نتایج جستجو برای: known algorithm that deals with signals is matching pursuit mp originally
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abstract the present study is concerned with the syntactic deviation in hafezs poetry. poems are known to be accompanied with various linguistic deviations. these deviations may be phonological, morphological and/or syntactic. the relatively high frequency of the cases of the syntactic deviation in hafezs poems makes this rhetorical feature as a main characteristic of his poetry. this thesis, ...
The Bath University Matching Pursuit (BUMP) project aims at developing new matching pursuit (MP) algorithms for still image and video compression. Compared to traditional MP coding, BUMP has many new features that have been designed with the aim of producing an efficient MP representation with reduced complexity. In this paper, we study in depth the characteristics the of bit rate change along ...
There is a growing interest on adapted signal expansions for efficient sparse approximations. For this purpose, signal expansions on over-complete bases are of high interest. Several strategies exist in order to get sparse approximations of a signal as a superposition of functions from a redundant dictionary. One of these strategies is the well known Matching Pursuit (MP). MP is an algorithm wh...
cognitive studies of translation process have recently been awarded a great deal of attention. there exists a psychological angle to almost all translation activities. the present study, thus, deals with analysing the relationships between iranian prospective translators tolerance for ambiguity (ta) and their willingness to translate (wtt). the research was conducted as a mixed methods study, d...
Matching Pursuit (MP)--a method of high-resolution signal analysis--is described in the context of other methods operating in time-frequency space. The method relies on an adaptive approximation of a signal by means of waveforms chosen from a very large and redundant dictionary of functions. The MP performance is illustrated by simulations and examples of sleep spindles and slow wave activity a...
|The use of matching pursuit (MP) to code video using over-complete Gabor basis functions has recently been introduced 8]. In this paper, we propose new functionalities such as SNR scalability and arbitrary shape coding for video coding based on matching pursuit. We improve the performance of the baseline algorithm in 8] by proposing a new search and a new position coding technique. The resulti...
BACKGROUND Somatosensory evoked potential (SEP) signal usually contains a set of detailed temporal components measured and identified in a time domain, giving meaningful information on physiological mechanisms of the nervous system. The purpose of this study is to measure and identify detailed time-frequency components in normal SEP using time-frequency analysis (TFA) methods and to obtain thei...
The use of matching pursuit (MP) to code video using overcomplete Gabor basis functions has recently been introduced. In this paper, we propose new functionalities such as SNR scalability and arbitrary shape coding for video coding based on matching pursuit. We improve the performance of the baseline algorithm presented earlier by proposing a new search and a new position coding technique. The ...
Time-frequency representations are commonly used to analyze the oscillatory nature of bioelectromagnetic signals. There is a growing interest in sparse representations, where the data is described using few components. In this study, we adapt the Matching Pursuit of Mallat and Zhang for biosignals consisting of a series of variations around a similar pattern, with emphasis on multi-trial datase...
Matching Pursuit (MP) uses a greedy search to construct a subset of vectors, from a larger set, which will best represent a signal of interest. Here, we extend this search for the best subset by keeping the K vectors which maximize the selection criterion at each iteration. This is termed the MP:K algorithm and represents a suboptimal search through the tree of all possible subsets where each n...
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