Maximum Entropy and Bayesian Methods: Fundamental Theories of Physics, cartea 43
Editat de W. T. Grandy Jr., L. H. Schicken Limba Engleză Paperback – 14 oct 2012
Din seria Fundamental Theories of Physics
-
Preț: 411.54 lei - 18%
Preț: 884.80 lei - 18%
Preț: 759.85 lei - 18%
Preț: 922.77 lei - 18%
Preț: 917.68 lei - 18%
Preț: 914.07 lei - 18%
Preț: 1186.68 lei - 18%
Preț: 1193.85 lei - 18%
Preț: 908.76 lei -
Preț: 384.28 lei - 18%
Preț: 921.71 lei - 18%
Preț: 1198.17 lei - 18%
Preț: 921.50 lei - 18%
Preț: 920.13 lei - 18%
Preț: 915.44 lei - 15%
Preț: 625.77 lei - 18%
Preț: 1189.05 lei - 18%
Preț: 962.19 lei - 18%
Preț: 913.84 lei - 20%
Preț: 623.48 lei - 15%
Preț: 620.87 lei -
Preț: 379.08 lei - 18%
Preț: 753.83 lei -
Preț: 380.05 lei - 15%
Preț: 627.14 lei -
Preț: 386.04 lei - 24%
Preț: 639.70 lei - 15%
Preț: 623.88 lei - 18%
Preț: 1183.93 lei - 18%
Preț: 916.95 lei - 15%
Preț: 626.99 lei -
Preț: 381.51 lei - 18%
Preț: 920.55 lei
Preț: 916.39 lei
Preț vechi: 1117.55 lei
-18%
Puncte Express: 1375
Carte tipărită la comandă
Livrare economică 13-27 iulie
Livrare prin curier în România Termenul estimat este afișat lângă disponibilitate.
Transport gratuit pentru acest produs Plată online sau ramburs, în funcție de opțiunile comenzii.
Retur gratuit în 14 zile Comandă securizată și suport în română.
Specificații
ISBN-13: 9789401055314
ISBN-10: 9401055319
Pagini: 388
Ilustrații: XII, 371 p.
Dimensiuni: 155 x 235 x 21 mm
Greutate: 0.59 kg
Ediția:Softcover reprint of the original 1st ed. 1991
Editura: Springer
Colecția Fundamental Theories of Physics
Seria Fundamental Theories of Physics
Locul publicării:Dordrecht, Netherlands
ISBN-10: 9401055319
Pagini: 388
Ilustrații: XII, 371 p.
Dimensiuni: 155 x 235 x 21 mm
Greutate: 0.59 kg
Ediția:Softcover reprint of the original 1st ed. 1991
Editura: Springer
Colecția Fundamental Theories of Physics
Seria Fundamental Theories of Physics
Locul publicării:Dordrecht, Netherlands
Public țintă
ResearchCuprins
Notes on Present Status and Future Prospects.- Bayesian Methods and Entropy in Economics and Econometrics.- The Role of Priors in Active Bayesian Learning in the Sequential Statistical Decision Framework.- The Principle of Maximum Entropy and the Difference Between Risk and Uncertainty.- Analysis of Lunar Occultation Data.- The Photometric Accuracy of Astronomical Images Restored with the MEMSYS3 Code.- Computational Problems and Signal Processing in SETI.- Maximum Entropy in Condensed Matter Theory.- Entropy Maximization in Nuclear Physics.- Applications of Maxent to Quantum Monte Carlo.- Maximum Entropy Applications in Radar.- The Application of Maximum Entropy Signal Processing to Ultrasonic Surface Parameterisation.- Steel Characterization using Bayesian Analysis of Barkhausen Noise.- Bayesian Spectral Analysis of Reflectivity Data.- On the Assignment of Prior Expectation Values and a Geometric Means of Maximizing — Tr?ln#x03C1; Constrained by Measured Expectation Values.- The Evaluation and Predictive Properties of the “MemSys3” Algorithm.- The Evolution of Our Probability Image for the Spin Orientation of a Spin-1/2 — Ensemble As Measurements Are Made on Several Members of the Ensemble — Connections with Information Theory and Bayesian Statistics.- Stochasticity in Nature, and Its Consequences.- Reasoning with Maximum Entropy in Expert Systems.- Some Applications of the Bayesian, Maximum-Entropy Concept in Geostatistics.- Maximum Entropy Image Reconstruction of DNA Sequencing Data.- Maximum Entropy Connections: Neural Networks.- Quantifying Drug Absorption.- Energy Flow-Networks and the Maximum Entropy Formalism.- On Parameter Estimation and Quantified Maxent.- A Subpixel Deconvolution Method for Astronomical Images.- Maximum Entropy Prior Laws ofImages and Estimation of their Parameters.- Two New Methods for Retrieving an Image from Noisy, Incomplete Data, and Comparison with the Cambridge Maxent Package.- Rayleigh Task Performance as A Method To Evaluate Image Reconstruction Algorithms.- Maximum Entropy Image Construction of the Galaxy M51.- The Image Reconstruction Contest.- Moment Estimation using Bayesian Probability Theory.- Maximum Entropy with Poisson Statistics.- From Euclid to Entropy.- Bayesian Interpolation.- Ockham’s Razor.- Probabilistic Displays.