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A Sequential Algorithm for Signal Segmentation
2018
Entropy
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For that, we apply a sequential algorithm with the only assumption that an event alters the energy of the signal. The algorithm is entirely based on Bayesian methods. ...
that can be used to train a classification algorithm. ...
In particular, they were the ones first suggesting that we should follow a general approach before trying to model specific events. ...
doi:10.3390/e20010055
pmid:33265142
fatcat:n4lys7le4ne35gdvdzlgm3tjua
Phase control algorithms for focusing light through turbid media
2008
Optics Communications
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Here we present three algorithms for constructing a wavefront that focuses through a scattering medium. ...
We analyze the dynamic behavior of these algorithms and compare their sensitivity to measurement noise. The algorithms are compared both experimentally and using numerical simulations. ...
Willem Vos for support and valuable discussions. ...
doi:10.1016/j.optcom.2008.02.022
fatcat:mrm2qgzk5rcptp42lzn4ramziq
HELIX
2012
Proceedings of the Tenth International Symposium on Code Generation and Optimization - CHO '12
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We describe and evaluate HELIX, a new technique for automatic loop parallelization that assigns successive iterations of a loop to separate threads. ...
On a six-core Intel R ✌ Core ❚ ▼ i7-980X, HELIX achieves speedups averaging 2.25✂, with a maximum of 4.12✂, for thirteen C benchmarks from SPEC CPU2000. ...
Acknowledgements Authors thank the anonymous reviewers for their hard work that allowed us to improve the paper significantly. ...
doi:10.1145/2259016.2259028
dblp:conf/cgo/CampanoniJHRWB12
fatcat:saxndpn5rvhodc7nsnfl7tjmxq
Hadoop-EDF: Large-scale Distributed Processing of Electrophysiological Signal Data in Hadoop MapReduce
2019
2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
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Sequential Processing of Electrophysiological Signal Data In order to perform a through performance evaluation of our Hadoop-EDF algorithm in parallel, we also implemented a sequential algorithm for processing ...
However, existing signal analysis algorithms and tools load and process EDF files in a sequential way (before performing analysis), which is time-consuming and inefficient when a large number of EDF files ...
doi:10.1109/bibm47256.2019.8983371
dblp:conf/bibm/WuLLC19
fatcat:ec5cbsgam5cihg6onx2qnauhuu
Recursive Bayesian Autoregressive Changepoint Detector For Sequential Signal Segmentation
2004
Zenodo
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Another very simple idea for the sequential changepoint detection seems to be the signal segmentation and repeatedly using the BACD. ...
The segmentation of these signals requires the sequential detection of multiple change-points. ...
doi:10.5281/zenodo.38626
fatcat:fsri2ev5lrf3fapppcfkxyvbym
Iterative and sequential Kalman filter-based speech enhancement algorithms
1998
IEEE Transactions on Speech and Audio Processing
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The enhanced speech signal is obtained as a byproduct of the parameter estimation algorithm. The second algorithm is a sequential, computationally efficient, gradient descent algorithm. ...
and sequential algorithms. ...
Sharony for helping with efficient programming of the algorithms. ...
doi:10.1109/89.701367
fatcat:dbhqbpre4zaczbrbvd2inia6hq
Universal Switching Linear Least Squares Prediction
2008
IEEE Transactions on Signal Processing
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Using a competitive algorithm framework, we construct sequential algorithms that are competitive with the best linear regression algorithms for any segmenting of the data as well as the best partitioning ...
We construct lower bounds on the performance of any sequential algorithm, demonstrating a form of min-max optimality under certain settings. ...
Applying this result for all segments (31) yields For a given , running an independent AA for each segment yields a sequential predictor, similar to the sequential predictor represented in (7) . ...
doi:10.1109/tsp.2007.901161
fatcat:7nmnr7xqx5ap7hxvxo6slyhmhm
Fast Implementation of a Bayesian Unsupervised Segmentation Algorithm
[article]
2018
arXiv
pre-print
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In a recent paper, we have proposed an unsupervised algorithm for audio signal segmentation entirely based on Bayesian methods. ...
We also offer a detailed analysis on the sensibility of the algorithm to its different parameters, and show its application to real-life subacquatic signals obtained off the brazilian South coast. ...
