Linear Form of the Radiative Transfer Equation Revisited. Bormin Huang

Size: px
Start display at page:

Download "Linear Form of the Radiative Transfer Equation Revisited. Bormin Huang"

Transcription

1 Lnear Form of the Radate Tranfer Equaton Reted Bormn Huang Cooerate Inttute for Meteorologcal Satellte Stude, Sace Scence and Engneerng Center Unerty of Wconn Madon The 5 th Internatonal TOVS Study Conference (ITSC-5) Maratea, Italy, 4- October 26

2 Outlne Smth lnear form (Aled( Otc, 99) ). t dual form. The lnear form wth exact analytcal Jacoban. the tangent-lnear and adjont model. The lnear form wth exact analytcal Jacoban. the lnear form wth nexact analytcal Jacoban. Why ue the forward model wth exact analytcal Jacoban for hycal retreal and data amlaton? Summary Future work

3 Bll Smth Acheement n Phycal Retreal Bll ha been oneerng the hycal retreal of temerature and aborbng conttuent rofle from the radance ectra nce the late 6. H mot recent lnear form of the RTE wa ublhed n the landmark aer n Aled Otc (99). Th monochromatcally aroxmate lnear form and t arant hae been tll ued n the hycal retreal [e.g. Ma et al., 2, L et al., 2]. H work nred Huang et al. (Aled Otc, 22) to uccefully dere the lnear form wth exact analytcal Jacoban for the wdely-ued McMlln- Flemng-Eyre-Woolf tye of forward model (e.g. RTTOV, RTIASI). In th talk I wll roe that there ext the dual rereentaton of Smth lnear form (99), and how ome mathematcally nteretng outcome dered from th dual form.

4 Smth Lnear Form (99). t Dual Form ob S R = B ( ) τ ( ) B ( ) dτ ( ) = τ τ R B ( ) ( ) B ( ) d ( ) P δr B δτ δb τ = ( ) ( ) + ( ) ( ) δ R R R ob δ B ( ) B ( ) B ( ) δτ τ τ ( ) ( ) ( ) Smth Lnear Form It Dual Form B( ) d[ δτ( ) ] δb( ) dτ( ) δb ( ) ( ) ( ) [ ( )] dτ B dδτ δr δb τ B δτ = ( ) ( ) + ( ) ( )

5 δ R = B( ) δ τ( ) + δb( ) τ( ) δr β ( ) τ ( ) δt + = = δb( d ) τ( ) B ( ) d[ δτ( ) ] β ( ) τ ( ) δt( ) dln τ ( ) dt( ) β( ) τ ( ) δu( ) dln τ ( ) du ( ) δ R = B + δ ( ) τ( ) B( ) δτ( ) B ( ) [ ( )] ( ) ( ) dδτ δb dτ B ( T ( )) δb ( ) = δt( ) β ( ) δt( ) T ( ) d δτ τ δu du ( ) ( ) ( ) ( ) = = τ dt = d τ dτ ( ) τ ( ) d ln τ ( ) δ R β ( ) τ ( ) δ T + = = ln τ ( ) U ( ) q ( ) d g = τ ( ) τ ( ) dln ( ) dt( ) ( ) ln ( ), du ( ) du ( ) dln τ ( ) du ( ) ( ) = ln τ ( ) du ( ) du ( ) du d du ( ) β ( ) τ ( ) δ T( ) dln τ ( ) du o ( ) dt ( ) β ( ) τ ( ) ( dln τ ( ) δ U ) du ( )

6 δr β ( ) τ ( ) δt + = = β ( ) τ ( ) δt ( ) dln τ ( ) dt( ) β( ) τ ( ) δu( ) dln τ ( ) du ( ) δr β ( ) τ ( ) δ T + = = du( ) β ( ) τ ( ) δ T ( ) dln τ ( ) du o ( ) dt ( ) β ( ) τ ( ) ( dln τ ( ) δu ) du ( ) The effecte temerature rofle of the th aborbng ga: dt( ) δt( ) δt( ) δu( ) du ( ) The effecte temerature rofle of the th aborbng ga: du dt δt( ) δt( ) δu( ) du du ( ) ( ) ( ) ( ) Fnal Lnear Form δt δt = δr β ( ) τ ( ) β ( ) ( ) τ ( ) dln τ ( )

7 dt( ) δt( ) δt( ) δu( ) du ( ) du dt δt( ) δt( ) δu( ) du du ( ) ( ) ( ) ( ) du ( ) = + [ ] U ( ) U ( ) T( ) T( ) dt( ) du ( ) ( ) ( ) ( ) dt ( ) T T + U du ( ) = U ( ) + T ( ) T ( ) dt ( ) A ecal cae: T T ( ) = ( ) du ( ) = + [ ] U ( ) U ( ) T( ) T( ) dt( ) The general cae: T T { ( ) } ( ) ( ) du dt ( ) U U T T d T T dt d ( ) = ( ) ( ) ( ) + ( ) ( ) ( ) The retreal qualty of aborbng ga rofle deend on the qualty of temerature frt gue!

8 Matlab examle

9 The exact analytcal Jacoban aroach. the tangent-lnear & adjont aroach. Same numercal recon! 2. The exact analytcal Jacoban aroach eeral tme fater!! Examle: T T ( A B)( ) A Td ( d) = ( ) e d V T C T + Comute dv δv = δtd dtd Source: Paul an Delt

10 Why Ue Exact Analytcal Jacoban n Retreal and Data Amlaton? Phycal Retreal (D-Var): Cot( X ) = R ob R( X ) or ob Cot( X ) = R R( X ) + λ X X WP Data Amlaton (3D/4D-Var): Cot( X,...) = Atmoherc Dynamc Term( X,...) + R ob R( X ) ~ deal choce for multertral ounder (e.g. HIRS, GOES, MODIS) ~ an underdetermned roblem (wth reect to a tycal forward model) retreal Cot( X,...) = Atmoherc Dynamc Term( X,...) + X X ~ deal choce for hyerctral ounder (e.g. AIRS, IASI, GIFTS) ~an oerdetermned roblem (wth reect to a tycal forward model) Atmoherc dynamc term bacally goerned by the aer-stoke equaton, whch ha no analytcal Jacoban. Thu, t tangent-lnear/adjont model are needed for data amlaton. The exact analytcal Jacoban for the wdely-ued McMlln-Flemng-Eyre-Woolf tye of radate tranfer/forward model (e.g. RTTOV, RTIASI) are derable (Huang et al., Aled Otc, 22).

