The Maximum Entropy Method
|
|
- Valerie Jenkins
- 5 years ago
- Views:
Transcription
1 Nailong Wu The Maximum Entropy Method With 53 Figures Springer
2 1. Introduction What is the Maximum Entropy Method Definition of Entropy Rationale of the Maximum Entropy Method Present and Future Research 9 2. Maximum Entropy Method MEMl and Its Application in Spectral Analysis Definition and Expressions of Entropy HI Approach Approach Discussion Formulation and Solution Formulation Solution Discussion Equivalents and Signal Model ACF Extension Subject to the Nonnegativity Constraint Principle of MCE AR Process (Signal Model) Bayesian Method Wiener Filter and Approximation Theoretic Approach Algorithms and Numerical Example (Given ACF) Levinson's Recursion for 1-D Noiseless Data Lim-Malik Algorithm for 2-D Noiseless Data Wernecke-D'Addario Algorithm for 2-D Noisy Data Numerical Example Algorithms and Numerical Example (Given Time Series) Burg Algorithm Marple Algorithm Other Fast Algorithms Numerical Example 91
3 X 2.6 Order Selection FPE Criterion AIC Criterion Other Criteria Summary Maximum Entropy Method MEM2 and Its Application in Image Restoration Definition and Expressions of Entropy HI MLM Direct Definition Method Discussion Formulation and Implicit Solution Formulation Implicit Solution Iterative Algorithm Discussion Explicit Solution Explicit Solution Discussion Examples Equivalents and Signal Model ACF Extension Subject to the Nonnegativity Constraint Principle of MCE Exponential Process (Signal Model) Bayesian Method MLM R-X Procedure Statements of the MEM2 Problem R-X Procedure Example Algorithms and Numerical Examples (I) Frieden Algorithm Gull-Daniell Algorithm Revised GD Algorithm Simplified Newton-Raphson Algorithm Numerical Example Algorithms and Numerical Examples (II) Skilling-Bryan Algorithm Differential Equation Approach Algorithms and Numerical Examples (III) MEM/MemSys5 Package MEM Task in IRAF Restoration with Variable Resolution 184
4 3.8.4 Numerical Examples Other Algorithms Analysis and Comparison of the Maximum Entropy Method Generalized MEM Formulation of GMEM "Entropy" Expressions in GMEM Properties of GMEM Expressions of Entropy Solution's Properties Existence Uniqueness Consistency Statistical Properties Resolution Enhancement and Data Extension (Experimental Results) Examples Resolvability in 1-D Spectral Estimation Resolvability in 2-D Spectral Estimation Superresolution and Spectral Line Splitting Resolution Enhancement and Data Extension (Theoretical Analysis) Data Extension in MEM1 and MEM Resolution Enhancement of MEM1 and MEM MEM1 and MEM2 Spectra at Low SNR Line Splitting of MEM Peak Location and Relative Power Estimation (Experimental Results) Peak Location (Given ACF) Peak Location (Given Time Series) Relative Power Estimation (Given ACF) Summary and Comments Peak Location and Relative Power Estimation (Theoretical Analysis) Interference Between Peaks Causes Peak Shifting Explanation of the Peak Shifting in MEM1 Spectra Relative Power Estimation for MEM Summary for Sects Comments on the Three Schools of Thought on MEM Applications of the Maximum Entropy Method in Mathematics and Physics Solution of Moment Problems General Theory 252 XI
5 XII Numerical Methods Noisy Moment Problems Numerical Examples Solution of Integral Equations Conversion of Integral Equations to Moment Problems Solution of Moment Problems by MEM Numerical Examples Discussion Solution of Partial Differential Equations Theory Numerical Example Discussion Predictive Statistical Mechanics Formulation and Solution Useful Formulae Distributions of Particles Among Energy Levels Boltzmann Distribution Fermi-Dirac and Bose-Einstein Distributions Classical Statistical Ensembles Micro canonical Ensemble Canonical Ensemble Grand Canonical Ensemble Quantum Statistical Ensembles Microcanonical Ensemble Canonical Ensemble Grand Canonical Ensemble 303 Appendices 305 A. Cepstral Analysis 305 A.I Cepstral Analysis System 305 A.2 I/O Relationship 306 A.3 Properties of the Complex Cepstrum 307 A.4 I/O Relationship for Minimum-Phase Input 309 B. Image Restoration 311 B.I Image Formation 311 B.2 Image Restoration 313 B.3 Relationship Between Image Restoration and Spectral Estimation 314 References 317 Index 323
Springer Berlin Heidelberg New York Barcelona Budapest Hong Kong London Milan Paris Santa Clara Singapore Tokyo
Springer Series in Information Sciences 32 Editor: Thomas S. Huang Springer Berlin Heidelberg New York Barcelona Budapest Hong Kong London Milan Paris Santa Clara Singapore Tokyo Springer Series in Information
More informationThermodynamics, Gibbs Method and Statistical Physics of Electron Gases
Bahram M. Askerov Sophia R. Figarova Thermodynamics, Gibbs Method and Statistical Physics of Electron Gases With im Figures Springer Contents 1 Basic Concepts of Thermodynamics and Statistical Physics...