Conclusions The sequential segmentation algorithm is a Bayesian unsupervised methodology aimed at segmentating audio signals. ...
arXiv:1803.01801v2
fatcat:3yb447oodrdq7fdetrfoya74mq
Model-based sequential organization in cochannel speech
2006
IEEE Transactions on Audio, Speech, and Language Processing
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We extract minimally corrupted segments, or usable speech, in cochannel speech using a robust multipitch tracking algorithm. ...
To utilize speaker characteristics for sequential organization, we extend the traditional SID framework to cochannel speech and derive a joint objective for sequential grouping and SID, leading to a problem ...
Wu for his assistance in using the multipitch tracking algorithm, J. Barker for a suggestion regarding exhaustive search complexity, and three anonymous referees for extensive and helpful comments. ...
doi:10.1109/tsa.2005.854106
fatcat:d22usgavvvc4rlnskoofpfhw2a
Real-Time 3D Depth Generation for Stereoscopic Video Applications with Thread-Level Superscalar-Pipeline Parallelization
2012
Journal of Signal Processing Systems
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We propose a low-complexity algorithm for stereoscopic video applications that generates a high-quality 3D image depth map from a single 2D image. ...
Experimental results for HD1080 resolution images demonstrate that the algorithm can generate high-quality depth maps with an average reduction in the computational complexity of 98.2 % compared with a ...
Using the proposed algorithm, the phase of 4bit removing segmentation yields speedups of 840 for QVGA, 939 for XGA, and 911.1 for HD1080. ...
doi:10.1007/s11265-012-0691-5
fatcat:4p2a6fcbznavvilx5mbitu6dgq
An approach to sequential grouping in cochannel speech
2011
2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Model-based methods for sequential organization in cochannel speech require pretrained speaker models and often prior knowledge of participating speakers. ...
Evaluations and comparisons show that the proposed method outperforms a model-based method in terms of speech segregation. ...
Fig. 1 . 1 An example of simultaneous streams generated using the tandem algorithm.
Fig. 2 . 2 Segments produced by onset/offset based segmentation followed by voiced signal removal. ...
doi:10.1109/icassp.2011.5947388
dblp:conf/icassp/HuW11
fatcat:byu4hgei35fhpclepux7d5ma5u
DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse Coding
2018
International Conference on Machine Learning
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In this paper, we introduce DICOD, a convolutional sparse coding algorithm which builds shift invariant representations for long signals. ...
Convolutional Representation for Long Signals Sparse coding aims at building sparse linear representations of a data set based on a dictionary of basic elements called atoms. ...
We also include LGCD M , for M ∈ {60, 600}, the sequential run of the DICOD algorithm using M segments, as described in Algorithm 3. ...
dblp:conf/icml/MoreauOV18
fatcat:pkoex4w3qvd2phppgja22lcfdm
Switching Strategies for Sequential Decision Problems With Multiplicative Loss With Application to Portfolios
2009
IEEE Transactions on Signal Processing
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A wide variety of problems in signal processing can be formulated such that decisions are made by sequentially taking convex combinations of vector-valued observations and these convex combinations are ...
A "universal" approach to such problems might attempt to sequentially achieve the performance of the best fixed convex combination, as might be achievable noncausally, by observing all of the outcomes ...
Ordentlich for providing them with the historical data used in their experiments. ...
doi:10.1109/tsp.2009.2013906
fatcat:47zaa2ykvzfmvoulvxo2amch2e
Universal Randomized Switching
2010
IEEE Transactions on Signal Processing
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number of segments and the best algorithm for each segment, based on observing the whole observation process a priori. ...
In this paper, we consider a competitive approach to sequential decision problems, suitable for a variety of signal processing applications where at each of a succession of times, a selection must be made ...
number of segments and the best algorithm for each segment, based on observing the whole observation process a priori. ...
doi:10.1109/tsp.2009.2037062
fatcat:2tucrb22xfg5lpmzeg4ufhbtna
Control of dexterous bio-prosthetic hand via sequential recognition of EMG signals using fuzzy relations
2009
Studies in Health Technology and Informatics
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The contextual (sequential) recognition is considered in which the fuzzy relation approach is applied to the construction of a classifying algorithm. ...
Experimental investigations of the proposed algorithm for real data are performed and results are discussed. ...
The rms values for 3 selected intervals of EMG signal spectrum were taken as the feature of each signal segment. Eventually vector x has a form: , Table 1 . ...
pmid:19745423
fatcat:hhphdhtrvnfxfmoc75zslku2sm
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