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Guest Editors' Introduction: Neural Networks For Signal Processing

A.G. Constantinides, S. Haykin, Yu Hen Hu, Jenq-neng Hwang, S. Katagiri, Sun-yuan Kung, T.A. Poggio
<span title="">1997</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/gkn2pu46ozb4tmkxczacnmtvkq" style="color: black;">IEEE Transactions on Signal Processing</a> </i> &nbsp;
In "Self-Organizing Feature Maps and Hidden Markov Models for Machine-Tool Monitoring," the self-organizing feature map is used as a feature extractor for a hidden Markov model classifier with applications  ...  In "Neural Network Modeling and Identification of Nonlinear Channels with Memory," the authors study the statistical transient and convergence behavior of a neural network structure (filter-nonlinearity-filter  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tsp.1997.650089">doi:10.1109/tsp.1997.650089</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/se3mm23wzna73iwb6to666b2re">fatcat:se3mm23wzna73iwb6to666b2re</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170829212439/https://minds.wisconsin.edu/bitstream/handle/1793/9176/file_1.pdf?sequence=1" 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/98/1f98a7cc827730521b36b2a8c1841bd1b4ed7315.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tsp.1997.650089"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Evolution of functional link networks

A. Sierra, J.A. Macias, F. Corbacho
<span title="">2001</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dqtjwgdgmjazlimlppwouyrzcq" style="color: black;">IEEE Transactions on Evolutionary Computation</a> </i> &nbsp;
Index Terms-Evolutionary neural networks, feature subset selection, functional link networks, polynomial regression.  ...  Despite their linear nature, FLNs can capture nonlinear input-output relationships, provided that they are fed with an adequate set of polynomial inputs, which are constructed out of the original input  ...  For instance, a GA has been used to select the features fed into a neural network trained by DistAI, a new constructive neural network learning algorithm [42] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/4235.910465">doi:10.1109/4235.910465</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/kbivrns3cbdmrk2i6g3qdy3jam">fatcat:kbivrns3cbdmrk2i6g3qdy3jam</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20091214145035/http://arantxa.ii.uam.es/~asierra/papers/IEEETEC.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/41/a1/41a13f058eb6ce31fe114470b4ad8bf905b6a42e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/4235.910465"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Recent developments in natural computation

JingTao Yao, Qingfu Zhang, Jingsheng Lei
<span title="">2009</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/bby322qx6ndsje4ypr56c7nnly" style="color: black;">Neurocomputing</a> </i> &nbsp;
The first one applies a single pair of neural networks while the second one uses an ensemble of pairs of neural networks for the binary classification.  ...  "Binary classification using ensemble neural networks and interval neutrosophic sets" by Pawalai Kraipeerapun and Chun Che Fung proposes two approaches for binary classification.  ...  Lipo Wang for providing such an excellent environment for research presentation and discussion.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.neucom.2009.02.014">doi:10.1016/j.neucom.2009.02.014</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rpxm46eqbfbyfoxi3dmzffukvq">fatcat:rpxm46eqbfbyfoxi3dmzffukvq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170830043500/http://www.gallup.unm.edu/~smarandache/RecentDevelopmentsInNaturalComputation.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/ae/23/ae232b831c2a8ca63e5b99ba0d49581d32c4ffa9.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.neucom.2009.02.014"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Co-operative Evolution of a Neural Classifier and Feature Subset [chapter]

Jennifer Hallinan, Paul Jackway
<span title="">1999</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;
These results indicate that tailoring a neural network classifier to a specific subset of features has the potential to produce a classifier with low classification error and good generalizability.  ...  This paper describes a novel feature selection algorithm which utilizes a genetic algorithm to select a feature subset in conjunction with the weights for a three-layer feedforward network classifier.  ...  They have been used to select feature sets for classification by a neural net trained using conventional learning algorithms (eg [6, 7] ), and to evolve the weight vector and/or architecture of a neural  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/3-540-48873-1_51">doi:10.1007/3-540-48873-1_51</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xrqqdsbvxrftncduipcmvjngxi">fatcat:xrqqdsbvxrftncduipcmvjngxi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20070417191749/http://www.itee.uq.edu.au/~hallinan/publications/SEAL1999.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/89/20/8920939893fb00c87c1c89c70a8f42ac118e8508.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/3-540-48873-1_51"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Comparison of linear, nonlinear, and feature selection methods for eeg signal classification