More informationPart II Statistical Physics
Part II Statistical Physics Theorems Based on lectures by H. S. Reall Notes taken by Dexter Chua Lent 2017 These notes are not endorsed by the lecturers, and I have modified them (often significantly)
More informationElements of Multivariate Time Series Analysis
Gregory C. Reinsel Elements of Multivariate Time Series Analysis Second Edition With 14 Figures Springer Contents Preface to the Second Edition Preface to the First Edition vii ix 1. Vector Time Series
More informationPhys Midterm. March 17
Phys 7230 Midterm March 17 Consider a spin 1/2 particle fixed in space in the presence of magnetic field H he energy E of such a system can take one of the two values given by E s = µhs, where µ is the
More informationContents. 1 Introduction and guide for this text 1. 2 Equilibrium and entropy 6. 3 Energy and how the microscopic world works 21
Preface Reference tables Table A Counting and combinatorics formulae Table B Useful integrals, expansions, and approximations Table C Extensive thermodynamic potentials Table D Intensive per-particle thermodynamic
More informationfiziks Institute for NET/JRF, GATE, IIT-JAM, JEST, TIFR and GRE in PHYSICAL SCIENCES
Content-Thermodynamics & Statistical Mechanics 1. Kinetic theory of gases..(1-13) 1.1 Basic assumption of kinetic theory 1.1.1 Pressure exerted by a gas 1.2 Gas Law for Ideal gases: 1.2.1 Boyle s Law 1.2.2
More information1 The fundamental equation of equilibrium statistical mechanics. 3 General overview on the method of ensembles 10
Contents EQUILIBRIUM STATISTICAL MECHANICS 1 The fundamental equation of equilibrium statistical mechanics 2 2 Conjugate representations 6 3 General overview on the method of ensembles 10 4 The relation
More informationAutomatic Autocorrelation and Spectral Analysis
Piet M.T. Broersen Automatic Autocorrelation and Spectral Analysis With 104 Figures Sprin ger 1 Introduction 1 1.1 Time Series Problems 1 2 Basic Concepts 11 2.1 Random Variables 11 2.2 Normal Distribution
More informationPHY 6500 Thermal and Statistical Physics - Fall 2017
PHY 6500 Thermal and Statistical Physics - Fall 2017 Time: M, F 12:30 PM 2:10 PM. From 08/30/17 to 12/19/17 Place: Room 185 Physics Research Building Lecturer: Boris Nadgorny E-mail: nadgorny@physics.wayne.edu
More information(# = %(& )(* +,(- Closed system, well-defined energy (or e.g. E± E/2): Microcanonical ensemble
Recall from before: Internal energy (or Entropy): &, *, - (# = %(& )(* +,(- Closed system, well-defined energy (or e.g. E± E/2): Microcanonical ensemble & = /01Ω maximized Ω: fundamental statistical quantity
More informationElementary Lectures in Statistical Mechanics
George DJ. Phillies Elementary Lectures in Statistical Mechanics With 51 Illustrations Springer Contents Preface References v vii I Fundamentals: Separable Classical Systems 1 Lecture 1. Introduction 3
More informationNPTEL
NPTEL Syllabus Nonequilibrium Statistical Mechanics - Video course COURSE OUTLINE Thermal fluctuations, Langevin dynamics, Brownian motion and diffusion, Fokker-Planck equations, linear response theory,
More informationRestoration of Degraded Images with Maximum Entropy
Journal of Global Optimization 10: 91 103, 1997. 91 c 1997 Kluwer Academic Publishers. Printed in the Netherlands. Restoration of Degraded Images with Maximum Entropy DOMINIKUS NOLL Université Paul Sabatier,
More informationStatistical Mechanics
Franz Schwabl Statistical Mechanics Translated by William Brewer Second Edition With 202 Figures, 26 Tables, and 195 Problems 4u Springer Table of Contents 1. Basic Principles 1 1.1 Introduction 1 1.2
More informationarxiv: v1 [astro-ph.im] 16 Apr 2009
Closed form solution of the maximum entropy equations with application to fast radio astronomical image formation arxiv:0904.2545v1 [astro-ph.im] 16 Apr 2009 Amir Leshem 1 School of Engineering, Bar-Ilan
More informationSuggestions for Further Reading
