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In this work, we propose a novel multi-pitch estimation technique that is robust with respect to the inharmonicity commonly occurring in many applications. The method does not require any a priori knowledge of the number of signal sources, the number of harmonics of each source, nor the structure or scope of any possibly occurring inharmonicity. Formulated as a minimum transport distance problem,
This paper proposes an iterative algorithm to reconstruct missing samples from non-stationary signals. The proposed algorithm is based on the well-known amplitude-modulation frequency-modulation model for non-stationary signals. The method initially estimates the instantaneous frequencies of the observed multi-component signal. The estimated IFs are then used to de-chirp the corresponding componen
We use a variational approach to find the best constants for certain Gagliardo-Nirenberg inequalities on the real line. To show the existence of a minimizer, we use the method of concentration-compactness.
This report titled Best available technologies and techniques for large point sources has been prepared within the framework of the programme on Regional Air Pollution in Developing Countries (RAPIDC), Phase III conducted during the period 2005-2008. RAPIDC is funded by the Department of Infrastructure and Economic Cooperation (INEC) of the Swedish International Development Cooperation Agency SIDA
We apply the statistical sparse jump model, a recently devel-oped, interpretable and robust regime switching model, to infer key featuresthat drive the return dynamics of the largest cryptocurrencies. The algorithmjointly performs feature selection, parameter estimation, and state classifica-tion. Our large set of candidate features are partly based on cryptocurrency,sentiment and financial market We apply the statistical sparse jump model, a recently devel-oped, interpretable and robust regime switching model, to infer key featuresthat drive the return dynamics of the largest cryptocurrencies. The algorithmjointly performs feature selection, parameter estimation, and state classifica-tion. Our large set of candidate features are partly based on cryptocurrency,sentiment and financial marke
When new technologies for the health care sector are developed, it is of outmost importance to increase the possibilities of survival and remain high quality of life for patients. During the conception and design of such technologies, the problem to solve and the possible solutions to achieve have to be well understood and the scope has to be defined. For the particular case of the project LISA, t
In this thesis, we address the problem of locating a passive target using a multiple-input multiple-output (MIMO) radar with widely separated antennas (WSA). Using a WSA geometry, the spatial diversity of the transmit and receive antennas are utilized to improve the localization accuracy. First, common numerical algorithms are examined, including the Newton-Raphson (NR) method with the maximum lik
Multi-component transient signals show up in many different areas, most commonly in communication and radar but are also often found in measurements of human related signals, such as electrical responses of the heart and the brain. Transient signals are also typical in animal acoustic applications, e.g., dolphin echo locations and bird song syllables. The usual basis functions in linear modeling oMulti-component transient signals show up in many different areas, most commonly in communication and radar but are also often found in measurements of human related signals, such as electrical responses of the heart and the brain. Transient signals are also typical in animal acoustic applications, e.g., dolphin echo locations and bird song syllables. The usual basis functions in linear modeling o
In this work, we extend recent results on the Cramé r-Rao lower bound for multidimensional non-uniformly sampled Nuclear Magnetic Resonance (NMR) signals. The used signal model is more general than earlier models, allowing for the typically present variance differences between the direct and the dif- ferent indirect sampling dimensions. The presented bound is verified with earlier presented 1-and
Cells in vivo are subjected continuously to multiple biochemical and biophysical stimuli from their microenvironment that regulate cell fate and function. Although two-dimensional (2D) platforms to check cell responses to various microenvironmental factors have been established, these methods lack physiological relevance. Macroscale three-dimensional (3D) cell culture platforms were developed to p
This master thesis was commissioned by Det Norske Veritas (DNV) and was conducted at the department of Energy Sciences at the Faculty of Engineering, Lund University. The purpose of the thesis was to develop a structured and uniform methodology for Best Available Techniques (BAT) assessments of oil-‐ and gas installations. BAT is defined in the EU directive on Integrated Pollution Prevention and
Constitutional monarchy offers Iran a politically stable and culturally resonant alternative to partisan republicanism. Grounded in both empirical research and philosophical tradition, it combines symbolic authority with institutional continuity, enabling national unity without authoritarianism. Monarchs function as neutral anchors above political conflict, often at lower public cost and with grea
This paper examines the potential benefits of applying next best view planning to sequential 3D reconstruction from unordered image sequences. A standard sequential structure-and-motion pipeline is extended with active selection of the order in which cameras are resectioned. To this end, approximate covariance propagation is implemented throughout the system, providing running estimates of the unc
Smoking and hazardous drinking are common and important risk factors for an increased rate of complications after surgery. The underlying pathophysiological mechanisms include organic dysfunctions that can recover with abstinence. Abstinence starting 3-8 weeks before surgery will significantly reduce the incidence of several serious postoperative complications, such as wound and cardiopulmonary co
This thesis is based on nine papers, all concerned with parameter estimation. The thesis aims at solving problems related to real-world applications such as spectroscopy, DNA sequencing, and audio processing, using sparse modeling heuristics. For the problems considered in this thesis, one is not only concerned with finding the parameters in the signal model, but also to determine the number of si
Financial markets exhibit time-varying volatility and cross-asset correlation. To construct and optimize a risk-adjusted portfolio and account for underlying collinearity between se- curities, a good understanding of these two dynamics is important. In this study global equity indices are modeled with the purpose of improving the forecasting accuracy of time-varying correlations, as well as distin
Time-frequency (TF) postprocessing methods are often used to form concentrated TF representations (TFRs) for nonstationary signals. Regrettably, most such techniques are sensitive to noise and tend to underestimate weak components when dealing with transient signals, resulting in sidelobes and low-resolution TFRs. In this work, we introduce a generalized group delay (GD) weighted sparse TF (GWSTF)
