868 resultados para Subspace Filter Diagonalization


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Das Ziel der vorliegenden Arbeit war die Herstellung und Charakterisierung mikromechanisch durchstimmbarer, dielektrischer Fabry-Pérot-Filter im nahen Infrarot-Bereich bei einer Zentralwellenlänge von λc = 950 nm. Diese Bauelemente wurden auf Basis kostengünstiger Technologien realisiert, dank deren Entwicklung extreme Miniaturisierung und gleichzeitig hohe spektrale Anforderungen möglich sind. Der Vorteil solcher Filter liegt darin, dass sie direkt in einen Photodetektor integriert werden können und mit ganz wenigen Komponenten zu einem kompakten Spektrometermodul zusammengesetzt werden können. Die Baugröße ist nur durch die Größe des Photodetektors limitiert und die gesamte Intensität des einfallenden Lichts kann vorteilhaft auf eine einzelne Filtermembran des Fabry-Pérot-Filters fokussiert werden. Für den Filteraufbau werden zwei hochreflektierende, dielektrische DBR-Spiegel, ein organisches Opferschichtmaterial, welches zur Erzeugung einer Luftkavität im Filter dient, und zwei unterschiedliche Elektroden aus ITO und Aluminium verwendet. Die mikromechanische Auslenkung der freigelegten Filtermembran geschieht mittels elektrostatischer Aktuation, wobei auf diese Weise die Kavitätshöhe des Fabry-Pérot-Filters geändert wird und somit dieser im erforderlichen Spektralbereich optisch durchgestimmt wird. Das in dieser Arbeit gewählte Filterkonzept stellt eine Weiterentwicklung eines bereits bestehenden Filterkonzepts für den sichtbaren Spektralbereich dar. Zum Einen wurden in dieser Arbeit das vertikale und das laterale Design der Filterstrukturen geändert. Eine entscheidende Änderung lag im mikromechanisch beweglichen Teil des Fabry-Pérot-Filters. Dieser schließt den oberen DBR-Spiegel und ein aus dielektrischen Schichten und der oberen Aluminium-Elektrode bestehendes Membranhaltesystem ein, welches später durch Entfernung der Opferschicht freigelegt wird. Die Fläche des DBR-Spiegels wurde auf die Fläche der Filtermembran reduziert und auf dem Membranhaltesystem positioniert. Zum Anderen wurde im Rahmen dieser Arbeit der vertikale Schichtaufbau des Membranhaltesystems variiert und der Einfluss der gewählten Materialien auf die Krümmung der freistehenden Filterstrukturen, auf das Aktuationsverhalten und auf die spektralen Eigenschaften des gesamten Filters untersucht. Der Einfluss der mechanischen Eigenschaften dieser Materialien spielt nämlich eine bedeutende Rolle bei der Erhaltung der erforderlichen optischen Eigenschaften des gesamten Filters. Bevor Fabry-Pérot-Filter ausgeführt wurden, wurde die mechanische Spannung in den einzelnen Materialien des Membranhaltesystems bestimmt. Für die Messung wurde Substratkrümmungsmethode angewendet. Es wurde gezeigt, dass die Plasmaanregungsfrequenzen der plasmaunterstützten chemischen Gasphasenabscheidung bei einer Prozesstemperatur von 120 °C die mechanische Spannung von Si3N4 enorm beeinflussen. Diese Ergebnisse wurden im Membranhaltesystem umgesetzt, wobei verschiedene Filter mit unterschiedlichen mechanischen Eigenschaften des Membranhaltesystems gezeigt wurden. Darüber hinaus wurden optische Eigenschaften der Filter unter dem Einfluss des lateralen Designs der Filterstrukturen untersucht. Bei den realisierten Filtern wurden ein optischer Durchstimmbereich von ca. 70 nm und eine spektrale Auflösung von 5 nm erreicht. Die erreichte Intensität der Transmissionslinie liegt bei 45-60%. Diese Parameter haben für den späteren spektroskopischen Einsatz der realisierten Fabry-Pérot-Filter eine hohe Bedeutung. Die Anwendung soll erstmalig in einem „Proof of Concept“ stattfinden, wobei damit die Oberflächentemperatur eines GaAs-Wafers über die Messung der spektralen Lage seiner Bandlücke bestimmt werden kann.

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The accuracy of a 3D reconstruction using laser scanners is significantly determined by the detection of the laser stripe. Since the energy pattern of such a stripe corresponds to a Gaussian profile, it makes sense to detect the point of maximum light intensity (or peak) by computing the zero-crossing point of the first derivative of such Gaussian profile. However, because noise is present in every physical process, such as electronic image formation, it is not sensitive to perform the derivative of the image of the stripe in almost any situation, unless a previous filtering stage is done. Considering that stripe scanning is an inherently row-parallel process, every row of a given image must be processed independently in order to compute its corresponding peak position in the row. This paper reports on the use of digital filtering techniques in order to cope with the scanning of different surfaces with different optical properties and different noise levels, leading to the proposal of a more accurate numerical peak detector, even at very low signal-to-noise ratios

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This paper reviews a study to investigate how a hearing impaired person can learn to discriminate speech distorted by a low pass filter in a sensory aid.

