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Out-of-Sample Extension for Dimensionality Reduction of Noisy Time Series

Hamid Dadkhahi, Marco F. Duarte, Benjamin M. Marlin
<span title="">2017</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dhlhr4jqkbcmdbua2ca45o7kru" style="color: black;">IEEE Transactions on Image Processing</a> </i> &nbsp;
Given a set of noise-free training data and its embedding, the proposed framework extends the embedding for a noisy time series.  ...  To the best of our knowledge, this is the first method for out-of-sample extension of manifold embeddings that leverages timing information available for the extension set.  ...  ACKNOWLEDGEMENTS We thank Addison Mayberry for providing us with the eyeglasses dataset and the codes for the implementation of the MLP eye gaze estimation algorithm.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tip.2017.2735189">doi:10.1109/tip.2017.2735189</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/28783635">pmid:28783635</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ttkwz4zmvzfqjgwyrkrstqu7bq">fatcat:ttkwz4zmvzfqjgwyrkrstqu7bq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200913190831/https://arxiv.org/pdf/1606.08282v2.pdf" title="fulltext PDF download [not primary version]" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <span style="color: #f43e3e;">&#10033;</span> <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ef/0e/ef0e3b3d59c085a62715b766cb39f7410021deee.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tip.2017.2735189"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Application of Neural Networks for Foreign Exchange Rates Forecasting with Noise Reduction [chapter]

Wei Huang, Kin Keung Lai, Shouyang Wang
<span title="">2007</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
Predictive models are generally fitted directly from the original noisy data. It is well known that noise can seriously limit the prediction performance on time series.  ...  The experiment results show that the nonlinear noise reduction methods can improve the prediction performance of NNs.  ...  It has been shown that the in-sample fit and the out-of-sample forecasting ability of NNs are not very sensitive to the number of hidden nodes [8] . Parsimony is a principle for designing NNs.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-540-72586-2_65">doi:10.1007/978-3-540-72586-2_65</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5oo2ujpn5bg3taec5iibdqqcmq">fatcat:5oo2ujpn5bg3taec5iibdqqcmq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190503004922/https://link.springer.com/content/pdf/10.1007%2F978-3-540-72586-2_65.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/86/01/86015d324930d50cdd3a028054dbc460d3efcd41.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-540-72586-2_65"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Predicting Spatio-Temporal Time Series Using Dimension Reduced Local States [article]

Jonas Isensee, George Datseris, Ulrich Parlitz
<span title="2019-04-12">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We present a method for both cross estimation and iterated time series prediction of spatio temporal dynamics based on reconstructed local states, PCA dimension reduction, and local modelling using nearest  ...  The effectiveness of this approach is shown for (noisy) data from a (cubic) Barkley model, the Bueno-Orovio-Cherry-Fenton model, and the Kuramoto-Sivashinsky model.  ...  Zimmermann for allowing the use of BOCF model simulation and S. Luther for scientific discussions and continuous support.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1904.06089v1">arXiv:1904.06089v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fevaops5effpjpmb7chfinnqxe">fatcat:fevaops5effpjpmb7chfinnqxe</a> </span>
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Unsupervised Discovery of Temporal Structure in Noisy Data with Dynamical Components Analysis [article]

David G. Clark, Jesse A. Livezey, Kristofer E. Bouchard
<span title="2019-10-27">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Combining these approaches, we introduce Dynamical Components Analysis (DCA), a linear dimensionality reduction method which discovers a subspace of high-dimensional time series data with maximal predictive  ...  Overall, DCA robustly extracts dynamical structure in noisy, high-dimensional data while retaining the computational efficiency and geometric interpretability of linear dimensionality reduction methods  ...  We thank the Neural Systems and Data Science Lab and Laurenz Wiskott for helpful discussion.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1905.09944v2">arXiv:1905.09944v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/mhejnzj7ebb5vibimcywlr5fc4">fatcat:mhejnzj7ebb5vibimcywlr5fc4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200914071043/https://arxiv.org/pdf/1905.09944v2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/72/b9/72b9b6b5f08f993769056aa9ca3dca6fb5df4913.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1905.09944v2" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Predicting Spatio-temporal Time Series Using Dimension Reduced Local States

