Nonextensibility of energy in Tsallis statistics and the zeroth law of

Size: px
Start display at page:

Download "Nonextensibility of energy in Tsallis statistics and the zeroth law of"

Transcription

1 Nonextensbty of energy n Tsas statstcs and the zeroth a of thermodynamcs onge Ou and Jncan hen* T Word Laboratory, P. O. 870, eng 00080, Peoe s Reubc of hna and Deartment of Physcs, Xamen nversty, Xamen 6005, Peoe s Reubc of hna To mortant robems exstng n Tsas statstcs are nvestgated, here one s hether energy s extensve or not, and the other s hether t s necessary to ntroduce the so-caed generazed zeroth a of thermodynamcs or not. The resuts obtaned sho ceary that ke entroy, energy s aso nonextensve n Tsas statstcs, and that the zeroth a of thermodynamcs has been mcty used n Tsas statstcs snce 988. Moreover, t s exounded that the standard energy addtvty rue adoted by a great number of researchers s not sutabe n Tsas statstcs, because t not ony voates the a of energy conservaton but aso ts coroary s n contradcton th the zeroth a of thermodynamcs. P numbers: d; 05.0.J; y; a *uthor to hom a corresondence shoud be addressed. Mang address: Deartment of Physcs, Xamen nversty, Xamen 6005, Peoe s Reubc of hna Ema: cchen@xmu.edu.cn

2 Temerature, nterna energy and entroy are three of the most mortant arameters n thermodynamcs. The concets of temerature and nterna energy become nontrva hen entroy aears to be nonextensve. nce the generazed statstca entroy as roosed by Tsas n 988, the non-extensbty of entroy n some comex systems th ong-range nteractons and/or ong-duraton memory has been dey recognzed -8. Hoever, there are st to robems of hysca mortance n Tsas statstcs, here one s hether the nterna energes of these comex systems are extensve or not, and the other s hether t s necessary to ntroduce the generazed zeroth a of thermodynamcs or not. though the to robems have been dscussed for many years 9-5, they have not been soved u to no, and conseuenty, have affected the deveoment and mrovement of Tsas statstcs. Thus, t s very mortant and urgent to sove the to robems and reach some usefu concusons. In nonextensve statstca mechancs deveoed from Tsas entroy, the frst choce s very tte used n the terature snce t coud not sove the reevant mathematca dffcutes athough there are three dfferent choces for the nterna energy constrant 6. For the second choce -, 8,, the dstrbuton functon 7 [ ] / can be derved from the generazed statstca entroy here k /,, R / ] [, k s a ostve constant, s the tota number of mcroscoc ossbtes of the system, s the energy of the system at the state. mary, for the thrd choce 4,6,8, /, one can obtan the dstrbuton functon as 6

3 / ] / [ th / ] / [. It can be roved -4,6,8,6-8 that,, / / T k, here T s the absoute temerature. For the sake of convenence, s reaced by beo. For an soated system comosed of to subsystems and of hch the dstrbutons satsfy,6-8, 4 usng the reatons and and Es. -4, e can obtan the seudo-addtvty entroy rue, 5, 8, 6 k 5 and the seudo-addtvty energy rues, 6 ] ][ [ ] [ ] [ ] [. 7 It s orthhe ontng out that Es. 6 and 7 are to mortant resuts that have never aeared n Tsas statstcs and one of the mortant bases for dscussng and sovng to robems mentoned n ths aer. When one mortant condton 8 s adoted, Es. 6 and 7 may be, resectvey, smfed as 9,8, 9

