantee parameterizations
In this article we focus on the parameterized complexity of the
Multidimensional Binary Vector Assignment problem (called \BVA). An input of
this problem is defined by disjoint sets , each
composed of binary vectors of size . An output is a set of disjoint
-tuples of vectors, where each -tuple is obtained by picking one vector
from each set . To each -tuple we associate a dimensional vector by
applying the bit-wise AND operation on the vectors of the tuple. The
objective is to minimize the total number of zeros in these vectors. mBVA
can be seen as a variant of multidimensional matching where hyperedges are
implicitly locally encoded via labels attached to vertices, but was originally
introduced in the context of integrated circuit manufacturing.
We provide for this problem FPT algorithms and negative results (-based
results, [2]-hardness and a kernel lower bound) according to several
parameters: the standard parameter i.e. the total number of zeros), as well
as two parameters above some guaranteed values.Comment: 16 pages, 6 figure
Parameter Identification of Pressure Sensors by Static and Dynamic Measurements
Fast identification methods of pressure sensors are investigated. With regard
to a complete accurate sensor parameter identification two different
measurement methods are combined. The approach consists on one hand in
performing static measurements - an applied pressure results in a membrane
deformation measured interferometrically and the corresponding output voltage.
On the other hand optical measurements of the modal responses of the sensor
membranes are performed. This information is used in an inverse identification
algorithm to identify geometrical and material parameters based on a FE model.
The number of parameters to be identified is thereby generally limited only by
the number of measurable modal frequencies. A quantitative evaluation of the
identification results permits furthermore the classification of processing
errors like etching errors. Algorithms and identification results for membrane
thickness, intrinsic stress and output voltage will be discussed in this
contribution on the basis of the parameter identification of relative pressure
sensors.Comment: Submitted on behalf of EDA Publishing Association
(http://irevues.inist.fr/EDA-Publishing
Tensor Computation: A New Framework for High-Dimensional Problems in EDA
Many critical EDA problems suffer from the curse of dimensionality, i.e. the
very fast-scaling computational burden produced by large number of parameters
and/or unknown variables. This phenomenon may be caused by multiple spatial or
temporal factors (e.g. 3-D field solvers discretizations and multi-rate circuit
simulation), nonlinearity of devices and circuits, large number of design or
optimization parameters (e.g. full-chip routing/placement and circuit sizing),
or extensive process variations (e.g. variability/reliability analysis and
design for manufacturability). The computational challenges generated by such
high dimensional problems are generally hard to handle efficiently with
traditional EDA core algorithms that are based on matrix and vector
computation. This paper presents "tensor computation" as an alternative general
framework for the development of efficient EDA algorithms and tools. A tensor
is a high-dimensional generalization of a matrix and a vector, and is a natural
choice for both storing and solving efficiently high-dimensional EDA problems.
This paper gives a basic tutorial on tensors, demonstrates some recent examples
of EDA applications (e.g., nonlinear circuit modeling and high-dimensional
uncertainty quantification), and suggests further open EDA problems where the
use of tensor computation could be of advantage.Comment: 14 figures. Accepted by IEEE Trans. CAD of Integrated Circuits and
System
Learning for Advanced Motion Control
Iterative Learning Control (ILC) can achieve perfect tracking performance for
mechatronic systems. The aim of this paper is to present an ILC design tutorial
for industrial mechatronic systems. First, a preliminary analysis reveals the
potential performance improvement of ILC prior to its actual implementation.
Second, a frequency domain approach is presented, where fast learning is
achieved through noncausal model inversion, and safe and robust learning is
achieved by employing a contraction mapping theorem in conjunction with
nonparametric frequency response functions. The approach is demonstrated on a
desktop printer. Finally, a detailed analysis of industrial motion systems
leads to several shortcomings that obstruct the widespread implementation of
ILC algorithms. An overview of recently developed algorithms, including
extensions using machine learning algorithms, is outlined that are aimed to
facilitate broad industrial deployment.Comment: 8 pages, 15 figures, IEEE 16th International Workshop on Advanced
Motion Control, 202
Impact of parameter variations on circuits and microarchitecture
Parameter variations, which are increasing along with advances in process technologies, affect both timing and power. Variability must be considered at both the circuit and microarchitectural design levels to keep pace with performance scaling and to keep power consumption within reasonable limits. This article presents an overview of the main sources of variability and surveys variation-tolerant circuit and microarchitectural approaches.Peer ReviewedPostprint (published version
Radiation effects studies for the high-resolution spectrograph
The generation and collection of charge carriers created during the passage of energetic protons through a silicon photodiode array are modeled. Pulse height distributions of noise charge collected during exposure of a digicon type diode array to 21 and 75 MeV protons were obtained. The magnitude of charge collected by a diode from each proton event is determined not only by diffusion, but by statistical considerations involving the ionization process itself. Utilizing analytical solutions to the diffusion equation for transport of minority carriers, together with the Vavilov theory of energy loss fluctuations in thin absorbers, simulations of the pulse height spectra which follow the experimental distributions fairly well are presented and an estimate for the minority carrier diffusion length L sub d is provided
Technical Design Report for the PANDA Micro Vertex Detector
This document illustrates the technical layout and the expected performance of the Micro Vertex Detector (MVD) of the PANDA experiment. The MVD will detect charged particles as close as possible to the interaction zone. Design criteria and the optimisation process as well as the technical solutions chosen are discussed and the results of this process are subjected to extensive Monte Carlo physics studies. The route towards realisation of the detector is
outlined
A review of advances in pixel detectors for experiments with high rate and radiation
The Large Hadron Collider (LHC) experiments ATLAS and CMS have established
hybrid pixel detectors as the instrument of choice for particle tracking and
vertexing in high rate and radiation environments, as they operate close to the
LHC interaction points. With the High Luminosity-LHC upgrade now in sight, for
which the tracking detectors will be completely replaced, new generations of
pixel detectors are being devised. They have to address enormous challenges in
terms of data throughput and radiation levels, ionizing and non-ionizing, that
harm the sensing and readout parts of pixel detectors alike. Advances in
microelectronics and microprocessing technologies now enable large scale
detector designs with unprecedented performance in measurement precision (space
and time), radiation hard sensors and readout chips, hybridization techniques,
lightweight supports, and fully monolithic approaches to meet these challenges.
This paper reviews the world-wide effort on these developments.Comment: 84 pages with 46 figures. Review article.For submission to Rep. Prog.
Phy
Terahertz dynamic aperture imaging at stand-off distances using a Compressed Sensing protocol
In this text, results of a 0.35 terahertz (THz) dynamic aperture imaging
approach are presented. The experiments use an optical modulation approach and
a single pixel detector at a stand-off imaging distance of approx 1 meter. The
optical modulation creates dynamic apertures of 5cm diameter with approx 2000
individually controllable elements. An optical modulation approach is used here
for the first time at a large far-field distance, for the investigation of
various test targets in a field-of-view of 8 x 8 cm. The results highlight the
versatility of this modulation technique and show that this imaging paradigm is
applicable even at large far-field distances. It proves the feasibility of this
imaging approach for potential applications like stand-off security imaging or
far field THz microscopy.Comment: 9 pages, 13 figure
- …