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Matching pursuits with time-frequency dictionaries

by Stephane G. Mallat, Zhifeng Zhang - IEEE Transactions on Signal Processing , 1993
"... Abstract-We introduce an algorithm, called matching pursuit, that decomposes any signal into a linear expansion of waveforms that are selected from a redundant dictionary of functions. These waveforms are chosen in order to best match the signal structures. Matching pursuits are general procedures t ..."
Abstract - Cited by 1671 (13 self) - Add to MetaCart
to compute adaptive signal representations. With a dictionary of Gabor functions a matching pursuit defines an adaptive time-frequency transform. We derive a signal energy distribution in the time-frequency plane, which does not include interference terms, unlike Wigner and Cohen class distributions. A

Some simple effective approximations to the 2-Poisson model for probabilistic weighted retrieval

by S. E. Robertson, S. Walker - In Proceedings of SIGIR’94 , 1994
"... The 2–Poisson model for term frequencies is used to suggest ways of incorporating certain variables in probabilistic models for information retrieval. The variables concerned are within-document term frequency, document length, and within-query term frequency. Simple weighting functions are develope ..."
Abstract - Cited by 460 (14 self) - Add to MetaCart
The 2–Poisson model for term frequencies is used to suggest ways of incorporating certain variables in probabilistic models for information retrieval. The variables concerned are within-document term frequency, document length, and within-query term frequency. Simple weighting functions

Semantically Enhanced Term Frequency

by Christof Müller, Iryna Gurevych , 2010
"... In this paper, we complement the term frequency, which is used in many bag-of-words based information retrieval models, with information about the semantic relatedness of query and document terms. Our experiments show that when employed in the standard probabilistic retrieval model BM25, the additi ..."
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In this paper, we complement the term frequency, which is used in many bag-of-words based information retrieval models, with information about the semantic relatedness of query and document terms. Our experiments show that when employed in the standard probabilistic retrieval model BM25

A statistical interpretation of term specificity and its application in retrieval

by Karen Spärck Jones - Journal of Documentation , 1972
"... Abstract: The exhaustivity of document descriptions and the specificity of index terms are usually regarded as independent. It is suggested that specificity should be interpreted statistically, as a function of term use rather than of term meaning. The effects on retrieval of variations in term spec ..."
Abstract - Cited by 589 (3 self) - Add to MetaCart
specificity are examined, experiments with three test collections showing, in particular, that frequently-occurring terms are required for good overall performance. It is argued that terms should be weighted according to collection frequency, so that matches on less frequent, more specific, terms

Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences

by Steven B. Davis, Paul Mermelstein - ACOUSTICS, SPEECH AND SIGNAL PROCESSING, IEEE TRANSACTIONS ON , 1980
"... Several parametric representations of the acoustic signal were compared as to word recognition performance in a syllable-oriented continuous speech recognition system. The vocabulary in-cluded many phonetically similar monosyllabic words, therefore the emphasis was on ability to retain phonetically ..."
Abstract - Cited by 1120 (2 self) - Add to MetaCart
of the mel-frequency cepstrum coefficients may be attributed to the fact that they better represent the perceptually relevant aspects of the short-term speech spectrum.

A Comparative Study on Feature Selection in Text Categorization

by Yiming Yang, Jan O. Pedersen , 1997
"... This paper is a comparative study of feature selection methods in statistical learning of text categorization. The focus is on aggressive dimensionality reduction. Five methods were evaluated, including term selection based on document frequency (DF), information gain (IG), mutual information (MI), ..."
Abstract - Cited by 1320 (15 self) - Add to MetaCart
This paper is a comparative study of feature selection methods in statistical learning of text categorization. The focus is on aggressive dimensionality reduction. Five methods were evaluated, including term selection based on document frequency (DF), information gain (IG), mutual information (MI

Recognizing human actions: A local SVM approach

by Christian Schüldt, Ivan Laptev, Barbara Caputo - In ICPR , 2004
"... Local space-time features capture local events in video and can be adapted to the size, the frequency and the velocity of moving patterns. In this paper we demonstrate how such features can be used for recognizing complex motion patterns. We construct video representations in terms of local space-ti ..."
Abstract - Cited by 758 (20 self) - Add to MetaCart
Local space-time features capture local events in video and can be adapted to the size, the frequency and the velocity of moving patterns. In this paper we demonstrate how such features can be used for recognizing complex motion patterns. We construct video representations in terms of local space

Information Extraction with Term Frequencies

by T. R. Lynam, C. L. A. Clarke, G. V. Cormack , 2001
"... this paper is the information extraction component. It is based on the premise that information related to the answer will be found many times in a large corpus like the Web ..."
Abstract - Cited by 2 (1 self) - Add to MetaCart
this paper is the information extraction component. It is based on the premise that information related to the answer will be found many times in a large corpus like the Web

The Log-Log Term Frequency Distribution

by Jason D. M. Rennie , 2005
"... Though commonly used, the unigram is widely known as being a poor model of term frequency; it assumes that term occurrences are independent, whereas many words, especially topic-oriented ones, tend to occur in bursts. Herein, we propose a model of term frequency that treats words independently, but ..."
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Though commonly used, the unigram is widely known as being a poor model of term frequency; it assumes that term occurrences are independent, whereas many words, especially topic-oriented ones, tend to occur in bursts. Herein, we propose a model of term frequency that treats words independently

Robust frequency and timing synchronization for OFDM

by Timothy M. Schmidl, Donald C. Cox - IEEE Transactions on Communications , 1997
"... Abstract — A rapid synchronization method is presented for an orthogonal frequency-division multiplexing (OFDM) system using either a continuous transmission or a burst operation over a frequency-selective channel. The presence of a signal can be detected upon the receipt of just one training sequen ..."
Abstract - Cited by 386 (0 self) - Add to MetaCart
over many subcarriers allows acquisition at very low signal-to-noise ratios (SNR’s). Index Terms — Carrier frequency, orthogonal frequency-division multiplexing, symbol timing estimation.
Results 1 - 10 of 27,480