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A Sequential Algorithm for Signal Segmentation

Paulo Hubert, Linilson Padovese, Julio Stern
2018 Entropy  
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

I.M. Vellekoop, A.P. Mosk
2008 Optics Communications  
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


Simone Campanoni, Timothy Jones, Glenn Holloway, Vijay Janapa Reddi, Gu-Yeon Wei, David Brooks
2012 Proceedings of the Tenth International Symposium on Code Generation and Optimization - CHO '12  
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

Yuanyuan Wu, Xiaojin Li, Jinze Liu, Licong Cui
2019 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)  
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

Roman Cmejla, P. Sovka
2004 Zenodo  
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

S. Gannot, D. Burshtein, E. Weinstein
1998 IEEE Transactions on Speech and Audio Processing  
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

S.S. Kozat, A.C. Singer
2008 IEEE Transactions on Signal Processing  
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]

Paulo Hubert, Linilson Padovese, Julio Stern
2018 arXiv   pre-print
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

Yang Shao, DeLiang Wang
2006 IEEE Transactions on Audio, Speech, and Language Processing  
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

Guo-An Jian, Cheng-An Chien, Peng-Sheng Chen, Jiun-In Guo
2012 Journal of Signal Processing Systems  
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

Ke Hu, DeLiang Wang
2011 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  
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

Thomas Moreau, Laurent Oudre, Nicolas Vayatis
2018 International Conference on Machine Learning  
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

Suleyman S. Kozat, Andrew C. Singer
2009 IEEE Transactions on Signal Processing  
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

Suleyman S. Kozat, Andrew C. Singer
2010 IEEE Transactions on Signal Processing  
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

Marek Kurzynski, Andrzej Wolczowski
2009 Studies in Health Technology and Informatics  
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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