Contents Preface viii 1 From Microscopic to Macroscopic Behavior 1 1.1 Introduction........................................ 1 1.2 Some Qualitative Observations............................. 2 1.3 Doing
More informationTHERMODYNAMICS THERMOSTATISTICS AND AN INTRODUCTION TO SECOND EDITION. University of Pennsylvania
THERMODYNAMICS AND AN INTRODUCTION TO THERMOSTATISTICS SECOND EDITION HERBERT B. University of Pennsylvania CALLEN JOHN WILEY & SONS New York Chichester Brisbane Toronto Singapore CONTENTS PART I GENERAL
More informationSyllabus and Topics Thermal Physics I Fall 2007
Syllabus and Topics 33-341 Thermal Physics I Fall 2007 Robert F. Sekerka 6416 Wean Hall, Phone 412-268-2362 sekerka@cmu.edu http://sekerkaweb.phys.cmu.edu August 27, 2007 Class Schedule: This class is
More informationINTRODUCTION TO о JLXJLA Из А lv-/xvj_y JrJrl Y üv_>l3 Second Edition
INTRODUCTION TO о JLXJLA Из А lv-/xvj_y JrJrl Y üv_>l3 Second Edition Kerson Huang CRC Press Taylor & Francis Croup Boca Raton London New York CRC Press is an imprint of the Taylor & Francis Group an Informa
More informationAcoustic MIMO Signal Processing
Yiteng Huang Jacob Benesty Jingdong Chen Acoustic MIMO Signal Processing With 71 Figures Ö Springer Contents 1 Introduction 1 1.1 Acoustic MIMO Signal Processing 1 1.2 Organization of the Book 4 Part I
More informationFundamentals. Statistical. and. thermal physics. McGRAW-HILL BOOK COMPANY. F. REIF Professor of Physics Universüy of California, Berkeley
Fundamentals of and Statistical thermal physics F. REIF Professor of Physics Universüy of California, Berkeley McGRAW-HILL BOOK COMPANY Auckland Bogota Guatemala Hamburg Lisbon London Madrid Mexico New
More informationPart III Spectrum Estimation
ECE79-4 Part III Part III Spectrum Estimation 3. Parametric Methods for Spectral Estimation Electrical & Computer Engineering North Carolina State University Acnowledgment: ECE79-4 slides were adapted
More informationMASSACHUSETTS INSTITUTE OF TECHNOLOGY Physics Department Statistical Physics I Spring Term 2013 Notes on the Microcanonical Ensemble
MASSACHUSETTS INSTITUTE OF TECHNOLOGY Physics Department 8.044 Statistical Physics I Spring Term 2013 Notes on the Microcanonical Ensemble The object of this endeavor is to impose a simple probability
More informationList of Comprehensive Exams Topics
List of Comprehensive Exams Topics Mechanics 1. Basic Mechanics Newton s laws and conservation laws, the virial theorem 2. The Lagrangian and Hamiltonian Formalism The Lagrange formalism and the principle
More informationCONTENTS NOTATIONAL CONVENTIONS GLOSSARY OF KEY SYMBOLS 1 INTRODUCTION 1
DIGITAL SPECTRAL ANALYSIS WITH APPLICATIONS S.LAWRENCE MARPLE, JR. SUMMARY This new book provides a broad perspective of spectral estimation techniques and their implementation. It concerned with spectral
More information6.730 Physics for Solid State Applications
6.730 Physics for Solid State Applications Lecture 25: Chemical Potential and Equilibrium Outline Microstates and Counting System and Reservoir Microstates Constants in Equilibrium Temperature & Chemical
More informationFISES - Statistical Physics
Coordinating unit: 230 - ETSETB - Barcelona School of Telecommunications Engineering Teaching unit: 748 - FIS - Department of Physics Academic year: Degree: 2018 BACHELOR'S DEGREE IN ENGINEERING PHYSICS
More informationPhysics 112 Spring 2014
Physics 112 Spring 2014 Phys 112 (S12) Syllabus/introduction 1 Goals Deeper understanding of concepts: less mysterious Entropy Free energy Chemical potential Statistical mechanics fluctuations kinetic
More informationAutoregressive tracking of vortex shedding. 2. Autoregression versus dual phase-locked loop
Autoregressive tracking of vortex shedding Dileepan Joseph, 3 September 2003 Invensys UTC, Oxford 1. Introduction The purpose of this report is to summarize the work I have done in terms of an AR algorithm
More informationNanoscale Energy Transport and Conversion A Parallel Treatment of Electrons, Molecules, Phonons, and Photons
