3,741 resources related to Backpropagation
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2013 12th IEEE International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)
Cognitive Informatics (CI) is a cutting-edge and multidisciplinary research field that tackles the fundamental problems shared by modern informatics, computing, AI, cybernetics, computational intelligence, cognitive science, intelligence science, neuropsychology, brain science, systems science, software engineering, knowledge engineering, cognitive robots, scientific philosophy, cognitive linguistics, life sciences, and cognitive computing.
2013 15th International Conference on Transparent Optical Networks (ICTON)
ICTON addresses applications of transparent and all optical technologies in telecommunication networks, systems, and components. ICTON topics are well balanced between basic optics and network engineering. Interactions between those two groups of professionals are a valuable merit of conference. ICTON combines high level invited talks with carefully selected regular submissions.
2013 26th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)
This is a general Electrical and Computer Engineering Conference which encompasses all aspects of these fields.
2013 International Joint Conference on Neural Networks (IJCNN 2013 - Dallas)
Both general and technical articles on current technologies and methods used in biomedical and clinical engineering; societal implications of medical technologies; current news items; book reviews; patent descriptions; and correspondence. Special interest departments, students, law, clinical engineering, ethics, new products, society news, historical features and government.
Devoted to the science and technology of neural networks, which disclose significant technical knowledge, exploratory developments, and applications of neural networks from biology to software to hardware. Emphasis is on artificial neural networks.
Fieno, T.E.; Viswanathan, V.; Tsoukalas, L.H. Information Intelligence and Systems, 1999. Proceedings. 1999 International Conference on, 1999
A neural network was developed for the purpose of automating the identification of skeletal structures of chemical compounds using 1 H Nuclear Magnetic Resonance (NMR) spectroscopy signals. The neural net developed was a three-layer, feed forward network using 21 hidden layer neurons. Backpropagation of error was used to train the network with a database of 93 chemical compounds. The inputs ...
Chi-jie Lu; Chih-Hsiang Chang; Chien-Yu Chen; Chih-Chou Chiu; Tian-Shyug Lee Industrial Engineering and Engineering Management, 2009. IEEM 2009. IEEE International Conference on, 2009
Stock index prediction seems to be a challenging task of the financial time series prediction process especially in emerging markets with their complex and inefficient structures. Multivariate adaptive regression splines (MARS) is a nonlinear and non-parametric regression methodology and has been successfully used in classification tasks. However, there are few applications using MARS in stock index prediction. In this study, ...
Cho, S.; Reggia, J.A. Neural Networks, 1992. IJCNN., International Joint Conference on, 1992
As the angle of gaze changes, so does the retinal location of the visual image of a stationary object. Since the object is correctly perceived as stationary, the retinopic coordinates of the object have been transformed into craniotopic coordinates somehow using eye position information. Neurons in area 7a of posterior parietal cortex in macaque monkeys are thought to contribute to ...
Rawtani, L.; Rana, J.L.; Tiwari, A.K. Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on, 2001
Scientific knowledge is often available in handbooks and journals in the form of curves. ANN representation of curves is necessary for including them in the knowledge base of a connectionist expert system. Apart from one input node and one output node, representing abscissa and ordinate of the curve, respectively, the ANN has a hidden layer with s neurons, with sigmoid ...
Parker, K.K.; Wikswo, John P. Engineering in Medicine and Biology Society, 1995., IEEE 17th Annual Conference, 1995
We have applied an artificial neural network (ANN) using the backpropagation learning algorithm to the biomagnetic inverse problem. A forward model was used to calculate the magnetic fields from propagating action potentials (APs) as would be seen in nerve or muscle bundles. This forward model depicted two design schemes of a high-resolution SQUID magnetometer, whose three pickup coils were in ...
Gori, Marco Introduction to Multilayer Perceptrons, 2009
The course introduces multilayer perceptrons in a self-contained way by providing motivations, architectural issues, and the main ideas behind the Backpropagation learning algorithm. In addition, the course shows how multilayer perceptrons can be successfully used in real-world applications
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