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Multiresolution analysis

About: Multiresolution analysis is a research topic. Over the lifetime, 4032 publications have been published within this topic receiving 140743 citations. The topic is also known as: Multiresolution analysis, MRA.


Papers
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Journal ArticleDOI
TL;DR: In this paper, the multiresolution analysis of supersonic mixing layer based on experimental images is still a formidable challenge, due to the difficulties in measuring su-personic density field.
Abstract: Due to the difficulties in measuring supersonic density field, the multiresolution analysis of supersonic mixing layer based on experimental images is still a formidable challenge. By utilizing the recently developed nanoparticle based planar laser scattering method, the density field of a supersonic mixing layer was measured at high spatiotemporal resolution. According to the dynamic behavior of coherent structures, the multiresolution characteristics of density fluctuation signals and density field images were studied based on Taylor’s hypothesis of space-time conversion and wavelet analysis. The wavelet coefficients reflect the characteristics of density fluctuation signals at different scales, and the detailed coefficients reflect the differences of approximation at adjacent levels. The density fluctuation signals of supersonic mixing layer differ from the periodic sine signal and exhibit similarity to the fractal Koch signal. The similarity at different scales reveals the fractal characteristic of mixing layer flowfield. The two-dimensional wavelet decomposition and reconstruction of density field images extract the approximate and detailed signals at different scales, which effectively resolve the characteristic structures of the flowfield at different scales.

18 citations

Proceedings ArticleDOI
09 Jan 1998
TL;DR: A novel multiresolution algorithm for low bit-rate image compression that performs better than the segmentation based matching pursuit and EZW encoders at lower bit rates, based on subjective image quality and peak signal-to-noise ratio is presented.
Abstract: In this paper, a novel multiresolution algorithm for low bit-rate image compression is presented. High quality low bit-rate image compression is achieved by first decomposing the image into approximation and detail subimages with a shift-orthogonal multiresolution analysis. Then, at the coarsest resolution level, the coefficients of the transformation are encoded by an orthogonal matching pursuit algorithm with a wavelet packet dictionary. Our dictionary consists of convolutional splines of up to order two for the detail and approximation subbands. The intercorrelation between the various resolutions is then exploited by using the same bases from the dictionary to encode the coefficients of the finer resolution bands at the corresponding spatial locations. To further exploit the spatial correlation of the coefficients, the zero trees of wavelets (EZW) algorithm was used to identify the potential zero trees. The coefficients of the presentation are then quantized and arithmetic encoded at each resolution, and packed into a scalable bit stream structure. Our new algorithm is highly bit-rate scalable, and performs better than the segmentation based matching pursuit and EZW encoders at lower bit rates, based on subjective image quality and peak signal-to-noise ratio.© (1998) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

18 citations

Journal ArticleDOI
TL;DR: In this article, the authors present the implementation and performance testing of the wavelet modulation technique for operating three phase, voltage source (VS), six-pulse ac-dc converters.
Abstract: This paper presents the implementation and performance testing of the wavelet modulation technique for operating three phase, voltage source (VS), six-pulse ac-dc converters. The wavelet modulation technique is realized by a nondyadic-type multiresolution analysis (MRA), which is constructed using sets of dilated and translated scale-based linearly combined wavelet basis functions. A dc reference signal is processed using this MRA, where three sets of groups of nonuniform recurrent samples are created by the analysis stage. The synthesis stage of the nondyadic MRA reconstructs the dc reference signal using three sets of dilated and translated scale-based linearly combined synthesis wavelet basis functions, which are used to activate the switching elements of the ac-dc converter. Simulation and experimental performances of the 3φ ac-dc converter, that is, operated by the wavelet modulation technique, are investigated for supplying static and dynamic load types. Performances of the 3φ wavelet modulated ac-dc converter are also investigated for unbalanced input 3φ voltages. Simulation and experimental results show that high magnitude of output dc components, and significant reductions of input and output harmonic components of the 3φ VS ac-dc converter can be accomplished using the wavelet modulation technique. These improvements in the performances of 3φ ac-dc converters are further demonstrated through comparisons with the pulse-width and space-vector modulation techniques under similar conditions of loading and 3φ input voltages.

18 citations

Proceedings ArticleDOI
23 Mar 1992
TL;DR: A new class of signal analysis tools that generalizes the popular wavelet and short-time Fourier transforms is introduced and provides a systematic method for designing new representations with properties useful for certain types of signals.
Abstract: A new class of signal analysis tools that generalizes the popular wavelet and short-time Fourier transforms is introduced. The class allows skews and rotations of the analyzing wavelet in the time-frequency plane, in addition to the time and frequency translations and scalings used by conventional transforms. In addition to providing a unifying framework for studying existing time-frequency representations, the general class provides a systematic method for designing new representations with properties useful for certain types of signals. >

18 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202320
202252
202159
202070
201969
201879