4 4 ] ][ [ ] [ ] [ ] [. 0 It s mortant to note the fact that E. 8 has been mcty used n nonextensve statstca mechancs 8-8 snce the generazed statstca entroy as advanced n 988, athough t has never been obvousy gven n terature of nonextensve statstca mechancs. One fnd from the foong anayss that E. 8 s essentay the mathematca exresson of the zero a of thermodynamcs. sng the as of entroy and energy conservaton and the above euatons, e can strcty rove, 0, ] [ ] [ k k δ δ and, 0, δ δ. From Es., and, one obtans,,, or. It s ust the zeroth a of thermodynamcs. Obvousy, the hysca essence of E. s cometey dentca th that of E. 8. It mes the fact that startng from E. 8, one get E. hch s the same resut as E. 8. It s thus cear that the dervatve rocess of E. s ony of a sef-consstent cacuaton, but s not a roof for the zeroth a of thermodynamcs n nonextensve statstca mechancs. Ths shos ceary that the zeroth a of thermodynamcs st hods n nonextensve statstca mechancs, but t can not be roved from theory. onseuenty, the concet of temerature s aso sutabe n nonextensve statstca mechancs.

5 It s aso mortant to note the other fact that n nonextensve statstca mechancs, f E. 8, has not been mcty used, one can not get the standard energy addtvty rue, 4 even though the thrd term on the rght hand sde of Es. 6 and 7 s not consdered. It s thus obvous that E. 8 s a necessary condton for the vadty of E. 4. Hoever, many researchers have not exounded the ueston and drecty used Es. -5 and 4 to nvestgate some mortant robems. For exame, they have been used to derve the so caed generazed zeroth a of thermodynamcs n nonextensve statstca mechancs. y comarng the exresson of the so caed generazed zeroth a of thermodynamcs 8,-6,8 or 5 k k [ / k] [ / k] 6 th E. 8, t can be seen thout dffcuty that E. 5 or 6 s obvousy n contradcton th E. 8, because and are not, n genera, eua to and, resectvey. Ths shos ceary that the standard energy addtvty rue 4 hch has been dey used by a ot of researchers may not be sutabe n nonextensve statstca mechancs because ts coroary voates the zeroth a of thermodynamcs 9. Therefore, t s unnecessary to ntroduce the so caed generazed zeroth a of thermodynamcs n nonextensve statstca mechancs and the ne concet of the hysca temerature 8,-6,0. The above resuts sho ceary that, Es. 9 and 0 can be derved n nonextensve statstca mechancs,based on Es. -4 and the zeroth a of thermodynamcs. They are the concrete mathematca exressons of the energy conservaton n nonextensve 5

6 thermodynamcs. Just as onted out n Ref. [8], f the correaton nonextensve terms of hatever observabe or nteractons can be negected, hat s the orgn of the nonextensvty of entroy? It s e-knon that entroy shoud be a contnuous functon of the observabes. For exame, for a sme nonextensve system th, T, f the nterna energy s extensve, s entroy ossby nonextensve? In addton, f E. 4 s true, one ose Es. 0[or 9] and 4, hch are cruca for the nonextensve theory. If E. 4 fas, e cannot, n fact, fnd even the entroy correaton gven by E. 5. It s thus cear that ke entroy, energy s aso nonextensve n Tsas statstcs, he the standard energy addtvty rue 4 s not sutabe n Tsas statstcs because t drecty voates the a of energy conservaton. ummng u, e have soved to ong-standng robems n nonextensve statstca mechancs. The zeroth a of thermodynamcs cannot be roved from theory, but t has been mcty used n nonextensve statstca mechancs, he the so-caed generazed zeroth a of thermodynamcs derved by severa authors may not be correct because t s derved on the basc of E. 8 and ts coroary s obvousy n contradcton th E. 8. The zeroth a of thermodynamcs s a base of nonextensve statstca mechancs, he t s unnecessary to ntroduce the so-caed generazed zeroth a of thermodynamcs and the ne concet of the hysca temerature. The standard energy addtvty rue 4 used dey by many researchers may not be sutabe n nonextensve statstca mechancs because t voates the a of energy conservaton and ts coroary s obvousy n contradcton th ts remse. In nonextensve statstca mechancs, one has to use the seudo-addtvty energy rue hch s consstent th the zeroth a of thermodynamcs and satsfes the a of energy conservaton. Fnay, t s onted out that the concusons obtaned here conform to be s standont 6, 6

7 statstca mechancs may be modfed but thermodynamcs shoud reman unchanged. cknoedgements Ths ork as suorted by the Natona Natura cence Foundaton No.07505, Peoe s Reubc of hna. 7

