Search Results - (((((((want OR wantis) OR semantic) OR find) OR cantor) OR anne) OR plane) OR hints) algorithms.

Handbook of Mathematical Induction. by Gunderson, David S.

Table of Contents: “…Chapter 14: Logic and languageChapter 15: Graphs; Chapter 16: Recursion and algorithms; Chapter 17: Games and recreations; Chapter 18: Relations and functions; Chapter 19: Linear and abstract algebra; Chapter 20: Geometry; Chapter 21: Ramsey theory; Chapter 22: Probability and statistics; Part III: Solutions and hints to exercises; Chapter 23: Solutions: Foundations; Chapter 24: Solutions: Inductive techniques applied to the infinite; Chapter 25: Solutions: Paradoxes and sophisms; Chapter 26: Solutions: Empirical induction; Chapter 27: Solutions: Identities.…”
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Inflectionary Invariants for Isolated Complete Intersection Curve Singularities. by Patel, Anand P., Swaminathan, Ashvin A.

Table of Contents: “…The Case of Cusps -- 5.2. An Algorithm for Finding a Basis of ^{ }( )^{∨} -- 5.3. …”
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Geometric Computation. by Chen, Falai

Table of Contents: “…Algebraic Plane Curves ; 3. Rational Plane Curves ; 4. Parametrization of Rational Plane Curves ; 5. …”
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Delaunay mesh generation by Cheng, Siu-Wing

Table of Contents: “…Front Cover; Contents; Preface; Chapter 1: Introduction; Chapter 2: Two-dimensional Delaunay triangulations; Chapter 3: Algorithms for constructing Delaunay triangulations; Chapter 4: Three-dimensional Delaunay triangulations; Chapter 5: Algorithms for constructing Delaunay triangulations in; Chapter 6: Delaunay refinement in the plane; Chapter 7: Voronoi diagrams and weighted complexes; Chapter 8: Tetrahedral meshing of PLCs; Chapter 9: Weighted Delaunay refinement for PLCs with small angles; Chapter 10: Sliver exudation; Chapter 11: Refinement for sliver exudation.…”
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Artificial neural systems : principle and practice by Lorrentz, Pierre

Table 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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Radio Propagation in the Urban Scenario. by Franceshetti, Giorgio

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Digital journalism, drones, and automation : the language and abstractions behind the news by Dowd, Cate

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In pursuit of the traveling salesman : mathematics at the limits of computation by Cook, William, 1957-

Table of Contents: “…General-purpose model -- The simplex algorithm -- Two for the price of one: LP duality -- The degree LP relaxation of the TSP -- Eliminating subtours -- A perfect relaxation -- Integer programming -- Operations research -- Cutting planes. …”
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A first course in combinatorial optimization by Lee, Jon, 1960-

Table of Contents: “…Flows and Cuts -- 6. Cutting Planes -- 7. Branch- & -Bound -- 8. Optimizing Submodular Functions.…”
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Generative design by Agkathidis, Asterios, 1974-

Table of Contents: “…Intro; 1.0 Introduction to Generative Design; 2.0 Continuous Surfaces; 3.0 Modularity and Accumulation; 4.0 Deformation and Subtraction; 5.0 Algorithmic Patterns; 6.0 Triangulation ; 7.0 Conclusion: The Digital Vs Physical Debate ; Bibliography ; Index; Picture Credits; Acknowledgements; 1.1 Design methods in architecture: A brief review; 1.2 Generative form-finding processes; 1.3 The approach of this book; 2.1 Soft mesh; 2.2 Double-curved shells; 2.3 Hyper paraboloids; 3.1 Interlocking units; 3.2 Irregular units; 4.1 Twisted block; 4.2 Porous space; 5.1 Tessellated planes…”
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Artificial intelligence with Python : build real-world artificial intelligence applications with Python to intelligently interact with the world around you by Joshi, Prateek

Table of Contents: “…; Clustering data with K-Means algorithm; Estimating the number of clusters with Mean Shift algorithm; Estimating the quality of clustering with silhouette scores; What are Gaussian Mixture Models?…”
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Emitter detection and geolocation for electronic warfare by O'Donoughue, Nicholas A.

