Blind separation of convolutive mixtures based on second order and third order statistics

This paper addresses the problem of blind separation of linear convolutive mixtures. We first reformulate the problem into a blind separation of linear instantaneous mixtures, and then a statistical approach is applied to solve the reformulated problem. From the statistics of the mixtures, two kinds of matrix pencils are constructed to estimate the mixing matrix. The original sources are then separated with the estimated mixing matrix. For the purpose of computational efficiency and robustness, in the matrix pencil, one matrix is constructed from the second order statistics, and the other is constructed from the third order statistics. The proposed novel methods do not require the exact knowledge of the channel order. Simulation results show that the methods are robust and have good performance.published_or_final_versio

Quantum field tomography

We introduce the concept of quantum field tomography, the efficient and reliable reconstruction of unknown quantum fields based on data of correlation functions. At the basis of the analysis is the concept of continuous matrix product states, a complete set of variational states grasping states in quantum field theory. We innovate a practical method, making use of and developing tools in estimation theory used in the context of compressed sensing such as Prony methods and matrix pencils, allowing us to faithfully reconstruct quantum field states based on low-order correlation functions. In the absence of a phase reference, we highlight how specific higher order correlation functions can still be predicted. We exemplify the functioning of the approach by reconstructing randomised continuous matrix product states from their correlation data and study the robustness of the reconstruction for different noise models. We also apply the method to data generated by simulations based on continuous matrix product states and using the time-dependent variational principle. The presented approach is expected to open up a new window into experimentally studying continuous quantum systems, such as encountered in experiments with ultra-cold atoms on top of atom chips. By virtue of the analogy with the input-output formalism in quantum optics, it also allows for studying open quantum systems.Comment: 31 pages, 5 figures, minor change

Configurable Input Devices for 3D Interaction using Optical Tracking

Three-dimensional interaction with virtual objects is one of the aspects that needs to be addressed in order to increase the usability and usefulness of virtual reality. Human beings have difficulties understanding 3D spatial relationships and manipulating 3D user interfaces, which require the control of multiple degrees of freedom simultaneously. Conventional interaction paradigms known from the desktop computer, such as the use of interaction devices as the mouse and keyboard, may be insufficient or even inappropriate for 3D spatial interaction tasks. The aim of the research in this thesis is to develop the technology required to improve 3D user interaction. This can be accomplished by allowing interaction devices to be constructed such that their use is apparent from their structure, and by enabling efficient development of new input devices for 3D interaction. The driving vision in this thesis is that for effective and natural direct 3D interaction the structure of an interaction device should be specifically tuned to the interaction task. Two aspects play an important role in this vision. First, interaction devices should be structured such that interaction techniques are as direct and transparent as possible. Interaction techniques define the mapping between interaction task parameters and the degrees of freedom of interaction devices. Second, the underlying technology should enable developers to rapidly construct and evaluate new interaction devices. The thesis is organized as follows. In Chapter 2, a review of the optical tracking field is given. The tracking pipeline is discussed, existing methods are reviewed, and improvement opportunities are identified. In Chapters 3 and 4 the focus is on the development of optical tracking techniques of rigid objects. The goal of the tracking method presented in Chapter 3 is to reduce the occlusion problem. The method exploits projection invariant properties of line pencil markers, and the fact that line features only need to be partially visible. In Chapter 4, the aim is to develop a tracking system that supports devices of arbitrary shapes, and allows for rapid development of new interaction devices. The method is based on subgraph isomorphism to identify point clouds. To support the development of new devices in the virtual environment an automatic model estimation method is used. Chapter 5 provides an analysis of three optical tracking systems based on different principles. The first system is based on an optimization procedure that matches the 3D device model points to the 2D data points that are detected in the camera images. The other systems are the tracking methods as discussed in Chapters 3 and 4. In Chapter 6 an analysis of various filtering and prediction methods is given. These techniques can be used to make the tracking system more robust against noise, and to reduce the latency problem. Chapter 7 focusses on optical tracking of composite input devices, i.e., input devices 197 198 Summary that consist of multiple rigid parts that can have combinations of rotational and translational degrees of freedom with respect to each other. Techniques are developed to automatically generate a 3D model of a segmented input device from motion data, and to use this model to track the device. In Chapter 8, the presented techniques are combined to create a configurable input device, which supports direct and natural co-located interaction. In this chapter, the goal of the thesis is realized. The device can be configured such that its structure reflects the parameters of the interaction task. In Chapter 9, the configurable interaction device is used to study the influence of spatial device structure with respect to the interaction task at hand. The driving vision of this thesis, that the spatial structure of an interaction device should match that of the task, is analyzed and evaluated by performing a user study. The concepts and techniques developed in this thesis allow researchers to rapidly construct and apply new interaction devices for 3D interaction in virtual environments. Devices can be constructed such that their spatial structure reflects the 3D parameters of the interaction task at hand. The interaction technique then becomes a transparent one-to-one mapping that directly mediates the functions of the device to the task. The developed configurable interaction devices can be used to construct intuitive spatial interfaces, and allow researchers to rapidly evaluate new device configurations and to efficiently perform studies on the relation between the spatial structure of devices and the interaction task

