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{ "item_title" : "Statistical Physics", "item_author" : [" Josef Honerkamp "], "item_description" : "Statistical Physics is more than Statistical Mechanics.- Part I: Modeling of Statistical Systems.- Random Variables: Fundamentals of Probability Theory and Statistics.- Random Variables in State Space: Classical Statistical Mechanics of Fluids.- Random Fields: Textures and Classical Statistical Mechanics of Spin Systems.- Time-Dependent Random Variables: Classical Stochastic Processes.- Quantum Random Systems.- Changes of External Conditions.- Part II: Analysis of Statistical Systems.- Estimation of Parameters.- Signal Analysis: Estimation of Spectra.- Estimators Based on a Probability Distribution for the Parameters.- Identification of Stochastic Models from Observations.- Estimating the Parameters of a Hidden Stochastic Model.- Statistical Tests and Classification Methods.- Appendix: Random Number Generation for Simulating Realizations of Random Variables.- Problems.- Hints and Solutions.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/3/64/228/683/3642286836_b.jpg", "price_data" : { "retail_price" : "84.99", "online_price" : "84.99", "our_price" : "84.99", "club_price" : "84.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Statistical Physics|Josef Honerkamp

Statistical Physics : An Advanced Approach with Applications

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Overview

Statistical Physics is more than Statistical Mechanics.- Part I: Modeling of Statistical Systems.- Random Variables: Fundamentals of Probability Theory and Statistics.- Random Variables in State Space: Classical Statistical Mechanics of Fluids.- Random Fields: Textures and Classical Statistical Mechanics of Spin Systems.- Time-Dependent Random Variables: Classical Stochastic Processes.- Quantum Random Systems.- Changes of External Conditions.- Part II: Analysis of Statistical Systems.- Estimation of Parameters.- Signal Analysis: Estimation of Spectra.- Estimators Based on a Probability Distribution for the Parameters.- Identification of Stochastic Models from Observations.- Estimating the Parameters of a Hidden Stochastic Model.- Statistical Tests and Classification Methods.- Appendix: Random Number Generation for Simulating Realizations of Random Variables.- Problems.- Hints and Solutions.

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Details

  • ISBN-13: 9783642286834
  • ISBN-10: 3642286836
  • Publisher: Springer
  • Publish Date: June 2012
  • Dimensions: 9.21 x 6.14 x 1.25 inches
  • Shipping Weight: 2.13 pounds
  • Page Count: 554

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