Nanoscale Energy Transport and Conversion A Parallel Treatment of Electrons, Molecules, Phonons, and Photons Gang Chen Massachusetts Institute of Technology OXFORD UNIVERSITY PRESS 2005 Contents Foreword,
More informationElements of Statistical Mechanics
Elements of Statistical Mechanics Thermodynamics describes the properties of macroscopic bodies. Statistical mechanics allows us to obtain the laws of thermodynamics from the laws of mechanics, classical
More informationDerivation of the Boltzmann Distribution
CLASSICAL CONCEPT REVIEW 7 Derivation of the Boltzmann Distribution Consider an isolated system, whose total energy is therefore constant, consisting of an ensemble of identical particles 1 that can exchange
More informationClasses of Linear Operators Vol. I
Classes of Linear Operators Vol. I Israel Gohberg Seymour Goldberg Marinus A. Kaashoek Birkhäuser Verlag Basel Boston Berlin TABLE OF CONTENTS VOLUME I Preface Table of Contents of Volume I Table of Contents
More informationPrinciples of Equilibrium Statistical Mechanics
Debashish Chowdhury, Dietrich Stauffer Principles of Equilibrium Statistical Mechanics WILEY-VCH Weinheim New York Chichester Brisbane Singapore Toronto Table of Contents Part I: THERMOSTATICS 1 1 BASIC
More informationBachelor s Degree in Chemistry. 1 st YEAR Mechanics and Thermodynamics ECTS credits: 6 Semester: 1. Teaching objectives
1 st YEAR 5263 Mechanics and Thermodynamics ECTS credits: 6 Semester: 1 The student should be able to: 1. Understand the concepts and describe the fundamental aspects of Mechanics and Thermodynamics. 2.
More informationII Relationship of Classical Theory to Quantum Theory A Quantum mean occupation number
Appendix B Some Unifying Concepts Version 04.AppB.11.1K [including mostly Chapters 1 through 11] by Kip [This appendix is in the very early stages of development] I Physics as Geometry A Newtonian Physics
More informationUNIVERSITY OF SOUTHAMPTON
UNIVERSITY OF SOUTHAMPTON PHYS2024W1 SEMESTER 2 EXAMINATION 2011/12 Quantum Physics of Matter Duration: 120 MINS VERY IMPORTANT NOTE Section A answers MUST BE in a separate blue answer book. If any blue
More informationInternational Physics Course Entrance Examination Questions
International Physics Course Entrance Examination Questions (May 2010) Please answer the four questions from Problem 1 to Problem 4. You can use as many answer sheets you need. Your name, question numbers
More informationA Guide to Experiments in Quantum Optics
Hans-A. Bachor and Timothy C. Ralph A Guide to Experiments in Quantum Optics Second, Revised and Enlarged Edition WILEY- VCH WILEY-VCH Verlag CmbH Co. KGaA Contents Preface 1 Introduction 1.1 Historical
More informationFluctuations of Trapped Particles
Fluctuations of Trapped Particles M.V.N. Murthy with Muoi Tran and R.K. Bhaduri (McMaster) IMSc Chennai Department of Physics, University of Mysore, Nov 2005 p. 1 Ground State Fluctuations Ensembles in
More information424 Index. Eigenvalue in quantum mechanics, 174 eigenvector in quantum mechanics, 174 Einstein equation, 334, 342, 393
Index After-effect function, 368, 369 anthropic principle, 232 assumptions nature of, 242 autocorrelation function, 292 average, 18 definition of, 17 ensemble, see ensemble average ideal,23 operational,
More informationThe MaxEnt Method Applied to Spectral Analysis and Image Reconstruction
The MaxEnt Method Applied to Spectral Analysis and Image Reconstruction Suzette C. Lizamore Institute of Statistics and Operations Research Victoria University of Wellington suzette@isor.vuw.ac.nz Abstract
More informationWe already came across a form of indistinguishably in the canonical partition function: V N Q =
Bosons en fermions Indistinguishability We already came across a form of indistinguishably in the canonical partition function: for distinguishable particles Q = Λ 3N βe p r, r 2,..., r N ))dτ dτ 2...