Jonas Isensee, George Datseris, Ulrich Parlitz
<span title="2019-10-26">2019</span> <i title="Springer Science and Business Media LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/b4h5uwh6mnadrpvtzjjtn5fyey" style="color: black;">Journal of nonlinear science</a> </i> &nbsp;
We present a method for both cross-estimation and iterated time series prediction of spatio-temporal dynamics based on local modelling and dimension reduction techniques.  ...  The effectiveness of this approach is shown for (noisy) data from a (cubic) Barkley model, the Bueno-Orovio-Cherry-Fenton model, and the Kuramoto-Sivashinsky model.  ...  Zimmermann for allowing the use of BOCF model simulation and S. Luther for scientific discussions and continuous support.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s00332-019-09588-7">doi:10.1007/s00332-019-09588-7</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wt23rfaf2bbufeqbnz5itonx7q">fatcat:wt23rfaf2bbufeqbnz5itonx7q</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200311084454/https://link.springer.com/content/pdf/10.1007%2Fs00332-019-09588-7.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/09/3d/093dd22c834cdf44b8b8cef6b2b43771b0a5ce3e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s00332-019-09588-7"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Reducing colored noise for chaotic time series in the local phase space

Junfeng Sun, Yi Zhao, Jie Zhang, Xiaodong Luo, Michael Small
<span title="2007-08-17">2007</span> <i title="American Physical Society (APS)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/nuk2stxzvvhf7ljciu325kj77m" style="color: black;">Physical Review E</a> </i> &nbsp;
With the observation that the energy of colored noise is mainly distributed in a low dimensional subspace, a noise dominated subspace is first estimated by the energy distribution of colored noise.  ...  The residual error of the output of step 1 tends to distribute on each direction uniformly.  ...  Performance of noise reduction for the noisy Lorenz time series with colored noise generated by AR͑3͒.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1103/physreve.76.026211">doi:10.1103/physreve.76.026211</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/17930125">pmid:17930125</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ffbajsn7krettjtztchpa3kiom">fatcat:ffbajsn7krettjtztchpa3kiom</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170808230227/http://ira.lib.polyu.edu.hk/bitstream/10397/4824/1/Sun_Reducing_Coloured_Noise.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/e6/64/e664bf412c7e4c7119d1c63e40309ebf1625abfc.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1103/physreve.76.026211"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> aps.org </button> </a>

Robust Dimensionality Reduction for Human Action Recognition

Oscar Perez Concha, Richard Yi Da Xu, Massimo Piccardi
<span title="">2010</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/awy6wv35krcgpf7qnuhrzax63i" style="color: black;">2010 International Conference on Digital Image Computing: Techniques and Applications</a> </i> &nbsp;
However, the dimensionality of typical feature sets joint with that of the time dimension often leads to a curse-ofdimensionality situation.  ...  Moreover, the measurement of the feature set is subject to sometime severe errors. This paper presents an approach to human action recognition based on robust dimensionality reduction.  ...  While previous work exists utilising dimensionality reduction in time-series classifiers [13, 7] , to the best of our knowledge this is the first work attempting a comparative analysis in the field of  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/dicta.2010.66">doi:10.1109/dicta.2010.66</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/dicta/ConchaXP10.html">dblp:conf/dicta/ConchaXP10</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/lmcflvi5lrabjguo7v3illpwe4">fatcat:lmcflvi5lrabjguo7v3illpwe4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170811063548/https://opus.lib.uts.edu.au/bitstream/10453/16577/1/2010000755.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ed/83/ed83160bb59d2d573b0b93f4e71b633bac96f083.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/dicta.2010.66"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Knowledge Network Approach to Noise Reduction [article]

Arturo Berrones
<span title="2006-09-06">2006</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
The formalism gives a novel algorithm from which statistical tests for the identification of deterministic behavior in noisy stationary time series can be constructed.  ...  Previous preliminary results on the application of knowledge networks to noise reduction in stationary harmonic and weakly chaotic signals are extended to more general cases.  ...  ACKNOWLEDGMENT The author would like to thank to CONACYT, SEP-PROMEP and UANL-PAICYT for partial financial support.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/physics/0609048v1">arXiv:physics/0609048v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/gwebpbd2oza3dbacf5hovhohiu">fatcat:gwebpbd2oza3dbacf5hovhohiu</a> </span>
<a target="_blank" rel="noopener" href="https://archive.org/download/arxiv-physics0609048/physics0609048.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> File Archive [PDF] </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/physics/0609048v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Detecting phase synchronization in noisy data from coupled chaotic oscillators

