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Machine learning and cognitive computing for mobile communications and wireless networks
Published 2020Full text (MFA users only)
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44
In the tradition of Ahlfors and Bers : proceedings of the First Ahlfors-Bers Colloquium, Ahlfors-Bers Colloquium, November 6-8, 1998, State University of New York at Stony Brook
Published 2000Table of Contents: “…Coverings of Cantor sets /…”
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Electronic Conference Proceeding eBook -
45
Komplexität : Design Strategy and World View.
Published 2008Table of Contents: “…ALGORITHMIC COMPLEXITY: OUT OF NOWHERE /…”
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The Evolution of Mathematics : A Rhetorical Approach
Published 2022Full text (MFA users only)
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Artificial neural networks in biological and environmental analysis
Published 2011Full text (MFA users only)
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Women in Numbers 2 : research directions in number theory : BIRS Workshop, WIN2 - Women in Numbers 2, November 6-11, 2011, Banff International Research Station, Banff, Alberta, Can...
Published 2013Full text (MFA users only)
Electronic Conference Proceeding eBook -
51
Dynamics and control of multibody systems : proceedings of the AMS-IMS-SIAM Joint Summer Research Conference held July 30-August 5, 1988, with support from the National Science Fou...
Published 1989Table of Contents: “…Slew-induced deformation shaping on slow integral manifolds /…”
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52
RF Positioning : Fundamentals, Applications, and Tools.
Published 2015Full text (MFA users only)
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The Princeton companion to mathematics
Published 2008Table of Contents: “…Algorithms ;…”
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When life is linear : from computer graphics to bracketology
Published 2015Full text (MFA users only)
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Satellite networking : principles and protocols
Published 2014Table of Contents: “…Traffic Shaping --…”
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Computational mechanics of discontinua
Published 2012Table of Contents: “…Front Matter -- Introduction to Mechanics of Discontinua -- Methods of Mechanics of Discontinua -- Disc to Edge Contact Interaction in 2D -- Triangle to Edge Contact Interaction in 2D -- Ball to Surface Contact Interaction in 3D -- Tetrahedron to Points Contact Interaction in 3D -- Tetrahedron to Triangle Contact Interaction in 3D -- Rock Joints -- MR Contact Detection Algorithm for Bodies of Similar Size -- MR Contact Detection Algorithm for Bodies of Different Sizes -- MR Contact Detection Algorithm for Complex Shapes in 2D -- MR Contact Detection Algorithm for Complex Shapes in 3D -- Parallelization.…”
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Artificial neural systems : principle and practice
Published 2015Table of Contents: “…INTRODUCTIONDENSITY BASED ALGORITHMS: CLUSTERING ALGORITHMS; NATURE-BASED ALGORITHMS; Evolutionary Algorithm and Programming ; Genetic Algorithm; GA Operators; APPLICATIONS OF GENETIC ALGORITHM; NETWORK METHOD: EDGES AND NODES; MULTI-LAYERED PERCEPTRON; REAL-TIME APPLICATIONS OF STATE-OF-THE-ART ANN SYSTEMS; DEFINITION OF ARTIFICIAL NEURAL NETWORKS (ANN); Intelligence; An Artificial Neural Network (ANN) system; PERFORMANCE MEASURES; Receiver's Operating Characteristics (ROC); Hypothesis Testing; Chi-squared (Goodness-of-fit) Test; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES…”
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Navigation signal processing for GNSS software receivers
Published 2010Full text (MFA users only)
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Machine learning : a Bayesian and optimization perspective
Published 2015Table of Contents: “…Probability and stochastic processes -- Learning in parametric modeling: basic concepts and directions -- Mean-square error linear estimation -- Stochastic gradient descent: the LMS algorithm -- The least-squares family -- Classification: a tour of the classics -- Parameter learning: a convex analytic path -- Sparsity-aware learning: concepts and theoretical foundations -- Sparcity-aware learning: algorithms and applications -- Learning in reproducing Kernel Hilbert spaces -- Bayesian learning: inference and the EM alogrithm -- Bayesian learning: approximate inference and nonparametric models -- Monte Carlo methods -- Probabilistic graphical models: Part I -- Probabilistic graphical models: Part II -- Particle filtering -- Neural networks and deep learning -- Dimensionality reduction -- Appendix A LInear algebra -- Appendix B Probability theory and statistics -- Appendix C Hints on constrained optimization.…”
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