11 Summary. The clacal deraton of the lnear form of the RTE by Smth et al. (99) reewed. It dual form dered. 2. The orgnal lnear form aear to be a ecal cae of t dual form when the temerature frt gue haen to be the true temerature rofle. 3. Lnear form wth nexact analytc Jacoban make retreal reult unrelable! 4. The exact analytc Jacoban mlementaton an effcent alternate to the tangent-lnear/adjont model for hyerectral retreal and data amlaton roblem wth the wdely-ued McMlln-Flemng-Eyre-Woolf tye of forward model (e.g. RTTOV, RTIASI).

12 Future Work The Remote Senng GEOME (Geometrcal( Exloraton of onlnear Otmzaton n Meaurement Enronment) Project: Unelng the Radance Hyerace for Quantfyng Geohycal Retreal

13 The remote enng GEOME roject am to ole the followng long-tandng fundamental roblem n ae remote enng Gen a enor ecfcaton, t forward model and exact Jacoban, an, to quantfy the nformaton content of each channel,.e., the bet exected contrbuton from each channel to the retreal of temerature and aborbng gae at each reure leel, the nformaton content of a enor,.e., the bet exected retreal accuracy that et the tattcal lmt for all retreal algorthm, the error of a fat model n term of the degradaton of the bet exected retreal accuracy, a comared to t LBL counterart, the mact of enor noe leel on the bet exected retreal accuracy, the frt gue tolerance a afety meaure beyond whch no retreal algorthm can reach the bet exected retreal, and the retreal effcency a robutne meaure for any retreal algorthm, a comared to the bet exected retreal. Alcaton: Loy comreon retreal mact tude: to conclude the retreal degradaton (due to loy comreon) by the bet exected retreal accuracy that et the lmt for all oble retreal algorthm. Otmal channel electon for retreal wth artal channel: to relee the comutatonal burden n retreal and data amlaton a wth the mnmum retreal degradaton for hyerectral ounder (e.g. AIRS, IASI, GIFTS). Future enor degn & trade-off tudy for rk reducton: to ae the nformaton content (the bet exected retreal accuracy) of a enor degned wth arou ectral range, ILS reoluton, and noe leel. Dfferent lng ece hae dfferent genome. So do dfferent t enor!

Linear Form of the Radiative Transfer Equation Revisited

Linear Form of the Radiative Transfer Equation Revisited Internatonal TOVS Study Conference-XV Proceedngs Lnear Form of the Radate Transfer Equaton Rested Bormn Huang Sace Scence and Engneerng Center Unersty of Wsconsn-Madson, Madson, WI 5376, USA Abstract A

More information

Design of Recursive Digital Filters IIR

Design of Recursive Digital Filters IIR Degn of Recurve Dgtal Flter IIR The outut from a recurve dgtal flter deend on one or more revou outut value, a well a on nut t nvolve feedbac. A recurve flter ha an nfnte mule reone (IIR). The mulve reone

More information

Introduction. Modeling Data. Approach. Quality of Fit. Likelihood. Probabilistic Approach

Introduction. Modeling Data. Approach. Quality of Fit. Likelihood. Probabilistic Approach Introducton Modelng Data Gven a et of obervaton, we wh to ft a mathematcal model Model deend on adutable arameter traght lne: m + c n Polnomal: a + a + a + L+ a n Choce of model deend uon roblem Aroach

More information

Improvements on Waring s Problem

Improvements on Waring s Problem Imrovement on Warng Problem L An-Png Bejng 85, PR Chna al@nacom Abtract By a new recurve algorthm for the auxlary equaton, n th aer, we wll gve ome mrovement for Warng roblem Keyword: Warng Problem, Hardy-Lttlewood

More information

Jacobian mapping between vertical coordinate systems in data assimilation (ITSC-14 RTSP-WG action c)

Jacobian mapping between vertical coordinate systems in data assimilation (ITSC-14 RTSP-WG action c) www.ec.gc.ca Jacoban mappng between vertcal coordnate systems n data assmlaton (ITSC-14 RTSP-WG acton 2.1.1-c) Atmospherc Scence and Technology Drectorate Yves J. Rochon, Lous Garand, D.S. Turner, and

More information

Algorithms for factoring

Algorithms for factoring CSA E0 235: Crytograhy Arl 9,2015 Instructor: Arta Patra Algorthms for factorng Submtted by: Jay Oza, Nranjan Sngh Introducton Factorsaton of large ntegers has been a wdely studed toc manly because of

More information

Topology optimization of plate structures subject to initial excitations for minimum dynamic performance index

Topology optimization of plate structures subject to initial excitations for minimum dynamic performance index th World Congress on Structural and Multdsclnary Otmsaton 7 th -2 th, June 25, Sydney Australa oology otmzaton of late structures subject to ntal exctatons for mnmum dynamc erformance ndex Kun Yan, Gengdong

More information

Digital PI Controller Equations

Digital PI Controller Equations Ver. 4, 9 th March 7 Dgtal PI Controller Equatons Probably the most common tye of controller n ndustral ower electroncs s the PI (Proortonal - Integral) controller. In feld orented motor control, PI controllers

More information

Fuzzy approach to solve multi-objective capacitated transportation problem

Fuzzy approach to solve multi-objective capacitated transportation problem Internatonal Journal of Bonformatcs Research, ISSN: 0975 087, Volume, Issue, 00, -0-4 Fuzzy aroach to solve mult-objectve caactated transortaton roblem Lohgaonkar M. H. and Bajaj V. H.* * Deartment of

More information

Iterative Methods for Searching Optimal Classifier Combination Function

Iterative Methods for Searching Optimal Classifier Combination Function htt://www.cub.buffalo.edu Iteratve Method for Searchng Otmal Clafer Combnaton Functon Sergey Tulyakov Chaohong Wu Venu Govndaraju Unverty at Buffalo Identfcaton ytem: Alce Bob htt://www.cub.buffalo.edu