Junfeng Sun, Jie Zhang, Jin Zhou, Xiaoke Xu, Michael Small
<span title="2008-04-17">2008</span> <i title="American Physical Society (APS)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/nuk2stxzvvhf7ljciu325kj77m" style="color: black;">Physical Review E</a> </i> &nbsp;
The first is a neighborhood-based method which links time delay embedding with instantaneous phase estimation. The second adopts the local projection method as a preprocessing filter to noisy data.  ...  Both schemes utilize the state recurrence, an important feature of chaotic data.  ...  For the measured time series ͕s͑n͖͒, its Hilbert transform is denoted as ͕s͑n͖͒.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1103/physreve.77.046213">doi:10.1103/physreve.77.046213</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/18517716">pmid:18517716</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/i557dvlhizh2nohn3evgmoqnei">fatcat:i557dvlhizh2nohn3evgmoqnei</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170811160122/http://ira.lib.polyu.edu.hk/bitstream/10397/4798/1/Sun_Detecting_Temporal_Pseudoperiodic.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ea/82/ea82f8a37c8e0857e121f7e7f950fe107635e168.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1103/physreve.77.046213"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> aps.org </button> </a>

Unsupervised Deep Anomaly Detection for Multi-Sensor Time-Series Signals [article]

Yuxin Zhang, Yiqiang Chen, Jindong Wang, Zhiwen Pan
<span title="2021-08-02">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
These sensors can generate a substantial amount of multivariate time-series data.  ...  Then, we construct a Memory Network consisting of linear (Autoregressive Model) and non-linear predictions (Bidirectional LSTM with Attention) to capture temporal dependence from time-series data.  ...  For OCSVM and HMM, they achieve better performance because of dimensionality reduction from 36 dimensions of PAMAP2 dataset to 7 dimensions.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2107.12626v2">arXiv:2107.12626v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/t6eyfskylnfhdhkv6btrzxtugu">fatcat:t6eyfskylnfhdhkv6btrzxtugu</a> </span>
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Nonlinear noise reduction for electrocardiograms

Thomas Schreiber, Daniel T. Kaplan
<span title="">1996</span> <i title="AIP Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/jh7idzebgzcuffjreetqux4374" style="color: black;">Chaos</a> </i> &nbsp;
The result constitutes evidence that techniques of time series analysis based on chaos theory can be useful despite the fact that very few natural phenomena have been actually established to be deterministically  ...  Although long term predictions are thus impossible, good predictions can be made for times smaller than one heart cycle.  ...  ACKNOWLEDGMENTS We are indebted to Leon Glass, Peter Grassberger and Holger Kantz for stimulating discussions.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1063/1.166148">doi:10.1063/1.166148</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/12780239">pmid:12780239</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/iulhcf5nl5bhdah2ghytvyup4q">fatcat:iulhcf5nl5bhdah2ghytvyup4q</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200325032652/https://works.bepress.com/daniel_kaplan/34/download/" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/15/73/15730f66810149532766170f7e0f12edef042cc3.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1063/1.166148"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Detecting and Estimating Multivariate Self-Similar Sources in High-Dimensional Noisy Mixtures

Patrice Abry, Herwig Wendt, Gustavo Didier
<span title="">2018</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dr2vggyhlngjrdtctigcda6lge" style="color: black;">2018 IEEE Statistical Signal Processing Workshop (SSP)</a> </i> &nbsp;
, even at low signal to noise ratio and for a very large number of actually observed mixed and noisy time series.  ...  Nowadays, because of the massive and systematic deployment of sensors, systems are routinely monitored via a large collection of time series.  ...  components (sources) M in L ≥ M noisy time series.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/ssp.2018.8450758">doi:10.1109/ssp.2018.8450758</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/ssp/AbryWD18.html">dblp:conf/ssp/AbryWD18</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wpqs4y3llvfmbldcpkkzqbwxhi">fatcat:wpqs4y3llvfmbldcpkkzqbwxhi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200511023443/https://hal.archives-ouvertes.fr/hal-02279354/file/abry_22492.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/7b/3a/7b3a341afaa7bd2ca8c831131290457222204968.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/ssp.2018.8450758"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Bayesian Dynamic Mode Decomposition