D. Garrett, D.A. Peterson, C.W. Anderson, M.H. Thaut
<span title="">2003</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kujklva47vealdwew7xiv34ble" style="color: black;">IEEE transactions on neural systems and rehabilitation engineering</a> </i> &nbsp;
Index Terms-Brain-computer interface (BCI) , electroencephalogram (EEG), feature selection, genetic algorithms (GA), neural networks, pattern classification, support vector machines (SVM).  ...  This paper reports the results of a linear (linear discriminant analysis) and two nonlinear classifiers (neural networks and support vector machines) applied to the classification of spontaneous EEG during  ...  Neural Networks Artificial neural networks are often used to develop nonlinear classification boundaries.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tnsre.2003.814441">doi:10.1109/tnsre.2003.814441</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/12899257">pmid:12899257</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/d5ypsrxmrbe2jb7dfi4dyrhefi">fatcat:d5ypsrxmrbe2jb7dfi4dyrhefi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170809030616/http://www.ru.is/kennarar/deong/pubs/ieee_eeg_final.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/c3/34/c334271678a186732edab0f50d9d2040f10db87b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tnsre.2003.814441"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Evolving neural network pattern classifiers

John R. McDonnell, Donald E. Waagen, Ward C. Page, Su-Shing Chen
<span title="1993-10-29">1993</span> <i title="SPIE"> Neural and Stochastic Methods in Image and Signal Processing II </i> &nbsp;
SpurioLs connections normally generated by evolutionary construction of networks were not observed.  ...  Further work will also apply this technique to more difficult mappings such as the two-spiral classification problem 5 as well as classification problems of Naval interest.  ...  ABSTRACT (Mormom 200 words) This work investigates the application of evolutionary programming for automatically configuring neural network architectures for pattern classification tasks.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1117/12.162036">doi:10.1117/12.162036</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ggb2oks43fh4xh2pc6df6kte4u">fatcat:ggb2oks43fh4xh2pc6df6kte4u</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170927025007/http://www.dtic.mil/get-tr-doc/pdf?AD=ADA281181" 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/81/5a/815a2c3e9816510b8a2ab1ab138b96b6d984ea7e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1117/12.162036"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Stock Index Modeling Using Hierarchical Radial Basis Function Networks [chapter]

Yuehui Chen, Lizhi Peng, Ajith Abraham
<span title="">2006</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;
Empirical results indicate that the proposed method is better than the conventional neural network and RBF networks forecasting models.  ...  This paper proposes a Hierarchical Radial Basis Function Network (HiRBF) model for forecasting three major international currency exchange rates.  ...  Feature/Input Selection with HiRBF It is often a difficult task to select important variables for a forecasting or classification problem, especially when the feature space is large.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/11893011_51">doi:10.1007/11893011_51</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/aa4uei247fcxpio7bwnbrjilzi">fatcat:aa4uei247fcxpio7bwnbrjilzi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170809234051/http://isda2001.softcomputing.net/kes06_2.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/d0/85/d085ca2177611ceb7e1cc63cdd75ac18f9215a43.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/11893011_51"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Evolving granular classification neural networks

Daniel F. Leite, Pyramo Costa, Fernando Gomide
<span title="">2009</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/qm5nunzmyva4tfjekdcm34uvhq" style="color: black;">2009 International Joint Conference on Neural Networks</a> </i> &nbsp;
The suggested eGNN are neural models supported by granule-based learning algorithms whose aim is to tackle classification problems in continuously changing environments. eGNN are constructed from streams  ...  The objective of this study is to introduce the concept of evolving granular neural networks (eGNN) and to develop a framework of information granulation and its role in the online design of neural networks  ...  Experiments with Iris and Wine benchmark classification problems have shown that eGNN is competitive when compared against alternative nonlinear classification techniques.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/ijcnn.2009.5178895">doi:10.1109/ijcnn.2009.5178895</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/ijcnn/LeiteCG09.html">dblp:conf/ijcnn/LeiteCG09</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/57zfif4yencdtfkgpoayt5ed3e">fatcat:57zfif4yencdtfkgpoayt5ed3e</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200321035542/http://www.dca.fee.unicamp.br/~danfl7/Evolving_granular_classification_neural_networks.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/63/cd/63cdb29bb6fec8655e9fb4d231a896b7526a0916.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/ijcnn.2009.5178895"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Evolutionary Product-Unit Neural Networks for Classification [chapter]