8 References. Tsas, J. tat. Phys. 5, V. H. Hamty and D. E. arraco, Phys. Rev. Lett. 76, E. K. Lenz, L.. Maacarne and R.. Mendes, Phys. Rev. Lett. 80, R. aazar and R. Tora, Phys. Rev. Lett. 8, E. Vves and. Panes, Phys. Rev. Lett. 88, be and. K. Raagoa, Phys. Rev. Lett. 9, Taruya and M. akagam, Phys. Rev. Lett. 90, be and Y. Okamoto, Nonextensve statstca mechanchs and ts acatons,rnger, Hedeberg, Q.. Wang and. L. Méhauté, haos, otons and Fractas, 5, R. D. sto,. Martíneza, F. Pennn,. Pastno and H. Vucetchb, Phys. Lett. 0, be,. Martínez, F. Pennn and. Pastno, Phys. Lett. 8, Martínez, F. Pennn and. Pastno, Physca 95, be, Physca. 00, Martínez, F. Pennn, and. Pastno, Physca 95, be, Physca. 69, Tsas, R.. Mendes and. R. Pastno, Physca 6, E. M. F. urado and. Tsas, J. Phys. 4, L Q.. Wang, Eur. Phys. J. 6, M. Nauenberg, Phys. Rev. E, 67, Martínez and. Pastno, Physca 45,

THERMODYNAMICS. Temperature

THERMODYNAMICS. Temperature HERMODYNMICS hermodynamcs s the henomenologcal scence whch descrbes the behavor of macroscoc objects n terms of a small number of macroscoc arameters. s an examle, to descrbe a gas n terms of volume ressure

More information

Xin Li Department of Information Systems, College of Business, City University of Hong Kong, Hong Kong, CHINA

Xin Li Department of Information Systems, College of Business, City University of Hong Kong, Hong Kong, CHINA RESEARCH ARTICLE MOELING FIXE OS BETTING FOR FUTURE EVENT PREICTION Weyun Chen eartment of Educatona Informaton Technoogy, Facuty of Educaton, East Chna Norma Unversty, Shangha, CHINA {weyun.chen@qq.com}

More information

b ), which stands for uniform distribution on the interval a x< b. = 0 elsewhere

b ), which stands for uniform distribution on the interval a x< b. = 0 elsewhere Fall Analyss of Epermental Measurements B. Esensten/rev. S. Errede Some mportant probablty dstrbutons: Unform Bnomal Posson Gaussan/ormal The Unform dstrbuton s often called U( a, b ), hch stands for unform

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

THE APPENDIX FOR THE PAPER: INCENTIVE-AWARE JOB ALLOCATION FOR ONLINE SOCIAL CLOUDS. Appendix A 1

THE APPENDIX FOR THE PAPER: INCENTIVE-AWARE JOB ALLOCATION FOR ONLINE SOCIAL CLOUDS. Appendix A 1 TE APPENDIX FOR TE PAPER: INCENTIVE-AWARE JO ALLOCATION FOR ONLINE SOCIAL CLOUDS Yu Zhang, Mihaea van der Schaar Aendix A 1 1) Proof of Proosition 1 Given the SCP, each suier s decision robem can be formuated

More information

The Use of Principal Components Analysis in the Assessment of Process Capability Indices

The Use of Principal Components Analysis in the Assessment of Process Capability Indices Jont Statstca Meetngs - Secton on Physca & Engneerng Scences (SPES) The Use of Prnca omonents Anayss n the Assessment of Process aabty Indces Evdoka Xekaak Mchae Peraks Deartment of Statstcs Athens Unversty

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

On New Selection Procedures for Unequal Probability Sampling

On New Selection Procedures for Unequal Probability Sampling Int. J. Oen Problems Comt. Math., Vol. 4, o. 1, March 011 ISS 1998-66; Coyrght ICSRS Publcaton, 011 www.-csrs.org On ew Selecton Procedures for Unequal Probablty Samlng Muhammad Qaser Shahbaz, Saman Shahbaz