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This paper reviews a study to investigate how a hearing impaired person can learn to discriminate speech distorted by a low pass filter in a sensory aid.

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The motion of a car is described using a stochastic model in which the driving processes are the steering angle and the tangential acceleration. The model incorporates exactly the kinematic constraint that the wheels do not slip sideways. Two filters based on this model have been implemented, namely the standard EKF, and a new filter (the CUF) in which the expectation and the covariance of the system state are propagated accurately. Experiments show that i) the CUF is better than the EKF at predicting future positions of the car; and ii) the filter outputs can be used to control the measurement process, leading to improved ability to recover from errors in predictive tracking.

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A driver controls a car by turning the steering wheel or by pressing on the accelerator or the brake. These actions are modelled by Gaussian processes, leading to a stochastic model for the motion of the car. The stochastic model is the basis of a new filter for tracking and predicting the motion of the car, using measurements obtained by fitting a rigid 3D model to a monocular sequence of video images. Experiments show that the filter easily outperforms traditional filters.

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We have developed an ensemble Kalman Filter (EnKF) to estimate 8-day regional surface fluxes of CO2 from space-borne CO2 dry-air mole fraction observations (XCO2) and evaluate the approach using a series of synthetic experiments, in preparation for data from the NASA Orbiting Carbon Observatory (OCO). The 32-day duty cycle of OCO alternates every 16 days between nadir and glint measurements of backscattered solar radiation at short-wave infrared wavelengths. The EnKF uses an ensemble of states to represent the error covariances to estimate 8-day CO2 surface fluxes over 144 geographical regions. We use a 12×8-day lag window, recognising that XCO2 measurements include surface flux information from prior time windows. The observation operator that relates surface CO2 fluxes to atmospheric distributions of XCO2 includes: a) the GEOS-Chem transport model that relates surface fluxes to global 3-D distributions of CO2 concentrations, which are sampled at the time and location of OCO measurements that are cloud-free and have aerosol optical depths <0.3; and b) scene-dependent averaging kernels that relate the CO2 profiles to XCO2, accounting for differences between nadir and glint measurements, and the associated scene-dependent observation errors. We show that OCO XCO2 measurements significantly reduce the uncertainties of surface CO2 flux estimates. Glint measurements are generally better at constraining ocean CO2 flux estimates. Nadir XCO2 measurements over the terrestrial tropics are sparse throughout the year because of either clouds or smoke. Glint measurements provide the most effective constraint for estimating tropical terrestrial CO2 fluxes by accurately sampling fresh continental outflow over neighbouring oceans. We also present results from sensitivity experiments that investigate how flux estimates change with 1) bias and unbiased errors, 2) alternative duty cycles, 3) measurement density and correlations, 4) the spatial resolution of estimated flux estimates, and 5) reducing the length of the lag window and the size of the ensemble. At the revision stage of this manuscript, the OCO instrument failed to reach its orbit after it was launched on 24 February 2009. The EnKF formulation presented here is also applicable to GOSAT measurements of CO2 and CH4.

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The Robert–Asselin time filter is widely used in numerical models of weather and climate. It successfully suppresses the spurious computational mode associated with the leapfrog time-stepping scheme. Unfortunately, it also weakly suppresses the physical mode and severely degrades the numerical accuracy. These two concomitant problems are shown to occur because the filter does not conserve the mean state, averaged over the three time slices on which it operates. The author proposes a simple modification to the Robert–Asselin filter, which does conserve the three-time-level mean state. When used in conjunction with the leapfrog scheme, the modification vastly reduces the impacts on the physical mode and increases the numerical accuracy for amplitude errors by two orders, yielding third-order accuracy. The modified filter could easily be incorporated into existing general circulation models of the atmosphere and ocean. In principle, it should deliver more faithful simulations at almost no additional computational expense. Alternatively, it may permit the use of longer time steps with no loss of accuracy, reducing the computational expense of a given simulation.

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Following an introduction to the diagonalization of matrices, one of the more difficult topics for students to grasp in linear algebra is the concept of Jordan normal form. In this note, we show how the important notions of diagonalization and Jordan normal form can be introduced and developed through the use of the computer algebra package Maple®.

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We have favoured the variational (secular equation) method for the determination of the (ro-) vibrational energy levels of polyatomic molecules. We use predominantly the Watson Hamiltonian in normal coordinates and an associated given potential in the variational code 'Multimode'. The dominant cost is the construction and diagonalization of matrices of ever-increasing size. Here we address this problem, using pertubation theory to select dominant expansion terms within the Davidson-Liu iterative diagonalization method. Our chosen example is the twelve-mode molecule methanol, for which we have an ab initio representation of the potential which includes the internal rotational motion of the OH group relative to CH3. Our new algorithm allows us to obtain converged energy levels for matrices of dimensions in excess of 100 000.

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The results from a range of different signal processing schemes used for the further processing of THz transients are contrasted. The performance of different classifiers after adopting these schemes are also discussed.

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This paper describes the integration of an Utkin observer with the unscented Kalman filter, investigates the performance of the combined observer, termed the unscented Utkin observer, and compares it with an unscented Kalman filter. Simulation tests are performed using a model of a single link robot arm with a revolute elastic joint rotating in a vertical plane. The results indicate that the unscented Utkin observer outperforms the unscented Kalman filter.