Super Resolution of Wavelet-Encoded Images and Videos

In this dissertation, we address the multiframe super resolution reconstruction problem for wavelet-encoded images and videos. The goal of multiframe super resolution is to obtain one or more high resolution images by fusing a sequence of degraded or aliased low resolution images of the same scene. Since the low resolution images may be unaligned, a registration step is required before super resolution reconstruction. Therefore, we first explore in-band (i.e. in the wavelet-domain) image registration; then, investigate super resolution. Our motivation for analyzing the image registration and super resolution problems in the wavelet domain is the growing trend in wavelet-encoded imaging, and wavelet-encoding for image/video compression. Due to drawbacks of widely used discrete cosine transform in image and video compression, a considerable amount of literature is devoted to wavelet-based methods. However, since wavelets are shift-variant, existing methods cannot utilize wavelet subbands efficiently. In order to overcome this drawback, we establish and explore the direct relationship between the subbands under a translational shift, for image registration and super resolution. We then employ our devised in-band methodology, in a motion compensated video compression framework, to demonstrate the effective usage of wavelet subbands. Super resolution can also be used as a post-processing step in video compression in order to decrease the size of the video files to be compressed, with downsampling added as a pre-processing step. Therefore, we present a video compression scheme that utilizes super resolution to reconstruct the high frequency information lost during downsampling. In addition, super resolution is a crucial post-processing step for satellite imagery, due to the fact that it is hard to update imaging devices after a satellite is launched. Thus, we also demonstrate the usage of our devised methods in enhancing resolution of pansharpened multispectral images

Entropy of partially polarized light and application to statistical processing techniques

International audienceWe have analyzed entropy properties of coherent and partially polarized light in an arbitrary number of spatial dimensions. We show that for Gaussian fields, the Shannon entropy is a simple function of the intensity and of the Barakat degree of polarization. In particular, we provide a probabilistic interpretation of this definition of the degree of polarization. Using information theory results, we also deduce some physical properties of partially polarized light such as additivity of the entropy and depolarization effects induced by mixing partially polarized states of light. Finally, we demonstrate that entropy measures can play an important role in segmentation and detection task

Service Offshoring and White-Collar Employment

I study the effects of service offshoring on white-collar employment, using highly disaggregated occupational data for the U.S.. I present a structural model of the firm’s behavior that allows tractable derivation of labor demand elasticities for highly detailed occupations. I estimate the model using Quasi-Maximum Likelihood, to simultaneously account for the high degree of censoring of the employment variable and the small cross-sectional dimension of the panel. I find that service offshoring is skill-biased, because it raises employment among high-skilled occupations and lowers employment among medium- and low-skilled ones. Within each skill group, service offshoring penalizes tradeable occupations and tends to benefit complex non tradeable jobs.service offshoring, white-collar occupations, labor demand elasticities, homothetic weak separability, censored demand system estimation

Temporary Trade

Most trade theories assume bilateral trade relationships are forged on the basis of some comparative advantages, scale considerations, market structure or some productivity advantage of firms. Since these factors change slowly, bilateral trade relationships should be stable. However, we argue that over half of the non-zero bilateral trade relationships are of temporary nature: they last for a short period only or appear and disappear in an erratic fashion. With a very detailed country-product transaction level dataset on Hungarian exports, evidence is provided for the importance of temporary trade relationships at the bilateral level. A large share of bilateral trade flows are driven by just a few firms, and results indicate that temporary trade is important for all kinds of firms and products. In terms of empirical applications, we show that gravity equations suggest important differences between the determinants of permanent and temporary trade; and the extensive and intensive margins of trade can also be very sensitive to changes in temporary trade.international trade, duration of trade, firm-product level data

Eigenvector-based multidimensional frequency estimation : identifiability, performance, and applications.