More information

QUANTITATIVE RISK MANAGEMENT TECHNIQUES USING INTERVAL ANALYSIS, WITH APPLICATIONS TO FINANCE AND INSURANCE

QUANTITATIVE RISK MANAGEMENT TECHNIQUES USING INTERVAL ANALYSIS, WITH APPLICATIONS TO FINANCE AND INSURANCE QANTITATIVE RISK MANAGEMENT TECHNIQES SING INTERVA ANAYSIS WITH APPICATIONS TO FINANCE AND INSRANCE Slva DED Ph.D. Bucharest nversty of Economc Studes Deartment of Aled Mathematcs; Romanan Academy Insttute

More information

Additional File 1 - Detailed explanation of the expression level CPD

Additional File 1 - Detailed explanation of the expression level CPD Addtonal Fle - Detaled explanaton of the expreon level CPD A mentoned n the man text, the man CPD for the uterng model cont of two ndvdual factor: P( level gen P( level gen P ( level gen 2 (.).. CPD factor

More information

A Quadratic Cumulative Production Model for the Material Balance of Abnormally-Pressured Gas Reservoirs F.E. Gonzalez M.S.

A Quadratic Cumulative Production Model for the Material Balance of Abnormally-Pressured Gas Reservoirs F.E. Gonzalez M.S. Natural as Engneerng A Quadratc Cumulatve Producton Model for the Materal Balance of Abnormally-Pressured as Reservors F.E. onale M.S. Thess (2003) T.A. Blasngame, Texas A&M U. Deartment of Petroleum Engneerng

More information

A Quadratic Cumulative Production Model for the Material Balance of Abnormally-Pressured Gas Reservoirs F.E. Gonzalez M.S.

A Quadratic Cumulative Production Model for the Material Balance of Abnormally-Pressured Gas Reservoirs F.E. Gonzalez M.S. Formaton Evaluaton and the Analyss of Reservor Performance A Quadratc Cumulatve Producton Model for the Materal Balance of Abnormally-Pressured as Reservors F.E. onale M.S. Thess (2003) T.A. Blasngame,

More information

a new crytoytem baed on the dea of Shmuley and roved t rovably ecure baed on ntractablty of factorng [Mc88] After that n 999 El Bham, Dan Boneh and Om

a new crytoytem baed on the dea of Shmuley and roved t rovably ecure baed on ntractablty of factorng [Mc88] After that n 999 El Bham, Dan Boneh and Om Weak Comote Dffe-Hellman not Weaker than Factorng Koohar Azman, azman@ceharfedu Javad Mohajer mohajer@harfedu Mahmoud Salmazadeh alma@harfedu Electronc Reearch Centre, Sharf Unverty of Technology Deartment

More information

Formal solvers of the RT equation

Formal solvers of the RT equation Formal solvers of the RT equaton Formal RT solvers Runge- Kutta (reference solver) Pskunov N.: 979, Master Thess Long characterstcs (Feautrer scheme) Cannon C.J.: 970, ApJ 6, 55 Short characterstcs (Hermtan

More information

Approximation of Optimal Interface Boundary Conditions for Two-Lagrange Multiplier FETI Method

Approximation of Optimal Interface Boundary Conditions for Two-Lagrange Multiplier FETI Method Aroxmaton of Otmal Interface Boundary Condtons for Two-Lagrange Multler FETI Method F.-X. Roux, F. Magoulès, L. Seres, Y. Boubendr ONERA, 29 av. de la Dvson Leclerc, BP72, 92322 Châtllon, France, ,

More information

2.3 Least-Square regressions

2.3 Least-Square regressions .3 Leat-Square regreon Eample.10 How do chldren grow? The pattern of growth vare from chld to chld, o we can bet undertandng the general pattern b followng the average heght of a number of chldren. Here

More information

Problem Set 3: Model Solutions

Problem Set 3: Model Solutions Ecoomc 73 Adaced Mcroecoomc Problem et 3: Model oluto. Coder a -bdder aucto wth aluato deedetly ad detcally dtrbuted accordg to F( ) o uort [,]. Let the hghet bdder ay the rce ( - k)b f + kb to the eller,

More information

Statistical Properties of the OLS Coefficient Estimators. 1. Introduction

Statistical Properties of the OLS Coefficient Estimators. 1. Introduction ECOOMICS 35* -- OTE 4 ECO 35* -- OTE 4 Stattcal Properte of the OLS Coeffcent Etmator Introducton We derved n ote the OLS (Ordnary Leat Square etmator ˆβ j (j, of the regreon coeffcent βj (j, n the mple

More information

Research Article Optimal Policies for a Finite-Horizon Production Inventory Model

Research Article Optimal Policies for a Finite-Horizon Production Inventory Model Advances n Oeratons Research Volume 2012, Artcle ID 768929, 16 ages do:10.1155/2012/768929 Research Artcle Otmal Polces for a Fnte-Horzon Producton Inventory Model Lakdere Benkherouf and Dalal Boushehr

More information

Numerical studies of space filling designs: optimization algorithms and subprojection properties

Numerical studies of space filling designs: optimization algorithms and subprojection properties umercal studes of sace fllng desgns: otmzaton algorthms and subroecton roertes Bertrand Iooss wth Gullaume Dambln & Matheu Coulet CEMRACS 03 July, 30th, 03 Motvatng eamle: Uncertantes management n smulaton

More information

Research Article The Point Zoro Symmetric Single-Step Procedure for Simultaneous Estimation of Polynomial Zeros

Research Article The Point Zoro Symmetric Single-Step Procedure for Simultaneous Estimation of Polynomial Zeros Aled Mathematcs Volume 2012, Artcle ID 709832, 11 ages do:10.1155/2012/709832 Research Artcle The Pont Zoro Symmetrc Sngle-Ste Procedure for Smultaneous Estmaton of Polynomal Zeros Mansor Mons, 1 Nasruddn

More information

Advanced Topics in Optimization. Piecewise Linear Approximation of a Nonlinear Function

Advanced Topics in Optimization. Piecewise Linear Approximation of a Nonlinear Function Advanced Tocs n Otmzaton Pecewse Lnear Aroxmaton of a Nonlnear Functon Otmzaton Methods: M8L Introducton and Objectves Introducton There exsts no general algorthm for nonlnear rogrammng due to ts rregular

More information

Fuzzy Set Approach to Solve Multi-objective Linear plus Fractional Programming Problem

Fuzzy Set Approach to Solve Multi-objective Linear plus Fractional Programming Problem Internatonal Journal of Oeratons Research Vol.8, o. 3, 5-3 () Internatonal Journal of Oeratons Research Fuzzy Set Aroach to Solve Mult-objectve Lnear lus Fractonal Programmng Problem Sanjay Jan Kalash

More information

Introduction to Interfacial Segregation. Xiaozhe Zhang 10/02/2015

Introduction to Interfacial Segregation. Xiaozhe Zhang 10/02/2015 Introducton to Interfacal Segregaton Xaozhe Zhang 10/02/2015 Interfacal egregaton Segregaton n materal refer to the enrchment of a materal conttuent at a free urface or an nternal nterface of a materal.