More informationLevel IV Course Units Offered by The Department of Chemistry For Special Degree in Computational Chemistry
Level IV Course Units Offered by The Department of Chemistry For Special Degree in Computational Chemistry [Bachelor of Science honours in Computational Chemistry SLQF6] Level IV CH 4001 Research Project
More informationNational Sun Yat-Sen University CSE Course: Information Theory. Maximum Entropy and Spectral Estimation
Maximum Entropy and Spectral Estimation 1 Introduction What is the distribution of velocities in the gas at a given temperature? It is the Maxwell-Boltzmann distribution. The maximum entropy distribution
More informationTHE UNIVERSITY OF NEW SOUTH WALES SCHOOL OF PHYSICS FINAL EXAMINATION JUNE 2010 PHYS3020. Statistical Physics
THE UNIVERSITY OF NEW SOUTH WALES SCHOOL OF PHYSICS FINAL EXAMINATION JUNE 2010 PHYS3020 Statistical Physics Time Allowed - 2 hours Total number of questions - 5 Answer ALL questions All questions ARE
More informationTable of Contents [ttc]
Table of Contents [ttc] 1. Equilibrium Thermodynamics I: Introduction Thermodynamics overview. [tln2] Preliminary list of state variables. [tln1] Physical constants. [tsl47] Equations of state. [tln78]
More informationStochastic Processes. A stochastic process is a function of two variables:
Stochastic Processes Stochastic: from Greek stochastikos, proceeding by guesswork, literally, skillful in aiming. A stochastic process is simply a collection of random variables labelled by some parameter:
More informationCOMPUTER ALGEBRA DERIVATION OF THE BIAS OF LINEAR ESTIMATORS OF AUTOREGRESSIVE MODELS
COMPUTER ALGEBRA DERIVATION OF THE BIAS OF LINEAR ESTIMATORS OF AUTOREGRESSIVE MODELS Y. ZHANG and A.I. MCLEOD Acadia University and The University of Western Ontario May 26, 2005 1 Abstract. A symbolic
More informationData Fitting and Uncertainty
TiloStrutz Data Fitting and Uncertainty A practical introduction to weighted least squares and beyond With 124 figures, 23 tables and 71 test questions and examples VIEWEG+ TEUBNER IX Contents I Framework
More informationPRINCIPLES OF PHYSICS. \Hp. Ni Jun TSINGHUA. Physics. From Quantum Field Theory. to Classical Mechanics. World Scientific. Vol.2. Report and Review in
LONDON BEIJING HONG TSINGHUA Report and Review in Physics Vol2 PRINCIPLES OF PHYSICS From Quantum Field Theory to Classical Mechanics Ni Jun Tsinghua University, China NEW JERSEY \Hp SINGAPORE World Scientific
More informationGeophysical Data Analysis: Discrete Inverse Theory
Geophysical Data Analysis: Discrete Inverse Theory MATLAB Edition William Menke Lamont-Doherty Earth Observatory and Department of Earth and Environmental Sciences Columbia University. ' - Palisades, New
More informationIV. Classical Statistical Mechanics
IV. Classical Statistical Mechanics IV.A General Definitions Statistical Mechanics is a probabilistic approach to equilibrium macroscopic properties of large numbers of degrees of freedom. As discussed
More informationCourse in. Geometric nonlinearity. Nonlinear FEM. Computational Mechanics, AAU, Esbjerg
Course in Nonlinear FEM Geometric nonlinearity Nonlinear FEM Outline Lecture 1 Introduction Lecture 2 Geometric nonlinearity Lecture 3 Material nonlinearity Lecture 4 Material nonlinearity it continued
More informationPart II: Statistical Physics
Chapter 7: Quantum Statistics SDSMT, Physics 2013 Fall 1 Introduction 2 The Gibbs Factor Gibbs Factor Several examples 3 Quantum Statistics From high T to low T From Particle States to Occupation Numbers
More informationReview Session: Econometrics - CLEFIN (20192)
