Fundamentals of Artificial Neural Networks

Keywords

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References

• Introduction to artificial neural systemsJacek M. Żurada — 1992
• The Mathematical Foundations of Learning MachinesNils J. Nilsson — 1990
• A Scaled Conjugate Gradient Algorithm for Fast Supervised LearningMartin F. Møller — 1990
• The capacity of the Hopfield associative memoryRobert J. McEliece, Edward C. Posner, E. R. Rodemich — 1987
• Completely integrable gradient systems on the manifolds of Gaussian and multinomial distributionsYoshimasa Nakamura — 1993
• Numerical methods of solving some operational research problemsYu. G. Evtushenko, V. G. Zhadan — 1973
• Completely integrable gradient flowsAnthony M. Bloch, Roger W. Brockett, Tudor S. Raţiu — 1992
• Hamiltonian structure of dynamical systems which solve linear programming problemsLeonid Faybusovich — 1991
• Neural Networks: A Comprehensive FoundationSimon Haykin — 1998
• Dynamical systems that sort lists, diagonalize matrices, and solve linear programming problemsR. Brockett — 1991
• Geometrical and Statistical Properties of Systems of Linear Inequalities with Applications in Pattern RecognitionThomas M. Cover — 1965
• What Size Net Gives Valid Generalization?Eric B. Baum, David Haussler — 1989
• Introduction to the theory of neural computationJohn Hertz, Anders Krogh, Richard Palmer — 1994

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• Extracting bb Higgs Decay Signals using Multivariate TechniquesUSDOE Office of Science (SC), W. Smith, George Washington Univ., Washington, DC (United States) — 2012
• APPLICATION OF NEURAL GENERATED ERROR SIGNAL IN CLASSIFICATION AND COMPRESSION OF ECGBEATSRaed Abu Zitar — 2002
• Toward the discrimination of early melanoma from common and dysplastic nevus using fiber optic diffuse reflectance spectroscopy.C Harmey, C Hemat — 2005
• Application of artificial neural network – genetic algorithm in inferential estimation and control of a distillation columnWah Sit Chen — 2005
• Improving the perforce of differential competitive learning model in clustering tasksGuilherme A. Barreto, A.F.R. Araujo — 1998
• Blood pressure waveform characteristics exposed by spectral analysis and neural netsA. Prentza — 1997
• A Comparative Study of Artificial Neural Networks and Support Vector Machine for Fault DiagnosisAzam Baheiraei, Fatemeh Bakouei, Eesa Mohammadi — 2013
• A New Conceptual Automated Property Valuation Model for Residential Housing MarketDat-Nguyen Vo — 2014
• Control of a differentially driven mobile robot using radial basis function based neural networksGökhan Bayar, Erhan İlhan Konukseven, Ahmet Buğra Koku — 2008
• An investigation of artificial neural networks applied to pairs trading inSouth AfricaRichard Buhr — 2014
• Neural identification for critical flutter load of a polar-orthotropic annular plateIchiro Takahashi — 2001
• REALTIME GUIDANCE FOR FLASH FLOOD RISK MANAGEMENTMarco Borga — 2009
• A study about fraud detection and the implementation of SUSPECT - Supervised and UnSuPervised Erlang Classifier ToolAlexander Lindholm — 2014
• Cardiac Condition Detection using Artificial Neural NetworksSean Franklin, Joseph Wallcave — 2013
• Fixture-Based Design Similarity Measures for Variant Fixture PlanningSundar Balasubramanian — 1999
• A Data Mining Approach in the Analysis of the Weight Space of Multilayer Perceptron Solving Complex Real World TasksStavros P. Adam, D.A. Karras, Michael N. Vrahatis — 2009

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