More information

IMPROVEMENT OF CONTROL PERFORMANCES USING FRACTIONAL PI λ D μ CONTROLLERS. K. Bettou., A. Charef

IMPROVEMENT OF CONTROL PERFORMANCES USING FRACTIONAL PI λ D μ CONTROLLERS. K. Bettou., A. Charef MPROVMT OF OTROL PRFORMAS USG FRATOAL P λ μ OTROLLRS. Bettou., A. haref éartement d lectronque Unverté Mentour Route An l-bey-5 - ontantne Algére -mal: bettou_kh@yahoo.com Abtract: Th aer deal wth the

More information

Analysis of Variance and Design of Experiments-II

Analysis of Variance and Design of Experiments-II Analyss of Varance and Desgn of Experments-II MODULE - III LECTURE - 8 PARTIALLY BALANCED INCOMPLETE BLOCK DESIGN (PBIBD) Dr Shalah Department of Mathematcs & Statstcs Indan Insttute of Technology Kanpur

More information

6. Hamilton s Equations

6. Hamilton s Equations 6. Hamlton s Equatons Mchael Fowler A Dynamcal System s Path n Confguraton Sace and n State Sace The story so far: For a mechancal system wth n degrees of freedom, the satal confguraton at some nstant

More information

Hongyi Miao, College of Science, Nanjing Forestry University, Nanjing ,China. (Received 20 June 2013, accepted 11 March 2014) I)ϕ (k)

Hongyi Miao, College of Science, Nanjing Forestry University, Nanjing ,China. (Received 20 June 2013, accepted 11 March 2014) I)ϕ (k) ISSN 1749-3889 (prnt), 1749-3897 (onlne) Internatonal Journal of Nonlnear Scence Vol.17(2014) No.2,pp.188-192 Modfed Block Jacob-Davdson Method for Solvng Large Sparse Egenproblems Hongy Mao, College of

More information

On the SO 2 Problem in Thermal Power Plants. 2.Two-steps chemical absorption modeling

On the SO 2 Problem in Thermal Power Plants. 2.Two-steps chemical absorption modeling Internatonal Journal of Engneerng Reearch ISSN:39-689)(onlne),347-53(prnt) Volume No4, Iue No, pp : 557-56 Oct 5 On the SO Problem n Thermal Power Plant Two-tep chemcal aborpton modelng hr Boyadjev, P

More information

Electric and magnetic field sensor and integrator equations

Electric and magnetic field sensor and integrator equations Techncal Note - TN12 Electrc and magnetc feld enor and ntegrator uaton Bertrand Da, montena technology, 1728 oen, Swtzerland Table of content 1. Equaton of the derate electrc feld enor... 1 2. Integraton

More information

Dynamics and Control of 6-DOF Shaking Table with Bell Crank Structure

Dynamics and Control of 6-DOF Shaking Table with Bell Crank Structure ICCS2005 June 2-5, KINTEX, Gyeongg-Do, Korea Dynamc and Control of 6-DOF Shakng Table wth Bell Crank Structure Duek-Jae Jeon*, Sung-Ho Park, Young-Jn Park, Youn-Sk Park, Hyoung-Eu Km and Jong-Won Park

More information

Homework 10 Stat 547. Problem ) Z D!

Homework 10 Stat 547. Problem ) Z D! Homework 0 Stat 547 Problem 74 Notaton: h s the hazard rate for the aneulod grou, h s the hazard rate for the dlod grou (a Log-rank test s erformed: H 0 : h (t = h (t Sgnfcance level α = 005 Test statstc

More information

risk and uncertainty assessment

risk and uncertainty assessment Optmal forecastng of atmospherc qualty n ndustral regons: rsk and uncertanty assessment Vladmr Penenko Insttute of Computatonal Mathematcs and Mathematcal Geophyscs SD RAS Goal Development of theoretcal

More information

Conservative Surrogate Model using Weighted Kriging Variance for Sampling-based RBDO

Conservative Surrogate Model using Weighted Kriging Variance for Sampling-based RBDO 9 th World Congress on Structural and Multdsclnary Otmzaton June 13-17, 011, Shzuoka, Jaan Conservatve Surrogate Model usng Weghted Krgng Varance for Samlng-based RBDO Lang Zhao 1, K.K. Cho, Ikn Lee 3,

More information

CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE

CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE Analytcal soluton s usually not possble when exctaton vares arbtrarly wth tme or f the system s nonlnear. Such problems can be solved by numercal tmesteppng

More information

Vibration Control of a Flexible Link Manipulator Using Smart Structures

Vibration Control of a Flexible Link Manipulator Using Smart Structures Proceedng of the 7th World Congre The Internatonal Federaton of Automatc Control Seoul, Korea, July 6-, 8 Vraton Control of a Flexle Lnk Manulator Ung Smart Structure H. Salma*. R. Fotouh**, P.. kforuk

More information

Lecture 21: Numerical methods for pricing American type derivatives

Lecture 21: Numerical methods for pricing American type derivatives Lecture 21: Numercal methods for prcng Amercan type dervatves Xaoguang Wang STAT 598W Aprl 10th, 2014 (STAT 598W) Lecture 21 1 / 26 Outlne 1 Fnte Dfference Method Explct Method Penalty Method (STAT 598W)

More information

A Simple Heuristic for Reducing the Number of Scenarios in Two-stage Stochastic Programming

A Simple Heuristic for Reducing the Number of Scenarios in Two-stage Stochastic Programming A Smle Heurtc for Reducng the Number of Scenaro n wo-tage Stochatc Programmng Ramumar aruah Marano Martn and gnaco E. Gromann * Deartment of Chemcal Engneerng Carnege Mellon Unverty Pttburgh PA 5 U.S.A.