Review Session: Econometrics - CLEFIN (20192) Part II: Univariate time series analysis Daniele Bianchi March 20, 2013 Fundamentals Stationarity A time series is a sequence of random variables x t, t =
More information(i) T, p, N Gibbs free energy G (ii) T, p, µ no thermodynamic potential, since T, p, µ are not independent of each other (iii) S, p, N Enthalpy H
Solutions exam 2 roblem 1 a Which of those quantities defines a thermodynamic potential Why? 2 points i T, p, N Gibbs free energy G ii T, p, µ no thermodynamic potential, since T, p, µ are not independent
More informationAnalysis and Synthesis of Single-Input Single-Output Control Systems
Lino Guzzella Analysis and Synthesis of Single-Input Single-Output Control Systems l+kja» \Uja>)W2(ja»\ um Contents 1 Definitions and Problem Formulations 1 1.1 Introduction 1 1.2 Definitions 1 1.2.1 Systems
More informationLecture 6: Ideal gas ensembles
Introduction Lecture 6: Ideal gas ensembles A simple, instructive and practical application of the equilibrium ensemble formalisms of the previous lecture concerns an ideal gas. Such a physical system
More information2.4 Quantum confined electrons
2.4. Quantum confined electrons 5 2.4 Quantum confined electrons We will now focus our attention on the electron charge densities in case of one, two and three-dimensional confinement. All the relations
More informationThermal and Statistical Physics Department Exam Last updated November 4, L π
Thermal and Statistical Physics Department Exam Last updated November 4, 013 1. a. Define the chemical potential µ. Show that two systems are in diffusive equilibrium if µ 1 =µ. You may start with F =
More informationLos Alamos, New Mexico 87545
Los A l a m National Laboratory is operated by the University of California for the United States Department of Energy under contract W-7405-ENG-36. TITLE: BAYESIAN INFERENCE AND THE ANALYTIC CONTINUATION
More informationTHE PROCESSING of random signals became a useful
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, VOL. 58, NO. 11, NOVEMBER 009 3867 The Quality of Lagged Products and Autoregressive Yule Walker Models as Autocorrelation Estimates Piet M. T. Broersen
More informationThe deconvolution of lunar brightness temperature based on maximum entropy method using Chang E-2 microwave data
Research in Astron. Astrophys. 201x Vol. X No. XX, 000 000 http://www.raa-journal.org http://www.iop.org/journals/raa Research in Astronomy and Astrophysics The deconvolution of lunar brightness temperature
More informationEx3009: Entropy and heat capacity of quantum ideal gases
Ex009: Entropy and heat capacity of quantum ideal gases Submitted by: Yoav Zigdon he problem: Consider an N particle ideal gas confined in volume V at temperature. Find a the entropy S and b the heat capacity
More informationDefinite Integral and the Gibbs Paradox
Acta Polytechnica Hungarica ol. 8, No. 4, 0 Definite Integral and the Gibbs Paradox TianZhi Shi College of Physics, Electronics and Electrical Engineering, HuaiYin Normal University, HuaiAn, JiangSu, China,
More informationImage restoration: numerical optimisation
Image restoration: numerical optimisation Short and partial presentation Jean-François Giovannelli Groupe Signal Image Laboratoire de l Intégration du Matériau au Système Univ. Bordeaux CNRS BINP / 6 Context
More informationA NEW INFORMATION THEORETIC APPROACH TO ORDER ESTIMATION PROBLEM. Massachusetts Institute of Technology, Cambridge, MA 02139, U.S.A.
A EW IFORMATIO THEORETIC APPROACH TO ORDER ESTIMATIO PROBLEM Soosan Beheshti Munther A. Dahleh Massachusetts Institute of Technology, Cambridge, MA 0239, U.S.A. Abstract: We introduce a new method of model
More informationCEPSTRAL ANALYSIS SYNTHESIS ON THE MEL FREQUENCY SCALE, AND AN ADAPTATIVE ALGORITHM FOR IT.
