SFSASDA · Spline-like function spaces with applications to scattered data approximations
7РП — „Хора“ (Действия „Мария Кюри“)
- Период
- 2008-04-01 → 2010-03-31
- Финансиране от ЕС
- 155 987 €
- Участници
- 1
- Схема
- MC-IEF
Линиите свързват координатора с партньорите.
Накратко на български
Математически методи за приблизително изчисляване на данни, разположени на неравномерни интервали, като например при геофизични измервания или медицински изображения. Те помагат за създаването на по-ефективни алгоритми за обработка на сигнали, премахване на шума и подобряване на устойчивостта при грешки.
Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.
Резултати накратко
Spline-like function spaces with applications to scattered data approximations
We developed mathematical methods for scattered data approximation that can be used to implement efficient algorithms in signal processing and related areas. We considered the problem in spaces generated by translates of compressed or dilated copies of a function (or finitely many functions) along irregularly spaced points. Both the functional analytic side and the computational aspects of the problem have been covered. After studying the behaviour of 'smooth warping' functions, we found a transformation rule that provides a method for constructing Riesz bases and frames for the proposed spaces by choosing proper affine transformations. The systems of affine transformations of a function have a simple structure and hence there are suitable for numerical implementations. Therefore the proposed technique has a wide range of applications like approximation of geophysical data, wireless communication and medical imaging. Algorithms for constructing this kind of Riesz bases have been implemented in Matlab for several 'mother' functions (for example splines) and different warping functions. All the experiments showed that the affinely obtained systems and the warped systems are very similar. The concept of frame is an important background for sampling theory and signal processing. Different from bases, frame decompositions are redundant. This property is advantageous in de-noising, error robustness or sparsity. In acoustics, a typical example of frames of translates are filterbanks. For example the phase vocoder corresponds to such a filterbank with regular shifts, which is often used in signal processing applications like time stretching. Introducing irregular shifts gives rise to a generalisation of this analysis/synthesis system. We studied properties of a set of irregular translates of a function in L^2(R^d). This was achieved by looking at a set of exponentials restricted to a subset E of R^d with frequencies in a countable set. The results were obtained by analysing which properties of this set of exponentials are preserved when multiplied by the Fourier transform of a function in L^2(E). Using density results due to Beurling, we proved the existence and gave ways to construct frames by irregular translates. Finite frames arise in many applications, where we usually work in finite dimensional spaces. Dual frames are an essential tool when we want to reconstruct a function. We considered a finite dimensional Hilbert space and introduced the concept of 'mixed frame potential', which generalises the notion of the Benedetto-Fickus frame potential and measures the biorthogonality of two systems of vectors. We characterised the minimisers of this new potential on a restricted domain. We obtained necessary and sufficient conditions on a real sequence {c_m}_{m=1,¿,N} in order to have a generalised dual pair of frames {f_m}_{m=1,¿,N},{g_m}_{m=1,¿,N} such that =c_m. Moreover we found that the elements of this generalised dual pair of frames can be constructed with any desired norm. It has been worked on the infinite dimensional version of the Bourgain-Tzafriri restricted invertibility theorem. Results for the wavelet case have been obtained using a result about interpolating sets.
Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз
Цел на проекта
We will develop mathematical methods for scattered data approximation that can be used to implement efficient algorithms in signal processing and related areas. So far, the problem of reconstructing an unknown function from a given discrete set of sampling points has been studied in shift invariant spaces, i.e. spaces generated by translates of a function (or finitely many functions). We propose to consider the problem in spaces generated by translates of compressed copies of a function (or finitely many functions) along irregularly spaced points. We are convinced that with our model we will obtain better approximation properties, since it takes into account the structure of the sampling data. The problem will be first studied on the real line, then in the plane and finally on the sphere, where the lack of regular grids requires certainly some modifications. Both the functional analytic side and the computational aspects of the problem will be covered. The candidate has experience in the field of the proposed topic, since her research area is time-frequency analysis, frame theory, sampling theory, shift invariant spaces, etc., which constitute the background of this project. She was member of several research projects related to the topic, her master and Ph.D thesis are connected to the proposed research. The project will be carried out at the Numerical Harmonic Analysis Group (NuHAG), University of Vienna, whose key scientists are Prof. H.G. Feichtinger and Prof. K. Gröchenig. The proposed research center has a leading position in the area of sampling theory, time-frequency analysis, frame theory and wavelet analysis, which makes it the proper environment for the proposed project. The experience that NuHAG has in the mentioned areas and also in training researchers will be helpful in the developing of the professional skills of the proposer. The MC Exc. Grant EUCETIFA (2005-2009) and the cooperation with other PostDocs at NuHAG will support the project.
Оригинален текст от CORDIS (на английски).
Участници
- UNIVERSITAT WIEN · WienКоординаторАвстрия
Връзки
Данни: CORDIS, © Европейски съюз