More information

Chapter 6 The Effect of the GPS Systematic Errors on Deformation Parameters

Chapter 6 The Effect of the GPS Systematic Errors on Deformation Parameters Chapter 6 The Effect of the GPS Sytematc Error on Deformaton Parameter 6.. General Beutler et al., (988) dd the frt comprehenve tudy on the GPS ytematc error. Baed on a geometrc approach and aumng a unform

More information

A total variation approach

A total variation approach Denosng n dgtal radograhy: A total varaton aroach I. Froso M. Lucchese. A. Borghese htt://as-lab.ds.unm.t / 46 I. Froso, M. Lucchese,. A. Borghese Images are corruted by nose ) When measurement of some

More information

From Newton s 2 nd Law: v v. The time rate of change of the linear momentum of a particle is equal to the net force acting on the particle.

From Newton s 2 nd Law: v v. The time rate of change of the linear momentum of a particle is equal to the net force acting on the particle. From Newton s 2 nd Law: F ma d dm ( ) m dt dt F d dt The tme rate of change of the lnear momentum of a artcle s equal to the net force actng on the artcle. Conseraton of Momentum +x The toy rocket n dee

More information

The Study of Teaching-learning-based Optimization Algorithm

The Study of Teaching-learning-based Optimization Algorithm Advanced Scence and Technology Letters Vol. (AST 06), pp.05- http://dx.do.org/0.57/astl.06. The Study of Teachng-learnng-based Optmzaton Algorthm u Sun, Yan fu, Lele Kong, Haolang Q,, Helongang Insttute

More information

Lecture # 02: Pressure measurements and Measurement Uncertainties

Lecture # 02: Pressure measurements and Measurement Uncertainties AerE 3L & AerE343L Lecture Notes Lecture # 0: Pressure measurements and Measurement Uncertantes Dr. Hu H Hu Deartment of Aerosace Engneerng Iowa State Unversty Ames, Iowa 500, U.S.A Mechancal Pressure

More information

ME 501A Seminar in Engineering Analysis Page 1

ME 501A Seminar in Engineering Analysis Page 1 umercal Solutons of oundary-value Problems n Os ovember 7, 7 umercal Solutons of oundary- Value Problems n Os Larry aretto Mechancal ngneerng 5 Semnar n ngneerng nalyss ovember 7, 7 Outlne Revew stff equaton

More information

Outline. Unit Eight Calculations with Entropy. The Second Law. Second Law Notes. Uses of Entropy. Entropy is a Property.

Outline. Unit Eight Calculations with Entropy. The Second Law. Second Law Notes. Uses of Entropy. Entropy is a Property. Unt Eght Calculatons wth Entropy Mechancal Engneerng 370 Thermodynamcs Larry Caretto October 6, 010 Outlne Quz Seven Solutons Second law revew Goals for unt eght Usng entropy to calculate the maxmum work

More information

Property-based Integration for Sustainable Development

Property-based Integration for Sustainable Development Proerty-baed Integraton for Sutanable Develoment V. Kazantz, D. Harell, F. Gabrel, Qn X., and M.M. El-Halwag * Deartment of Chemcal Engneerng Texa A&M Unverty, College Staton, TX 77843-3122, USA Abtract

More information

Solved problems 4 th exercise

Solved problems 4 th exercise Soled roblem th exercie Soled roblem.. On a circular conduit there are different diameter: diameter D = m change into D = m. The elocity in the entrance rofile wa meaured: = m -. Calculate the dicharge

More information

Variable Structure Control ~ Basics

Variable Structure Control ~ Basics Varable Structure Control ~ Bac Harry G. Kwatny Department of Mechancal Engneerng & Mechanc Drexel Unverty Outlne A prelmnary example VS ytem, ldng mode, reachng Bac of dcontnuou ytem Example: underea

More information

Probabilistic Variation Mode and Effect Analysis: A Case Study of an Air Engine Component

Probabilistic Variation Mode and Effect Analysis: A Case Study of an Air Engine Component Probablstc Varaton Mode and Effect Analyss: A Case Study of an Ar Engne Comonent Pär Johannesson Fraunhofer-Chalmers Research Centre for Industral Mathematcs, Sweden; Par.Johannesson@fcc.chalmers.se Thomas

More information

Dr. Shalabh Department of Mathematics and Statistics Indian Institute of Technology Kanpur

Dr. Shalabh Department of Mathematics and Statistics Indian Institute of Technology Kanpur Analyss of Varance and Desgn of Exerments-I MODULE III LECTURE - 2 EXPERIMENTAL DESIGN MODELS Dr. Shalabh Deartment of Mathematcs and Statstcs Indan Insttute of Technology Kanur 2 We consder the models

More information

Hidden Markov Model Cheat Sheet

Hidden Markov Model Cheat Sheet Hdden Markov Model Cheat Sheet (GIT ID: dc2f391536d67ed5847290d5250d4baae103487e) Ths document s a cheat sheet on Hdden Markov Models (HMMs). It resembles lecture notes, excet that t cuts to the chase

More information

11.5 MAP Estimator MAP avoids this Computational Problem!

11.5 MAP Estimator MAP avoids this Computational Problem! .5 MAP timator ecall that the hit-or-mi cot function gave the MAP etimator it maimize the a oteriori PDF Q: Given that the MMS etimator i the mot natural one why would we conider the MAP etimator? A: If

More information

Consistency & Convergence

Consistency & Convergence /9/007 CHE 374 Computatonal Methods n Engneerng Ordnary Dfferental Equatons Consstency, Convergence, Stablty, Stffness and Adaptve and Implct Methods ODE s n MATLAB, etc Consstency & Convergence Consstency

More information

COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS

COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS Avalable onlne at http://sck.org J. Math. Comput. Sc. 3 (3), No., 6-3 ISSN: 97-537 COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS

More information

CHAPTER 9 LINEAR MOMENTUM, IMPULSE AND COLLISIONS

CHAPTER 9 LINEAR MOMENTUM, IMPULSE AND COLLISIONS CHAPTER 9 LINEAR MOMENTUM, IMPULSE AND COLLISIONS 103 Phy 1 9.1 Lnear Momentum The prncple o energy conervaton can be ued to olve problem that are harder to olve jut ung Newton law. It ued to decrbe moton

More information

RADIATION THERMOMETRY OF METAL IN HIGH TEMPERATURE FURNACE

RADIATION THERMOMETRY OF METAL IN HIGH TEMPERATURE FURNACE XVII IMEKO World Congre Metrology in the 3rd Millennium June 22 27, 2003, Dubrovnik, Croatia RADIATION THERMOMETRY OF METAL IN HIGH TEMPERATURE FURNACE Tohru Iuchi, Tohru Furukawa and Nobuharu Sato Deartment

More information

Boise State University Department of Electrical and Computer Engineering ECE 212L Circuit Analysis and Design Lab

Boise State University Department of Electrical and Computer Engineering ECE 212L Circuit Analysis and Design Lab Bose State Unersty Department of Electrcal and omputer Engneerng EE 1L rcut Analyss and Desgn Lab Experment #8: The Integratng and Dfferentatng Op-Amp rcuts 1 Objectes The objectes of ths laboratory experment

More information

Boise State University Department of Electrical and Computer Engineering ECE 212L Circuit Analysis and Design Lab

Boise State University Department of Electrical and Computer Engineering ECE 212L Circuit Analysis and Design Lab Bose State Unersty Department of Electrcal and omputer Engneerng EE 1L rcut Analyss and Desgn Lab Experment #8: The Integratng and Dfferentatng Op-Amp rcuts 1 Objectes The objectes of ths laboratory experment

More information

A new Approach for Solving Linear Ordinary Differential Equations

A new Approach for Solving Linear Ordinary Differential Equations , ISSN 974-57X (Onlne), ISSN 974-5718 (Prnt), Vol. ; Issue No. 1; Year 14, Copyrght 13-14 by CESER PUBLICATIONS A new Approach for Solvng Lnear Ordnary Dfferental Equatons Fawz Abdelwahd Department of

More information

Machine Learning. Classification. Theory of Classification and Nonparametric Classifier. Representing data: Hypothesis (classifier) Eric Xing

Machine Learning. Classification. Theory of Classification and Nonparametric Classifier. Representing data: Hypothesis (classifier) Eric Xing Machne Learnng 0-70/5 70/5-78, 78, Fall 008 Theory of Classfcaton and Nonarametrc Classfer Erc ng Lecture, Setember 0, 008 Readng: Cha.,5 CB and handouts Classfcaton Reresentng data: M K Hyothess classfer

More information

Bayesian Decision Theory

Bayesian Decision Theory No.4 Bayesan Decson Theory Hu Jang Deartment of Electrcal Engneerng and Comuter Scence Lassonde School of Engneerng York Unversty, Toronto, Canada Outlne attern Classfcaton roblems Bayesan Decson Theory

More information

Bloch Quantum-behaved Pigeon-Inspired Optimization for Continuous Optimization Problems*

Bloch Quantum-behaved Pigeon-Inspired Optimization for Continuous Optimization Problems* Proceedngs of 4 IEEE Chnese Gudance, avgaton and Control Conference August 8-, 4 Yanta, Chna Bloch Quantum-behaved Pgeon-Insred Otmzaton for Contnuous Otmzaton Problems* Honghao L, and Habn Duan, Senor

More information

Separation Axioms of Fuzzy Bitopological Spaces

Separation Axioms of Fuzzy Bitopological Spaces IJCSNS Internatonal Journal of Computer Scence and Network Securty VOL3 No October 3 Separaton Axom of Fuzzy Btopologcal Space Hong Wang College of Scence Southwet Unverty of Scence and Technology Manyang

More information

CHAPTER X PHASE-CHANGE PROBLEMS

CHAPTER X PHASE-CHANGE PROBLEMS Chapter X Phae-Change Problem December 3, 18 917 CHAPER X PHASE-CHANGE PROBLEMS X.1 Introducton Clacal Stefan Problem Geometry of Phae Change Problem Interface Condton X. Analytcal Soluton for Soldfcaton

More information

Delay equations with engineering applications Gábor Stépán Department of Applied Mechanics Budapest University of Technology and Economics

Delay equations with engineering applications Gábor Stépán Department of Applied Mechanics Budapest University of Technology and Economics Delay equatons wth engneerng applcatons Gábor Stépán Department of Appled Mechancs Budapest Unversty of Technology and Economcs Contents Delay equatons arse n mechancal systems by the nformaton system

More information

Electron-Impact Double Ionization of the H 2

Electron-Impact Double Ionization of the H 2 I R A P 6(), Dec. 5, pp. 9- Electron-Impact Double Ionzaton of the H olecule Internatonal Scence Press ISSN: 9-59 Electron-Impact Double Ionzaton of the H olecule. S. PINDZOLA AND J. COLGAN Department

More information

4DVAR, according to the name, is a four-dimensional variational method.

4DVAR, according to the name, is a four-dimensional variational method. 4D-Varatonal Data Assmlaton (4D-Var) 4DVAR, accordng to the name, s a four-dmensonal varatonal method. 4D-Var s actually a drect generalzaton of 3D-Var to handle observatons that are dstrbuted n tme. The

More information

Michael Batty. Alan Wilson Plenary Session Entropy, Complexity, & Information in Spatial Analysis

Michael Batty. Alan Wilson Plenary Session Entropy, Complexity, & Information in Spatial Analysis Alan Wlson Plenary Sesson Entroy, Comlexty, & Informaton n Satal Analyss Mchael Batty m.batty@ucl.ac.uk @jmchaelbatty htt://www.comlexcty.nfo/ htt://www.satalcomlexty.nfo/ for Advanced Satal Analyss CentreCentre

More information

Numerical Methods. ME Mechanical Lab I. Mechanical Engineering ME Lab I

Numerical Methods. ME Mechanical Lab I. Mechanical Engineering ME Lab I 5 9 Mechancal Engneerng -.30 ME Lab I ME.30 Mechancal Lab I Numercal Methods Volt Sne Seres.5 0.5 SIN(X) 0 3 7 5 9 33 37 4 45 49 53 57 6 65 69 73 77 8 85 89 93 97 0-0.5 Normalzed Squared Functon - 0.07

More information

Slide. King Saud University College of Science Physics & Astronomy Dept. PHYS 103 (GENERAL PHYSICS) CHAPTER 5: MOTION IN 1-D (PART 2) LECTURE NO.