CEPSTRAL ANALYSIS SYNTHESIS ON THE EL FREQUENCY SCALE, AND AN ADAPTATIVE ALGORITH FOR IT. Summarized overview of the IEEE-publicated papers Cepstral analysis synthesis on the mel frequency scale by Satochi
More informationStatistical Signal Processing Detection, Estimation, and Time Series Analysis
Statistical Signal Processing Detection, Estimation, and Time Series Analysis Louis L. Scharf University of Colorado at Boulder with Cedric Demeure collaborating on Chapters 10 and 11 A TT ADDISON-WESLEY
More informationChapter 14. Ideal Bose gas Equation of state
Chapter 14 Ideal Bose gas In this chapter, we shall study the thermodynamic properties of a gas of non-interacting bosons. We will show that the symmetrization of the wavefunction due to the indistinguishability
More informationThe Statistical Distribution of quantum particles where any of them can be a fermion with probability [P] or a boson with probability [1-p].
The Statistical Distribution of quantum particles where any of them can be a fermion with probability [P] or a boson with probability [1-p]. Ahmad Abu Taleb * Department of Mathematics, Faculty of Science,
More informationMaster Program. Integrated MSc/PhD Program: Chemistry of Complex Systems. Molecular Chemistry and Physical Chemistry
Master Program Integrated MSc/PhD Program: Chemistry of Complex Systems SEMESTER 1 SEMESTER 2 SEMESTER 3 Molecular Chemistry and Physical Chemistry Organic Chemistry (Chemistry of heterocycles given at
More informationThe non-interacting Bose gas
Chapter The non-interacting Bose gas Learning goals What is a Bose-Einstein condensate and why does it form? What determines the critical temperature and the condensate fraction? What changes for trapped
More informationA Course in Time Series Analysis
A Course in Time Series Analysis Edited by DANIEL PENA Universidad Carlos III de Madrid GEORGE C. TIAO University of Chicago RUEY S. TSAY University of Chicago A Wiley-Interscience Publication JOHN WILEY
More informationIndependent Component Analysis. Contents
Contents Preface xvii 1 Introduction 1 1.1 Linear representation of multivariate data 1 1.1.1 The general statistical setting 1 1.1.2 Dimension reduction methods 2 1.1.3 Independence as a guiding principle
More informationThe Twisting Trick for Double Well Hamiltonians
Commun. Math. Phys. 85, 471-479 (1982) Communications in Mathematical Physics Springer-Verlag 1982 The Twisting Trick for Double Well Hamiltonians E. B. Davies Department of Mathematics, King's College,
More informationGrand Canonical Formalism
Grand Canonical Formalism Grand Canonical Ensebmle For the gases of ideal Bosons and Fermions each single-particle mode behaves almost like an independent subsystem, with the only reservation that the
More informationStatistical Thermodynamics and Monte-Carlo Evgenii B. Rudnyi and Jan G. Korvink IMTEK Albert Ludwig University Freiburg, Germany
Statistical Thermodynamics and Monte-Carlo Evgenii B. Rudnyi and Jan G. Korvink IMTEK Albert Ludwig University Freiburg, Germany Preliminaries Learning Goals From Micro to Macro Statistical Mechanics (Statistical
More informationError Entropy Criterion in Echo State Network Training
Error Entropy Criterion in Echo State Network Training Levy Boccato 1, Daniel G. Silva 1, Denis Fantinato 1, Kenji Nose Filho 1, Rafael Ferrari 1, Romis Attux 1, Aline Neves 2, Jugurta Montalvão 3 and
More informationClassical Mechanics and Statistical/Thermodynamics. January 2015
Classical Mechanics and Statistical/Thermodynamics January 2015 1 Handy Integrals: Possibly Useful Information 0 x n e αx dx = n! α n+1 π α 0 0 e αx2 dx = 1 2 x e αx2 dx = 1 2α 0 x 2 e αx2 dx = 1 4 π α
More informationAnalytical Mechanics for Relativity and Quantum Mechanics
Analytical Mechanics for Relativity and Quantum Mechanics Oliver Davis Johns San Francisco State University OXPORD UNIVERSITY PRESS CONTENTS Dedication Preface Acknowledgments v vii ix PART I INTRODUCTION:
More informationStochastic Processes. Theory for Applications. Robert G. Gallager CAMBRIDGE UNIVERSITY PRESS
Stochastic Processes Theory for Applications Robert G. Gallager CAMBRIDGE UNIVERSITY PRESS Contents Preface page xv Swgg&sfzoMj ybr zmjfr%cforj owf fmdy xix Acknowledgements xxi 1 Introduction and review
More informationClassical Statistical Mechanics: Part 1