F. J. Martínez-Estudillo, C. Hervás-Martínez, P. A. Gutiérrez Peña, A. C. Martínez-Estudillo, S. Ventura-Soto
<span title="">2006</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;
We propose a classification method based on a special class of feedforward neural network, namely product-unit neural networks.  ...  They are based on multiplicative nodes instead of additive ones, where the nonlinear basis functions express the possible strong interactions between variables.  ...  for classification problems, can be seen as different basis function models.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/11875581_157">doi:10.1007/11875581_157</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/kgaepo7bxrcodeimflfkzsubai">fatcat:kgaepo7bxrcodeimflfkzsubai</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20091223195712/http://sci2s.ugr.es/keel/pdf/keel/congreso/Evolutionary%20Product%20Units%20for%20Classification%20IDEAL.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/46/86/46866c7b5dba0bf4f4a7cf5b137f8535e0ce6e1b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/11875581_157"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Evolutionary discriminant analysis

A. Sierra, A. Echeverria
<span title="">2006</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dqtjwgdgmjazlimlppwouyrzcq" style="color: black;">IEEE Transactions on Evolutionary Computation</a> </i> &nbsp;
A nonlinear generalization of this procedure based on the hierarchical composition of linear projections is shown to solve the UCI thyroid problem with state of the art recognition rates.  ...  This allows to obtain two-dimensional renderings of data sets with more than three classes such as the 19 class UCI soybean problem.  ...  This is a clear advantage with respect to neural networks, for instance, which depend on output codes.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tevc.2005.856069">doi:10.1109/tevc.2005.856069</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/iuiwfkpw5bbxpmq73gek6cj3b4">fatcat:iuiwfkpw5bbxpmq73gek6cj3b4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20120124153426/http://arantxa.ii.uam.es/~asierra/papers/IEEETEC2006.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/49/52/495201e9bbc8122d11f8d4d7b0a2da2c724adaac.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tevc.2005.856069"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Evolutionary product-unit neural networks classifiers

F.J. Martínez-Estudillo, C. Hervás-Martínez, P.A. Gutiérrez, A.C. Martínez-Estudillo
<span title="">2008</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/bby322qx6ndsje4ypr56c7nnly" style="color: black;">Neurocomputing</a> </i> &nbsp;
This paper proposes a classification method based on a special class of feed-forward neural network, namely product-unit neural networks.  ...  The approach can be seen as nonlinear multinomial logistic regression where the parameters are estimated using evolutionary computation.  ...  Comparison with a cooperative co-evolutionary neural network method: COVNET In this section we compare our approach with COVNET, a new cooperative co-evolutionary model for evolving artificial neural networks  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.neucom.2007.11.019">doi:10.1016/j.neucom.2007.11.019</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xib2itilsvajjdq5yobxuyi5pi">fatcat:xib2itilsvajjdq5yobxuyi5pi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20120628233909/http://sci2s.ugr.es/keel/pdf/algorithm/articulo/EPUNN%20Classifiers.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/19/5d/195dfb84d5168f1042dd3a2932c9dc38f32e255a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.neucom.2007.11.019"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Pattern Recognition for the Electronic Phase of Bismuth Antimony Thin Films