Naoya Takeishi, Yoshinobu Kawahara, Yasuo Tabei, Takehisa Yairi
<span title="">2017</span> <i title="International Joint Conferences on Artificial Intelligence Organization"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/vfwwmrihanevtjbbkti2kc3nke" style="color: black;">Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence</a> </i> &nbsp;
Moreover, as a specific example, we discuss the case of using a sparsity-promoting prior for an automatic determination of the number of dynamic modes.  ...  Dynamic mode decomposition (DMD) is a data-driven method for calculating a modal representation of a nonlinear dynamical system, and it has been utilized in various fields of science and engineering.  ...  Dimensionality reduction BDMD-sp provides a way for dimensionality reduction of time-series data, since it can concentrate their information on a small number of dynamic modes.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.24963/ijcai.2017/392">doi:10.24963/ijcai.2017/392</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/ijcai/TakeishiKTY17.html">dblp:conf/ijcai/TakeishiKTY17</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wsvei32n3bfonhcn4xwmfp36ne">fatcat:wsvei32n3bfonhcn4xwmfp36ne</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180721031831/https://www.ijcai.org/proceedings/2017/0392.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/1f/68/1f68585f490a359d09efdd8d3cd2b6d7ef0e6cbf.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.24963/ijcai.2017/392"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Extraction of Process-Structure Evolution Linkages from X-ray Scattering Measurements Using Dimensionality Reduction and Time Series Analysis

David B. Brough, Abhiram Kannan, Benjamin Haaland, David G. Bucknall, Surya R. Kalidindi
<span title="2017-03-10">2017</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/4qemydmlqnekthpopchvrysdj4" style="color: black;">Integrating Materials and Manufacturing Innovation</a> </i> &nbsp;
Towards this end, this paper lays a theoretical framework that injects the established time series analysis into the recently developed materials knowledge systems (MKS) framework.  ...  of new materials.  ...  , and (ii) leave one sample out cross-validation is equivalent to a traditional train-test split where 11 samples are used to calibration and one sample is used for validation, repeated 12 times in the  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s40192-017-0093-4">doi:10.1007/s40192-017-0093-4</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/31976206">pmid:31976206</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC6945990/">pmcid:PMC6945990</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/56t374jftbe6zekzk4ewsd6awa">fatcat:56t374jftbe6zekzk4ewsd6awa</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180726140754/https://link.springer.com/content/pdf/10.1007%2Fs40192-017-0093-4.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/99/27/9927ce2e049cc4029f32c79e6ba8d116213f0dd3.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s40192-017-0093-4"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6945990" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

A realistic coupled nonlinear artificial ECG, BP, and respiratory signal generator for assessing noise performance of biomedical signal processing algorithms

Gari D. Clifford, Patrick E. McSharry, Derek Abbott, Sergey M. Bezrukov, Andras Der, Angel Sanchez
<span title="2004-05-25">2004</span> <i title="SPIE"> Fluctuations and Noise in Biological, Biophysical, and Biomedical Systems II </i> &nbsp;
The model accurately reproduces many of the important clinical qualities of these signals such as QT dispersion, realistic beat to beat variability in timing and morphology and pulse transit time.  ...  Extensions to a previously published nonlinear model for generating realistic artificial electrocardiograms to include blood pressure and respiratory signals are presented.  ...  The authors would like to thank Andrew Reisner M.D. for his helpful comments during the preparation of this paper.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1117/12.544525">doi:10.1117/12.544525</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/awt356d25fai3ceff4dlllytv4">fatcat:awt356d25fai3ceff4dlllytv4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20050506212420/http://web.mit.edu:80/~gari/www/papers/CliffordMcSharryFinal.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/65/7c/657cbf6acb3a3c13e16a496f230f5c7a632d9969.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1117/12.544525"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>
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