Slide. King Saud University College of Science Physics & Astronomy Dept. PHYS 103 (GENERAL PHYSICS) CHAPTER 5: MOTION IN 1-D (PART 2) LECTURE NO. Slde Kng Saud Unersty College of Scence Physcs & Astronomy Dept. PHYS 103 (GENERAL PHYSICS) CHAPTER 5: MOTION IN 1-D (PART ) LECTURE NO. 6 THIS PRESENTATION HAS BEEN PREPARED BY: DR. NASSR S. ALZAYED Lecture

More information

Electrical Circuits II (ECE233b)

Electrical Circuits II (ECE233b) Electrcal Crcut II (ECE33b) Applcaton of Laplace Tranform to Crcut Analy Anet Dounav The Unverty of Wetern Ontaro Faculty of Engneerng Scence Crcut Element Retance Tme Doman (t) v(t) R v(t) = R(t) Frequency

More information

Derivatives of Value at Risk and Expected Shortfall

Derivatives of Value at Risk and Expected Shortfall Dervatves of Value at Rsk and Exected Shortfall November 2003 Hans Rau-Bredow hans.rau-bredow@mal.un-wuerzburg.de Dr. Hans Rau-Bredow Unversty of Cologne; Unversty of Würzburg Leo Wesmantel Str. 4 D-97074

More information

UPGRADE OF THE GSP GYROKINETIC CODE MID-YEAR PROGRESS REPORT

UPGRADE OF THE GSP GYROKINETIC CODE MID-YEAR PROGRESS REPORT 12/6/211 1 UPGRADE OF THE GSP GYROKINETIC CODE MID-YEAR PROGRESS REPORT George Wlke gwlke@umd.edu December 6, 211 Supersor: Wllam Dorland, Dept. of Physcs bdorland@umd.edu Abstract: Smulatons of turbulent

More information

Comparisons between Rough Set Based and Computational Applications in Data Mining

Comparisons between Rough Set Based and Computational Applications in Data Mining Internatonal Journal of Machne Learnng and Comutng ol. 4 No. 4 August 04 Comarsons between Rough Set Based and Comutatonal Alcatons n Data Mnng En-Bng Ln and Yu-Ru Syau Each obect s assocated wth a famly

More information

Using Genetic Algorithms in System Identification

Using Genetic Algorithms in System Identification Usng Genetc Algorthms n System Identfcaton Ecaterna Vladu Deartment of Electrcal Engneerng and Informaton Technology, Unversty of Oradea, Unverstat, 410087 Oradea, Româna Phone: +40259408435, Fax: +40259408408,

More information

Industrial Control and Monitoring

Industrial Control and Monitoring Internatonal Book Seres "Informaton Scence and Comutng" 89 Industral Control and Montorng APPLICATION OF GENETIC ALGORITHMS TO VECTOR OPTIMIZATION OF THE AUTOMATIC CONTROL SYSTEMS Valery Severn Abstract:

More information

An Accurate Heave Signal Prediction Using Artificial Neural Network

An Accurate Heave Signal Prediction Using Artificial Neural Network Internatonal Journal of Multdsclnary and Current Research Research Artcle ISSN: 2321-3124 Avalale at: htt://jmcr.com Mohammed El-Dasty 1,2 1 Hydrograhc Surveyng Deartment, Faculty of Martme Studes, Kng

More information

Model Reference Adaptive Temperature Control of the Electromagnetic Oven Process in Manufacturing Process

Model Reference Adaptive Temperature Control of the Electromagnetic Oven Process in Manufacturing Process RECENT ADVANCES n SIGNAL PROCESSING, ROBOTICS and AUTOMATION Model Reference Adatve Temerature Control of the Electromagnetc Oven Process n Manufacturng Process JIRAPHON SRISERTPOL SUPOT PHUNGPHIMAI School

More information

Quality Assessment of Restored Satellite Data. Based on Signal to Noise Ratio

Quality Assessment of Restored Satellite Data. Based on Signal to Noise Ratio Appled Mathematcal Scences, Vol. 0, 06, no. 49, 443-450 IKARI Ltd, www.m-hkar.com http://dx.do.org/0.988/ams.06.6448 ualty Assessment of Restored Satellte Data Based on Sgnal to Nose Rato Asmala Ahmad

More information

Topic 5: Non-Linear Regression

Topic 5: Non-Linear Regression Topc 5: Non-Lnear Regresson The models we ve worked wth so far have been lnear n the parameters. They ve been of the form: y = Xβ + ε Many models based on economc theory are actually non-lnear n the parameters.

More information

#64. ΔS for Isothermal Mixing of Ideal Gases

#64. ΔS for Isothermal Mixing of Ideal Gases #64 Carnot Heat Engne ΔS for Isothermal Mxng of Ideal Gases ds = S dt + S T V V S = P V T T V PV = nrt, P T ds = v T = nr V dv V nr V V = nrln V V = - nrln V V ΔS ΔS ΔS for Isothermal Mxng for Ideal Gases

More information

Maximum Likelihood Estimation of Binary Dependent Variables Models: Probit and Logit. 1. General Formulation of Binary Dependent Variables Models

Maximum Likelihood Estimation of Binary Dependent Variables Models: Probit and Logit. 1. General Formulation of Binary Dependent Variables Models ECO 452 -- OE 4: Probt and Logt Models ECO 452 -- OE 4 Maxmum Lkelhood Estmaton of Bnary Dependent Varables Models: Probt and Logt hs note demonstrates how to formulate bnary dependent varables models

More information

PID Controller Design Based on Second Order Model Approximation by Using Stability Boundary Locus Fitting

PID Controller Design Based on Second Order Model Approximation by Using Stability Boundary Locus Fitting PID Controller Desgn Based on Second Order Model Aroxmaton by Usng Stablty Boundary Locus Fttng Furkan Nur Denz, Bars Baykant Alagoz and Nusret Tan Inonu Unversty, Deartment of Electrcal and Electroncs