Table of Contents: “…7.3 DOPPLER-BASED DIRECTION FINDING -- 7.3.1 Formulation -- 7.3.2 Implementation -- 7.3.3 Performance -- 7.4 PHASE INTERFEROMETRY -- 7.4.1 Implementation -- 7.4.2 Performance -- 7.4.3 Resolving Ambiguities with Multiple Baselines -- 7.5 PERFORMANCE COMPARISON -- 7.6 MONOPULSE DIRECTION FINDING -- 7.6.1 Performance -- 7.7 PROBLEM SET -- References -- Chapter 8 Array-Based AOA -- 8.1 BACKGROUND -- 8.1.1 Nonstandard Array Configurations -- 8.2 FORMULATION -- 8.2.1 Multiple PlaneWaves -- 8.2.2 Wideband Signals -- 8.2.3 Array Beamforming -- 8.2.4 Nonisotropic Element Patterns…”
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An introduction to computational engineering with Matlab by Yang, Xin-She

Table of Contents: “…9.2.2 Plane Stress and Plane Strain9.2.3 Implementation -- 10. …”
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Navigation signal processing for GNSS software receivers by Pany, Thomas

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Mastering machine learning with scikit-learn : learn to implement and evaluate machine learning solutions with scikit-learn by Hackeling, Gavin

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Machine learning : a Bayesian and optimization perspective by Theodoridis, Sergios, 1951-

Table 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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Stairs 2006 : Proceedings of the Third Starting AI Researchers' Symposium

Table of Contents: “…Binarization Algorithms for Approximate Updating in Credal NetsOn Generalizing the AGM Postulates; The Two-Variable Situation Calculus; Base Belief Change and Optimized Recovery; Unsupervised Word Sense Disambiguation Using the WWW; Relational Descriptive Analysis of Gene Expression Data; Solving Fuzzy PERT Using Gradual Real Numbers; Approaches to Efficient Resource-Constrained Project Rescheduling; A Comparison of Web Service Interface Similarity Measures; Finding Alternatives Web Services to Parry Breakdowns; Posters; Smart Ride Seeker Introductory Plan…”
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Python unlocked : become more fluent in Python--learn strategies and techniques for smart and high-performance Python programming by Tigeraniya, Arun

Table of Contents: “…Method resolution orderSuper's superpowers; Using language protocols in classes; Iteration protocol; Context manager protocol; Using abstract classes; Summary; Chapter 3: Functions and Utilities; Defining functions; Decorating callables; Utilities; Summary; Chapter 4: Data Structures and Algorithms; Python built-in data structures; Python library data structures; Third party data structures; Arrays/List; Binary tree; Sorted containers; Trie; Algorithms on scale; Summary; Chapter 5: Elegance with Design Patterns; Observer pattern; Strategy pattern; Singleton pattern; Template pattern.…”
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Learning Boost C++ libraries : solve practical programming problems using powerful, portable, and expressive libraries from Boost by Mukherjee, Arindam

Table of Contents: “…Shared ownership semanticsboost::shared_ptr and std::shared_ptr; Intrusive smart pointers -- boost::intrusive_ptr; shared_array; Managing non-memory resources using smart pointers; Self-test questions; Summary; References; Chapter 4: Working with Strings; Text processing with Boost String Algorithms library; Using Boost String Algorithms; Find algorithms; Case-conversion and trimming algorithms; The replace and erase algorithms; The split and join algorithms; Splitting text using the Boost Tokenizer library; Tokenizing based on separators…”
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Modeling Reality : How Computers Mirror Life. by Białynicki-Birula, Iwo

Table of Contents: “…Contents; 1 From building blocks to computers: Models and modeling; 2 The game of life: A legendary cellular automaton; 3 Heads or tails: Probability of an event; 4 Galton's board: Probability and statistics; 5 Twenty questions: Probability and information; 6 Snowflakes: The evolution of dynamical systems; 7 The Lorenz butterfly: Deterministic chaos; 8 From Cantor to Mandelbrot: Self-similarity and fractals; 9 Typing monkeys: Statistical linguistics; 10 The bridges of Königsberg: Graph theory; 11 Prisoner's dilemma: Game theory; 12 Let the best man win: Genetic algorithms.…”
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