Listing 1 - 5 of 5 |
Sort by
|
Choose an application
This book commemorates Solomon Marcus’s fifth death anniversary with a selection of articles in mathematics, theoretical computer science, and physics written by authors who work in Marcus’s research fields, some of whom have been influenced by his results and/or have collaborated with him.
Information technology industries --- Computer science --- automata theory --- formal language theory --- bio-informatics --- recursive function theory --- evolutionary processor --- network of evolutionary processors --- network topology --- theory of computation --- computational models --- intrinsic perception --- Hausdorff dimension --- fractal --- computational complexity --- Turing machine --- oracle Turing machine --- shortest computations --- quasiperiod --- formal language --- asymptotic growth --- polynomial --- membrane computing --- computational complexity theory --- P vs. NP problem --- evolutional communication --- symport/antiport --- Kolmogorov complexity --- random strings --- extractors --- finite languages --- deterministic finite cover automata --- multiple entry automata --- automata with “do not care” symbols --- similarity relations --- process calculus --- communication patterns --- control structures --- hypergraph model --- P systems --- cP systems --- NP-complete --- NP-hard --- SAT --- logarithmic time complexity
Choose an application
This book commemorates Solomon Marcus’s fifth death anniversary with a selection of articles in mathematics, theoretical computer science, and physics written by authors who work in Marcus’s research fields, some of whom have been influenced by his results and/or have collaborated with him.
automata theory --- formal language theory --- bio-informatics --- recursive function theory --- evolutionary processor --- network of evolutionary processors --- network topology --- theory of computation --- computational models --- intrinsic perception --- Hausdorff dimension --- fractal --- computational complexity --- Turing machine --- oracle Turing machine --- shortest computations --- quasiperiod --- formal language --- asymptotic growth --- polynomial --- membrane computing --- computational complexity theory --- P vs. NP problem --- evolutional communication --- symport/antiport --- Kolmogorov complexity --- random strings --- extractors --- finite languages --- deterministic finite cover automata --- multiple entry automata --- automata with “do not care” symbols --- similarity relations --- process calculus --- communication patterns --- control structures --- hypergraph model --- P systems --- cP systems --- NP-complete --- NP-hard --- SAT --- logarithmic time complexity
Choose an application
This book commemorates Solomon Marcus’s fifth death anniversary with a selection of articles in mathematics, theoretical computer science, and physics written by authors who work in Marcus’s research fields, some of whom have been influenced by his results and/or have collaborated with him.
Information technology industries --- Computer science --- automata theory --- formal language theory --- bio-informatics --- recursive function theory --- evolutionary processor --- network of evolutionary processors --- network topology --- theory of computation --- computational models --- intrinsic perception --- Hausdorff dimension --- fractal --- computational complexity --- Turing machine --- oracle Turing machine --- shortest computations --- quasiperiod --- formal language --- asymptotic growth --- polynomial --- membrane computing --- computational complexity theory --- P vs. NP problem --- evolutional communication --- symport/antiport --- Kolmogorov complexity --- random strings --- extractors --- finite languages --- deterministic finite cover automata --- multiple entry automata --- automata with “do not care” symbols --- similarity relations --- process calculus --- communication patterns --- control structures --- hypergraph model --- P systems --- cP systems --- NP-complete --- NP-hard --- SAT --- logarithmic time complexity --- automata theory --- formal language theory --- bio-informatics --- recursive function theory --- evolutionary processor --- network of evolutionary processors --- network topology --- theory of computation --- computational models --- intrinsic perception --- Hausdorff dimension --- fractal --- computational complexity --- Turing machine --- oracle Turing machine --- shortest computations --- quasiperiod --- formal language --- asymptotic growth --- polynomial --- membrane computing --- computational complexity theory --- P vs. NP problem --- evolutional communication --- symport/antiport --- Kolmogorov complexity --- random strings --- extractors --- finite languages --- deterministic finite cover automata --- multiple entry automata --- automata with “do not care” symbols --- similarity relations --- process calculus --- communication patterns --- control structures --- hypergraph model --- P systems --- cP systems --- NP-complete --- NP-hard --- SAT --- logarithmic time complexity
Choose an application
This self-contained introduction to the distributed control of robotic networks offers a distinctive blend of computer science and control theory. The book presents a broad set of tools for understanding coordination algorithms, determining their correctness, and assessing their complexity; and it analyzes various cooperative strategies for tasks such as consensus, rendezvous, connectivity maintenance, deployment, and boundary estimation. The unifying theme is a formal model for robotic networks that explicitly incorporates their communication, sensing, control, and processing capabilities--a model that in turn leads to a common formal language to describe and analyze coordination algorithms. Written for first- and second-year graduate students in control and robotics, the book will also be useful to researchers in control theory, robotics, distributed algorithms, and automata theory. The book provides explanations of the basic concepts and main results, as well as numerous examples and exercises. Self-contained exposition of graph-theoretic concepts, distributed algorithms, and complexity measures for processor networks with fixed interconnection topology and for robotic networks with position-dependent interconnection topology Detailed treatment of averaging and consensus algorithms interpreted as linear iterations on synchronous networks Introduction of geometric notions such as partitions, proximity graphs, and multicenter functions Detailed treatment of motion coordination algorithms for deployment, rendezvous, connectivity maintenance, and boundary estimation