More information

Reliability Gain of Network Coding in Lossy Wireless Networks

Reliability Gain of Network Coding in Lossy Wireless Networks Relablty Gan of Network Codng n Lossy Wreless Networks Majd Ghader Deartment of Comuter Scence Unversty of Calgary mghader@cs.ucalgary.ca Don Towsley and Jm Kurose Deartment of Comuter Scence Unversty

More information

An Efficient Least-Squares Trilateration Algorithm for Mobile Robot Localization

An Efficient Least-Squares Trilateration Algorithm for Mobile Robot Localization he IEEE/RSJ Internatonal Conference on Intellgent Robots and Systems October -5, St. Lous, USA An Effcent Least-Squares rlateraton Algorthm for Moble Robot Localzaton Yu Zhou, Member, IEEE Abstract A novel

More information

Dimension reduction method for reliability-based robust design optimization

Dimension reduction method for reliability-based robust design optimization Comuters and Structures xxx (2007) xxx xxx www.elsever.com/locate/comstruc Dmenson reducton method for relablty-based robust desgn otmzaton Ikjn Lee a, K.K. Cho a, *, Lu Du a, Davd Gorsch b a Deartment

More information

A Robust Optimization Approach for the Milk Run Problem with Time Windows under Inventory Uncertainty - An Auto Industry Supply Chain Case Study

A Robust Optimization Approach for the Milk Run Problem with Time Windows under Inventory Uncertainty - An Auto Industry Supply Chain Case Study Proceedngs of the 21 Internatonal Conference on Industral Engneerng and Oeratons Management Dhaa, Bangladesh, January 9 1, 21 A Robust Otmzaton Aroach for the Ml Run Problem wth Tme Wndows under Inventory

More information

ABSTRACT. 1. Introduction. propagation of. with respect to. Method. dered in. terms of the velocity Cartesin. waves in the. the Atmosphere. D one.

ABSTRACT. 1. Introduction. propagation of. with respect to. Method. dered in. terms of the velocity Cartesin. waves in the. the Atmosphere. D one. Journal of Aled Mathematcs and Physcs,, 13, 1, 1-17 htt://dx.do.org/1.436/jam..13.143 Publshed Onlne October 13 (htt://www.scr.org/journal/jam) Numercal Smulaton of Acoustc-Gravty Waves Proagaton n a Heterogeneous

More information

General theory of fuzzy connectedness segmentations: reconciliation of two tracks of FC theory

General theory of fuzzy connectedness segmentations: reconciliation of two tracks of FC theory General theory of fuzzy connectedness segmentatons: reconclaton of two tracks of FC theory Krzysztof Chrs Ceselsk Department of Mathematcs, West Vrgna Unversty and MIPG, Department of Radology, Unversty

More information

Maximum Likelihood Estimation of Binary Dependent Variables Models: Probit and Logit. 1. General Formulation of Binary Dependent Variables Models

Maximum Likelihood Estimation of Binary Dependent Variables Models: Probit and Logit. 1. General Formulation of Binary Dependent Variables Models ECO 452 -- OE 4: Probt and Logt Models ECO 452 -- OE 4 Mamum Lkelhood Estmaton of Bnary Dependent Varables Models: Probt and Logt hs note demonstrates how to formulate bnary dependent varables models for

More information

Linear convergence of an algorithm for computing the largest eigenvalue of a nonnegative tensor

Linear convergence of an algorithm for computing the largest eigenvalue of a nonnegative tensor NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS Numer Lnear Algebra Al 22; 9:83 84 Publshed onlne 8 October 2 n Wley Onlne Lbrary (wleyonlnelbrarycom) OI: 2/nla822 Lnear convergence of an algorthm for comutng

More information

Lecture 8: S-modular Games and Power Control

Lecture 8: S-modular Games and Power Control CDS270: Otmzaton Game and Layerng n Commncaton Networ Lectre 8: S-modlar Game and Power Control Ln Chen /22/2006 Otlne S-modlar game Sermodlar game Sbmodlar game Power control Power control va rcng A general

More information

Priority Queuing with Finite Buffer Size and Randomized Push-out Mechanism

Priority Queuing with Finite Buffer Size and Randomized Push-out Mechanism ICN 00 Prorty Queung wth Fnte Buffer Sze and Randomzed Push-out Mechansm Vladmr Zaborovsy, Oleg Zayats, Vladmr Muluha Polytechncal Unversty, Sant-Petersburg, Russa Arl 4, 00 Content I. Introducton II.

More information

Mechanics Physics 151

Mechanics Physics 151 Mechancs hyscs 151 Lecture Canoncal Transformatons (Chater 9) What We Dd Last Tme Drect Condtons Q j Q j = = j, Q, j, Q, Necessary and suffcent j j for Canoncal Transf. = = j Q, Q, j Q, Q, Infntesmal CT

More information

Linear Momentum. Center of Mass.

Linear Momentum. Center of Mass. Lecture 6 Chapter 9 Physcs I 03.3.04 Lnear omentum. Center of ass. Course webste: http://faculty.uml.edu/ndry_danylov/teachng/physcsi Lecture Capture: http://echo360.uml.edu/danylov03/physcssprng.html

More information

Article from: ARCH Proceedings

Article from: ARCH Proceedings Artcle from: ARCH 204. Proceedngs July 3-August 3, 203 Opton Prcng Wthout Tears: Valung Equty-Lnked Death Benefts Elas S. W. Shu Department of Statstcs & Actuaral Scence The Unversty of Iowa U.S.A. Jont

More information

The multivariate Gaussian probability density function for random vector X (X 1,,X ) T. diagonal term of, denoted

The multivariate Gaussian probability density function for random vector X (X 1,,X ) T. diagonal term of, denoted Appendx Proof of heorem he multvarate Gauan probablty denty functon for random vector X (X,,X ) px exp / / x x mean and varance equal to the th dagonal term of, denoted he margnal dtrbuton of X Gauan wth

More information

6.01: Introduction to EECS I Lecture 7 March 15, 2011

6.01: Introduction to EECS I Lecture 7 March 15, 2011 6.0: Introducton to EECS I Lecture 7 March 5, 20 6.0: Introducton to EECS I Crcuts The Crcut Abstracton Crcuts represent systems as connectons of elements through whch currents (through arables) flow and

More information