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"A few short decades ago, we were informed by the smooth signals of analog television and radio; we communicated using our analog telephones; and we even computed with analog computers. Today our world is digital, built with zeros and ones. Why did this revolution occur? The Discrete Charm of the Machine explains, in an engaging and accessible manner, the varied physical and logical reasons behind this radical transformation. The spark of individual genius shines through this story of innovation: the stored program of Jacquard’s loom; Charles Babbage’s logical branching; Alan Turing’s brilliant abstraction of the discrete machine; Harry Nyquist’s foundation for digital signal processing; Claude Shannon’s breakthrough insights into the meaning of information and bandwidth; and Richard Feynman’s prescient proposals for nanotechnology and quantum computing. Ken Steiglitz follows the progression of these ideas in the building of our digital world, from the internet and artificial intelligence to the edge of the unknown. Are questions like the famous traveling salesman problem truly beyond the reach of ordinary digital computers? Can quantum computers transcend these barriers? Does a mysterious magical power reside in the analog mechanisms of the brain? Steiglitz concludes by confronting the moral and aesthetic questions raised by the development of artificial intelligence and autonomous robots. The Discrete Charm of the Machine examines why our information technology, the lifeblood of our civilization, became digital, and challenges us to think about where its future trajectory may lead." -- Publisher's description.

Digital communications. --- Technological innovations. --- Breakthroughs, Technological --- Innovations, Industrial --- Innovations, Technological --- Technical innovations --- Technological breakthroughs --- Technological change --- Creative ability in technology --- Inventions --- Domestication of technology --- Innovation relay centers --- Research, Industrial --- Technology transfer --- Communications, Digital --- Digital transmission --- Pulse communication --- Digital electronics --- Pulse techniques (Electronics) --- Telecommunication --- Digital media --- Signal processing --- Digital techniques --- Digital communications --- Technological innovations --- AND gate. --- Alan Turing. --- Algorithm. --- Analog computer. --- Analog device. --- Analog signal. --- Analog-to-digital converter. --- Artificial neural network. --- Autonomous robot. --- Bell's theorem. --- Calculation. --- Charles Babbage. --- Church–Turing thesis. --- Classical physics. --- Claude Shannon. --- Compact disc. --- Computation. --- Computer music. --- Computer program. --- Computer science. --- Computer scientist. --- Computer. --- Computing. --- Data transmission. --- Detection. --- Difference engine. --- Differential equation. --- Digital data. --- Digital electronics. --- Digital signal processing. --- Digital signal. --- Diode. --- Electrical network. --- Electricity. --- Electromagnetic radiation. --- Electronics. --- Exponential growth. --- Field-effect transistor. --- Fourier analysis. --- High frequency. --- Information theory. --- Instance (computer science). --- Instruction set. --- Integrated circuit. --- Integrator. --- Isaac Asimov. --- Johnson–Nyquist noise. --- Laptop. --- Laughter. --- Logarithm. --- Low frequency. --- Mathematician. --- Mathematics. --- Measurement. --- Microphone. --- Microphotograph. --- Microscope. --- Molecule. --- Moore's law. --- NP-completeness. --- Optical fiber. --- P versus NP problem. --- Patch panel. --- Photograph. --- Photon. --- Physicist. --- Probability. --- Processing (programming language). --- Proportionality (mathematics). --- Punched card. --- Quantity. --- Quantum computing. --- Quantum mechanics. --- Radio wave. --- Resistor. --- Result. --- Retransmission (data networks). --- Richard Feynman. --- Scientist. --- Semiconductor. --- Shot noise. --- Silicon. --- Simulation. --- Solid-state electronics. --- Sound recording and reproduction. --- Standardization. --- Technology. --- Television. --- Theorem. --- Theoretical computer science. --- Time complexity. --- Transistor. --- Turing machine. --- Uncertainty. --- Vacuum tube. --- Vacuum. --- Video. --- Wafer (electronics). --- Wave–particle duality. --- Your Computer (British magazine).

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Robust optimization is still a relatively 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. Written by the principal developers of robust optimization, and describing the main achievements of a decade of research, this is the first book to provide a comprehensive and up-to-date account of the subject. Robust optimization is designed to meet some major challenges associated with uncertainty-affected optimization problems: to operate under lack of full information on the nature of uncertainty; to model the problem in a form that can be solved efficiently; and to provide guarantees about the performance of the solution. The book starts with a relatively simple treatment of uncertain linear programming, proceeding with a deep analysis of the interconnections between the construction of appropriate uncertainty sets and the classical chance constraints (probabilistic) approach. It then develops the robust optimization theory for uncertain conic quadratic and semidefinite optimization problems and dynamic (multistage) problems. The theory is supported by numerous examples and computational illustrations. An essential book for anyone working on optimization and decision making under uncertainty, Robust Optimization also makes an ideal graduate textbook on the subject.

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.