Recently, adaptive approximation techniques have become popular for obtaining parsimonious representations of large classes of signals. These methods include method of frames, matching pursuit, and, most recently, basis pursuit. In this work, high resolution pursuit (HRP) is developed as an alternative to existing function approximation techniques. Existing techniques do not always efficiently ...

This paper describes an automatic road sign recognition system by using matching pursuit (MP) filters. The system consists of two phases. In the detection phase, it finds the relative position of road sign in the original distant image by using a priori knowledge, shape and color information and captures a closer view image. Then it extracts the road sign image from the closer view image by usi...

This paper suggests an upside-down tree-based orthogonal matching pursuit UDT-OMP compressive sampling signal reconstruction method in wavelet domain. An upside-down tree for the wavelet coefficients of signal is constructed, and an improved version of orthogonal matching pursuit is presented. The proposed algorithm reconstructs compressive sampling signal by exploiting the upside-down tree str...

This paper studies quantization error in the context of Matching Pursuit coded streams and proposes a new coefficient quantization scheme taking benefit of the Matching Pursuit properties. The coefficients energy in Matching Pursuit indeed decreases with the iteration number, and the decay rate can be upper-bounded with an exponential curve driven by the redundancy of the dictionary. The redund...

A large amount of research in pathological voice classification consider the task of feature extraction for discrimination between normal and dysphonic sustained vowels. The most widely used dataset for this purpose is the Massachusetts Eye & Ear Infirmary (MEEI) Voice Disorders Database commercialized by KayPENTAX Corp. During the last two decades, dozens of methods have been proposed to extra...

It is often claimed that instantaneous frequency, taken as the derivative of the phase of the signal, is appropriate or meaningful only for mono-component signals, and that for multi-component signals a weighted average of individual instantaneous frequencies should be used. In this paper, we show if a signal is decomposed adaptively and we compute the matching pursuit distribution, then the fi...

In the field of granular decomposition of sound, the Matching Pursuit algorithm is particularly well suited in representing signals with simple sonic entities localized in time and frequency. Our main goal here is to extend this method towards a sound decomposition on a set of arbitrary microsounds leading to a more adaptive framework.