Shuang Tang, College of Engineering, State University of New York Polytechnic Institute, Albany, NY, 12203, USA, Lucy Dow, Emmanuel Ojukwu, College of Engineering, State University of New York Polytechnic Institute, Albany, NY, 12203, USA, College of Engineering, State University of New York Polytechnic Institute, Albany, NY, 12203, USA
<span title="">2022</span> <i title="Engineered Science Publisher"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ijbouava65bo5gv7vfdxbfsaem" style="color: black;">ES Materials &amp; Manufacturing</a> </i> &nbsp;
Fortunately, with the development of pattern recognition technology, scientists can build many black-box tools for predicting various materials properties.  ...  The support vector machine, the decision tree, and the artificial neural network are used to achieve a prediction accuracy of ~90%, ~95% and ~100%, respectively.  ...  Acknowledge The author(s) acknowledge the Center for Computational Innovations at the Rensselaer Polytechnic Institute for providing the AIMOS supercomputer for our research and student training.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.30919/esmm5f661">doi:10.30919/esmm5f661</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5ied4fvfs5epjexrie2wq3vx5a">fatcat:5ied4fvfs5epjexrie2wq3vx5a</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220428093707/https://www.espublisher.com/uploads/article_pdf/esmm5f661.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/f2/e9/f2e9a86a40022f08f58a386f74a0e9c6da62bf40.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.30919/esmm5f661"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Novel optical neural network architecture with the temporal synthetic dimension [article]

Bo Peng, Shuo Yan, Dali Cheng, Danying Yu, Zhanwei Liu, Vladislav V. Yakovlev, Luqi Yuan, Xianfeng Chen
<span title="2021-01-21">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We validate the functionality of the proposed optical neural network using an example of a complicated wine classification problem.  ...  Such linear transformation can be arbitrarily controlled by applied modulation phases, which serve as the building block of the neural network together with a nonlinear component for pulses.  ...  A wine classification problem is a well-established example to test the validity of an artificial neural network.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2101.08439v1">arXiv:2101.08439v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/g6gm5ny4eng4tjhhk7l3jlrdiu">fatcat:g6gm5ny4eng4tjhhk7l3jlrdiu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210128101319/https://arxiv.org/pdf/2101.08439v1.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/d3/3a/d33a988c7f2965b013bb91c7736c5059413c04ea.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2101.08439v1" 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>

Guest Editorial: Deep Fuzzy Models

Alexander Gegov, Uzay Kaymak, Joao Miguel da Costa Sousa
<span title="">2020</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/7dwepyc5xbc47narcaqganu4vu" style="color: black;">IEEE transactions on fuzzy systems</a> </i> &nbsp;
The article "An Incremental Construction of Deep Neuro Fuzzy System for Continual Learning of Nonstationary Data Streams" proposes a deep evolving fuzzy neural network whose fuzzy rules can be automatically  ...  The article "A Deep Fuzzy Neural Network With Sparse Autoencoder for Emotional Intention Understanding in Human Robot Interaction" proposes a novel deep fuzzy neural network that uses fuzzy c-means for  ...  Sousa is an Associate Editor for the IEEE TRANSACTIONS ON FUZZY SYSTEMS, an Editor of Mathematics and Computers in Simulation and Member of the Editorial Board from Fuzzy Sets and Systems.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tfuzz.2020.2996512">doi:10.1109/tfuzz.2020.2996512</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/mofqtt7kufbp7hxwfyhh5oenpa">fatcat:mofqtt7kufbp7hxwfyhh5oenpa</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201108080252/https://ieeexplore.ieee.org/ielx7/91/9130783/09130630.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/cc/cf/cccffdf691600c5281a5d730407ed4fc90ad75aa.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tfuzz.2020.2996512"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Evolving Automatic Target Detection Algorithms by LogicallyCombining Decision Spaces

K Benson
<span title="">2000</span> <i title="British Machine Vision Association"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6bfo5625nvdfvbgyf7ldi5wmfe" style="color: black;">Procedings of the British Machine Vision Conference 2000</a> </i> &nbsp;
Discriminant functions are constructed by combining selected features from the feature set with simple mathematical functions such as · ¢ ¤ Ñ Ü Ñ Ò.  ...  For multimodal data more than one discriminant function may be combined with logical operators before classification is performed.  ...  Acknowledgements The author would like to thank David Booth, James Cubillo, and Colin Reeves for their support whilst carrying out this research; and Steve Foulkes for providing the imagery and ground  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5244/c.14.69">doi:10.5244/c.14.69</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/bmvc/Benson00.html">dblp:conf/bmvc/Benson00</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/agil23mabfeppkei2pdq27gm6a">fatcat:agil23mabfeppkei2pdq27gm6a</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20130528171616/http://www.bmva.org/bmvc/2000/papers/p69.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/f2/b3/f2b32d2a53d322ef2d6db9d1d50e20fd961d28c2.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5244/c.14.69"> <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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