Robotics. --- Computer algorithms. --- Robots --- Automation --- Machine theory --- Robot control --- Robotics --- Algorithms --- Control systems. --- Computer algorithms --- Control systems --- 1-center problem. --- Adjacency matrix. --- Aggregate function. --- Algebraic connectivity. --- Algebraic topology (object). --- Algorithm. --- Analysis of algorithms. --- Approximation algorithm. --- Asynchronous system. --- Bellman–Ford algorithm. --- Bifurcation theory. --- Bounded set (topological vector space). --- Calculation. --- Cartesian product. --- Centroid. --- Chebyshev center. --- Circulant matrix. --- Circumscribed circle. --- Cluster analysis. --- Combinatorial optimization. --- Combinatorics. --- Communication complexity. --- Computation. --- Computational complexity theory. --- Computational geometry. --- Computational model. --- Computer simulation. --- Computer vision. --- Connected component (graph theory). --- Connectivity (graph theory). --- Consensus (computer science). --- Control function (econometrics). --- Differentiable function. --- Dijkstra's algorithm. --- Dimensional analysis. --- Directed acyclic graph. --- Directed graph. --- Discrete time and continuous time. --- Disk (mathematics). --- Distributed algorithm. --- Doubly stochastic matrix. --- Dynamical system. --- Eigenvalues and eigenvectors. --- Estimation. --- Euclidean space. --- Function composition. --- Hybrid system. --- Information theory. --- Initial condition. --- Instance (computer science). --- Invariance principle (linguistics). --- Invertible matrix. --- Iteration. --- Iterative method. --- Kinematics. --- Laplacian matrix. --- Leader election. --- Linear dynamical system. --- Linear interpolation. --- Linear programming. --- Lipschitz continuity. --- Lyapunov function. --- Markov chain. --- Mathematical induction. --- Mathematical optimization. --- Mobile robot. --- Motion planning. --- Multi-agent system. --- Network model. --- Network topology. --- Norm (mathematics). --- Numerical integration. --- Optimal control. --- Optimization problem. --- Parameter (computer programming). --- Partition of a set. --- Percolation theory. --- Permutation matrix. --- Polytope. --- Proportionality (mathematics). --- Quantifier (logic). --- Quantization (signal processing). --- Robustness (computer science). --- Scientific notation. --- Sensor. --- Set (mathematics). --- Simply connected space. --- Simulation. --- Simultaneous equations. --- State space. --- State variable. --- Stochastic matrix. --- Stochastic. --- Strongly connected component. --- Synchronous network. --- Theorem. --- Time complexity. --- Topology. --- Variable (mathematics). --- Vector field.
Choose an application
Robust optimization is a fairly new approach to optimization problems affected by uncertainty, but it has already proved so useful in real applications that it is difficult to tackle such problems today without considering this powerful methodology. The authors are the principal developers of robust optimization.
Robust optimization. --- Linear programming. --- 519.8 --- 681.3*G16 --- 681.3*G16 Optimization: constrained optimization; gradient methods; integer programming; least squares methods; linear programming; nonlinear programming (Numericalanalysis) --- Optimization: constrained optimization; gradient methods; integer programming; least squares methods; linear programming; nonlinear programming (Numericalanalysis) --- 519.8 Operational research --- Operational research --- Robust optimization --- Linear programming --- Optimisation robuste --- Programmation linéaire --- Optimization, Robust --- RO (Robust optimization) --- Mathematical optimization --- Production scheduling --- Programming (Mathematics) --- 0O. --- Accuracy and precision. --- Additive model. --- Almost surely. --- Approximation algorithm. --- Approximation. --- Best, worst and average case. --- Bifurcation theory. --- Big O notation. --- Candidate solution. --- Central limit theorem. --- Chaos theory. --- Coefficient. --- Computational complexity theory. --- Constrained optimization. --- Convex hull. --- Convex optimization. --- Convex set. --- Cumulative distribution function. --- Curse of dimensionality. --- Decision problem. --- Decision rule. --- Degeneracy (mathematics). --- Diagram (category theory). --- Duality (optimization). --- Dynamic programming. --- Exponential function. --- Feasible region. --- Floor and ceiling functions. --- For All Practical Purposes. --- Free product. --- Ideal solution. --- Identity matrix. --- Inequality (mathematics). --- Infimum and supremum. --- Integer programming. --- Law of large numbers. --- Likelihood-ratio test. --- Linear dynamical system. --- Linear inequality. --- Linear map. --- Linear matrix inequality. --- Linear regression. --- Loss function. --- Margin classifier. --- Markov chain. --- Markov decision process. --- Mathematical optimization. --- Max-plus algebra. --- Maxima and minima. --- Multivariate normal distribution. --- NP-hardness. --- Norm (mathematics). --- Normal distribution. --- Optimal control. --- Optimization problem. --- Orientability. --- P versus NP problem. --- Pairwise. --- Parameter. --- Parametric family. --- Probability distribution. --- Probability. --- Proportionality (mathematics). --- Quantity. --- Random variable. --- Relative interior. --- Robust control. --- Robust decision-making. --- Semi-infinite. --- Sensitivity analysis. --- Simple set. --- Singular value. --- Skew-symmetric matrix. --- Slack variable. --- Special case. --- Spherical model. --- Spline (mathematics). --- State variable. --- Stochastic calculus. --- Stochastic control. --- Stochastic optimization. --- Stochastic programming. --- Stochastic. --- Strong duality. --- Support vector machine. --- Theorem. --- Time complexity. --- Uncertainty. --- Uniform distribution (discrete). --- Unimodality. --- Upper and lower bounds. --- Variable (mathematics). --- Virtual displacement. --- Weak duality. --- Wiener filter. --- With high probability. --- Without loss of generality.
Listing 1 - 5 of 5 |
Sort by
|