Maximum Entropy and Bayesian Methods
Editat de John Skilling, Sibusio Sibisien Limba Engleză Hardback – 31 iul 1996
| Toate formatele și edițiile | Preț | Express |
|---|---|---|
| Paperback (1) | 1173.73 lei 6-8 săpt. | |
| Springer – 20 sep 2011 | 1173.73 lei 6-8 săpt. | |
| Hardback (1) | 1178.09 lei 6-8 săpt. | |
| Springer – 31 iul 1996 | 1178.09 lei 6-8 săpt. |
Preț: 1178.09 lei
Preț vechi: 1436.70 lei
-18% Nou
Puncte Express: 1767
Preț estimativ în valută:
208.44€ • 242.83$ • 182.02£
208.44€ • 242.83$ • 182.02£
Carte tipărită la comandă
Livrare economică 17-31 ianuarie 26
Preluare comenzi: 021 569.72.76
Specificații
ISBN-13: 9780792334521
ISBN-10: 0792334523
Pagini: 340
Ilustrații: XI, 323 p.
Dimensiuni: 160 x 241 x 23 mm
Greutate: 0.68 kg
Ediția:1996
Editura: Springer
Locul publicării:Dordrecht, Netherlands
ISBN-10: 0792334523
Pagini: 340
Ilustrații: XI, 323 p.
Dimensiuni: 160 x 241 x 23 mm
Greutate: 0.68 kg
Ediția:1996
Editura: Springer
Locul publicării:Dordrecht, Netherlands
Public țintă
ResearchCuprins
Applications.- Flow and diffusion images from Bayesian spectral analysis of motion-encoded NMR data.- Bayesian estimation of MR images from incomplete raw data.- Quantified maximum entropy and biological EPR spectra.- The vital importance of prior information for the decomposition of ion scattering spectroscopy data.- Bayesian consideration of the tomography problem.- Using MaxEnt to determine nuclear level densities.- A fresh look at model selection in inverse scattering.- The maximum entropy method in small-angle scattering.- Maximum entropy multi-resolution EM tomography by adaptive subdivision.- High resolution image construction from IRAS survey — parallelization and artifact suppression.- Maximum entropy performance analysis of spread-spectrum multiple-access communications.- Noise analysis in optical fibre sensing: A study using the maximum entropy method.- Algorithms.- AutoClass — a Bayesian approach to classification.- Evolution reviews of BayesCalc, a MATHEMATICA package for doing Bayesian calculations.- Bayesian inference for basis function selection in nonlinear system identification using genetic algorithms.- The meaning of the word “Probability”.- The hard truth.- Are the samples doped — If so, how much?.- Confidence intervals from one observation.- Hypothesis refinement.- Bayesian density estimation.- Scale-invariant Markov models for Bayesian inversion of linear inverse problems.- Foundations: Indifference, independence and MaxEnt.- The maximum entropy on the mean method, noise and sensitivity.- The maximum entropy algorithm applied to the two-dimensional random packing problem.- Neural Networks.- Bayesian comparison of models for images.- Interpolation models with multiple hyperparameters.- Density networks and their application to proteinmodelling.- The cluster expansion: A hierarchical density model.- The partitioned mixture distribution: Multiple overlapping density models.- Physics.- Generating functional for the BBGKY hierarchy and the N-identical-body problem.- Entropies for continua: Fluids and magnetofluids.- A logical foundation for real thermodynamics.