Multidimensional frequency estimation is a classic signal processing problem that has versatile applications in sensor array processing and wireless communications. Eigenvalue-based two-dimensional (2-D) and N -dimensional ( N -D) frequency estimation algorithms have been well documented, however, these algorithms suffer from limited identifiability and demanding computations. This dissertation develops a framework on eigenvector-based N -D frequency estimation, which contains several novel algorithms that estimate a structural matrix from eigenvectors and then resolve the N -D frequencies by dividing the elements of the structural matrix. Compared to the existing eigenvalue-based algorithms, these eigenvector-based algorithms can achieve automatic pairing without an extra frequency pairing step, and tins the computational complexity is reduced. The identifiability, performance, and complexity of these algorithms are also systematically studied. Based on this study, the most relaxed identifiability condition for the N -D frequency estimation problem is given and an effective approach using optimized weighting factors to improve the performance of frequency estimation is developed. These results are applied in wireless communication for time-varying multipath channel estimation and prediction, as well as for joint 2-D Direction-of-arrival (DOA) tracking of multiple moving targets

Single-ensemble-based eigen-processing methods for color flow imaging-Part II. the matrix pencil estimator

Parametric spectral estimators can potentially be used to obtain flow estimates directly from raw slow-time ensembles whose clutter has not been suppressed. We present a new eigen-based parametric flow estimation method called the matrix pencil, whose principles are based on a matrix form under the same name. The presented method models the slow-time signal as a sum of dominant complex sinusoids in the slow-time ensemble, and it computes the principal Doppler frequencies by using a generalized eigenvalue problem formulation and matrix rank reduction principles. Both fixed-rank (rank-one, rank-two) and adaptive-rank matrix pencil flow estimators are proposed, and their potential applicability to color flow signal processing is discussed. For the adaptive-rank estimator, the nominal rank was defined as the minimum eigen-structure rank that yields principal frequency estimates with a spread greater than a prescribed bandwidth. In our initial performance evaluation, the fixed-rank matrix pencil estimators were applied to raw color flow data (transmit frequency: 5 MHz; pulse repetition period: 0.175 ms; ensemble size: 14) acquired from a steady flow phantom (70 cm/s at centerline) that was surrounded by rigid-tissue-mimicking material. These fixed-rank estimators produced velocity maps that are well correlated with the theoretical flow profile (correlation coefficient: 0.964 to 0.975). To facilitate further evaluation, the matrix pencil estimators were applied to synthetic slow-time data (transmit frequency: 5 MHz; pulse repetition period: 1.0 ms; ensemble size: 10) modeling flow scenarios without and with tissue motion (up to 1 cm/s). The bias and root-mean-squared error of the estimators were computed as a function of blood-signal-to-noise ratio and blood velocity. The matrix pencil flow estimators showed that they are comparatively less biased than most of the existing frequency-based flow estimators like the lag-one autocorrelator. © 2006 IEEE.published_or_final_versio

Multivariate NIR studies of seed-water interaction in Scots Pine Seeds (Pinus sylvestris L.)

This thesis describes seed-water interaction using near infrared (NIR) spectroscopy, multivariate regression models and Scots pine seeds. The presented research covers classification of seed viability, prediction of seed moisture content, selection of NIR wavelengths and interpretation of seed-water interaction modelled and analysed by principal component analysis, ordinary least squares (OLS), partial least squares (PLS), bi-orthogonal least squares (BPLS) and genetic algorithms. The potential of using multivariate NIR calibration models for seed classification was demonstrated using filled viable and non-viable seeds that could be separated with an accuracy of 98-99%. It was also shown that multivariate NIR calibration models gave low errors (0.7% and 1.9%) in prediction of seed moisture content for bulk seed and single seeds, respectively, using either NIR reflectance or transmittance spectroscopy. Genetic algorithms selected three to eight wavelength bands in the NIR region and these narrow bands gave about the same prediction of seed moisture content (0.6% and 1.7%) as using the whole NIR interval in the PLS regression models. The selected regions were simulated as NIR filters in OLS regression resulting in predictions of the same quality (0.7 % and 2.1%). This finding opens possibilities to apply NIR sensors in fast and simple spectrometers for the determination of seed moisture content. Near infrared (NIR) radiation interacts with overtones of vibrating bonds in polar molecules. The resulting spectra contain chemical and physical information. This offers good possibilities to measure seed-water interactions, but also to interpret processes within seeds. It is shown that seed-water interaction involves both transitions and changes mainly in covalent bonds of O-H, C-H, C=O and N-H emanating from ongoing physiological processes like seed respiration and protein metabolism. I propose that BPLS analysis that has orthonormal loadings and orthogonal scores giving the same predictions as using conventional PLS regression, should be used as a standard to harmonise the interpretation of NIR spectra