Classical Statistical Mechanics: Part 1 January 16, 2013 Classical Mechanics 1-Dimensional system with 1 particle of mass m Newton s equations of motion for position x(t) and momentum p(t): ẋ(t) dx p =
More informationQUANTUM MECHANICS. Franz Schwabl. Translated by Ronald Kates. ff Springer
Franz Schwabl QUANTUM MECHANICS Translated by Ronald Kates Second Revised Edition With 122Figures, 16Tables, Numerous Worked Examples, and 126 Problems ff Springer Contents 1. Historical and Experimental
More informationThermodynamics of the nucleus
Thermodynamics of the nucleus Hilde-Therese Nyhus 1. October, 8 Hilde-Therese Nyhus Thermodynamics of the nucleus Owerview 1 Link between level density and thermodynamics Definition of level density Level
More informationTopics for the Qualifying Examination
Topics for the Qualifying Examination Quantum Mechanics I and II 1. Quantum kinematics and dynamics 1.1 Postulates of Quantum Mechanics. 1.2 Configuration space vs. Hilbert space, wave function vs. state
More informationRandom Walks A&T and F&S 3.1.2
Random Walks A&T 110-123 and F&S 3.1.2 As we explained last time, it is very difficult to sample directly a general probability distribution. - If we sample from another distribution, the overlap will
More informationLecture 4: Types of errors. Bayesian regression models. Logistic regression
Lecture 4: Types of errors. Bayesian regression models. Logistic regression A Bayesian interpretation of regularization Bayesian vs maximum likelihood fitting more generally COMP-652 and ECSE-68, Lecture
More informationThe integrating factor method (Sect. 1.1)
The integrating factor method (Sect. 1.1) Overview of differential equations. Linear Ordinary Differential Equations. The integrating factor method. Constant coefficients. The Initial Value Problem. Overview
More informationSGN Advanced Signal Processing: Lecture 8 Parameter estimation for AR and MA models. Model order selection
SG 21006 Advanced Signal Processing: Lecture 8 Parameter estimation for AR and MA models. Model order selection Ioan Tabus Department of Signal Processing Tampere University of Technology Finland 1 / 28
More informationI. BASICS OF STATISTICAL MECHANICS AND QUANTUM MECHANICS
I. BASICS OF STATISTICAL MECHANICS AND QUANTUM MECHANICS Marus Holzmann LPMMC, Maison de Magistère, Grenoble, and LPTMC, Jussieu, Paris marus@lptl.jussieu.fr http://www.lptl.jussieu.fr/users/marus (Dated:
More informationMOLECULAR SPECTROSCOPY
MOLECULAR SPECTROSCOPY First Edition Jeanne L. McHale University of Idaho PRENTICE HALL, Upper Saddle River, New Jersey 07458 CONTENTS PREFACE xiii 1 INTRODUCTION AND REVIEW 1 1.1 Historical Perspective
More informationUndergraduate Physics Courses in Semesters:
Undergraduate Physics Courses in Semesters: PHYS1901 Physics Seminar Credit Hours: 1.0; Content: SEMINAR (1.0); Prerequisites: ; Course Description: Overview of current topics in physics, based on readings,
More informationThe fine-grained Gibbs entropy
Chapter 12 The fine-grained Gibbs entropy 12.1 Introduction and definition The standard counterpart of thermodynamic entropy within Gibbsian SM is the socalled fine-grained entropy, or Gibbs entropy. It
More informationStatistics 349(02) Review Questions
Statistics 349(0) Review Questions I. Suppose that for N = 80 observations on the time series { : t T} the following statistics were calculated: _ x = 10.54 C(0) = 4.99 In addition the sample autocorrelation
More informationContents. 1 Preliminaries 3. Martingales
Table of Preface PART I THE FUNDAMENTAL PRINCIPLES page xv 1 Preliminaries 3 2 Martingales 9 2.1 Martingales and examples 9 2.2 Stopping times 12 2.3 The maximum inequality 13 2.4 Doob s inequality 14
More informationa( i), where N i N ) is accurately d( i), where N i N. The derivative at ( ) ( ) ( )
More on implementing the derivative filter John C. Bancroft ABSTRACT More on implementing the derivative filter An update is presented on finding faster and or more accurate implementations of differentiator
More informationMinimum entropy deconvolution with frequency-domain constraints
GEOPHYSICS, VOL. 59, NO. 6 (JUNE 1994); P. 938-945, 9 FIGS., 1 TABLE. Minimum entropy deconvolution with frequency-domain constraints Mauricio D. Sacchi*, Danilo R. Velis*, and Alberto H. Cominguez ABSTRACT
More information