More information

Managing Capacity Through Reward Programs. on-line companion page. Byung-Do Kim Seoul National University College of Business Administration

Managing Capacity Through Reward Programs. on-line companion page. Byung-Do Kim Seoul National University College of Business Administration Managng Caacty Through eward Programs on-lne comanon age Byung-Do Km Seoul Natonal Unversty College of Busness Admnstraton Mengze Sh Unversty of Toronto otman School of Management Toronto ON M5S E6 Canada

More information

Mechanics Physics 151

Mechanics Physics 151 Mechancs Physcs 151 Lecture 22 Canoncal Transformatons (Chater 9) What We Dd Last Tme Drect Condtons Q j Q j = = j P, Q, P j, P Q, P Necessary and suffcent P j P j for Canoncal Transf. = = j Q, Q, P j

More information

An application of generalized Tsalli s-havrda-charvat entropy in coding theory through a generalization of Kraft inequality

An application of generalized Tsalli s-havrda-charvat entropy in coding theory through a generalization of Kraft inequality Internatonal Journal of Statstcs and Aled Mathematcs 206; (4): 0-05 ISS: 2456-452 Maths 206; (4): 0-05 206 Stats & Maths wwwmathsjournalcom Receved: 0-09-206 Acceted: 02-0-206 Maharsh Markendeshwar Unversty,

More information

On the Connectedness of the Solution Set for the Weak Vector Variational Inequality 1

On the Connectedness of the Solution Set for the Weak Vector Variational Inequality 1 Journal of Mathematcal Analyss and Alcatons 260, 15 2001 do:10.1006jmaa.2000.7389, avalable onlne at htt:.dealbrary.com on On the Connectedness of the Soluton Set for the Weak Vector Varatonal Inequalty

More information

Dmitry A. Zaitsev Odessa National Telecommunication Academy Kuznechnaya, 1, Odessa, Ukraine

Dmitry A. Zaitsev Odessa National Telecommunication Academy Kuznechnaya, 1, Odessa, Ukraine th Worksho on Agorthms and Toos for Petr Nets, Setember - October, 4, Unversty of Paderborn, Germany, 75-8 Sovng the fundamenta equaton of Petr net usng the decomoston nto functona subnets Dmtry A Zatsev

More information

REMODELLING OF VIBRATING SYSTEMS VIA FREQUENCY-DOMAIN-BASED VIRTUAL DISTORTION METHOD

REMODELLING OF VIBRATING SYSTEMS VIA FREQUENCY-DOMAIN-BASED VIRTUAL DISTORTION METHOD REMODELLING OF VIBRATING SYSTEMS VIA FREQUENCY-DOMAIN-BASED VIRTUAL DISTORTION METHOD Małgorzata MRÓZ and Jan HOLNICKI-SZULC Insttute of Fundamenta Technoogca Research, Swetokrzyska 21, -9 Warsaw, Poand

More information

G : Statistical Mechanics

G : Statistical Mechanics G25.2651: Statstca Mechancs Notes for Lecture 11 I. PRINCIPLES OF QUANTUM STATISTICAL MECHANICS The probem of quantum statstca mechancs s the quantum mechanca treatment of an N-partce system. Suppose the

More information

arxiv: v1 [physics.comp-ph] 17 Dec 2018

arxiv: v1 [physics.comp-ph] 17 Dec 2018 Pressures nsde a nano-porous medum. The case of a snge phase fud arxv:1812.06656v1 [physcs.comp-ph] 17 Dec 2018 Oav Gateand, Dck Bedeaux, and Sgne Kjestrup PoreLab, Department of Chemstry, Norwegan Unversty

More information

Quantum Runge-Lenz Vector and the Hydrogen Atom, the hidden SO(4) symmetry

Quantum Runge-Lenz Vector and the Hydrogen Atom, the hidden SO(4) symmetry Quantum Runge-Lenz ector and the Hydrogen Atom, the hdden SO(4) symmetry Pasca Szrftgser and Edgardo S. Cheb-Terrab () Laboratore PhLAM, UMR CNRS 85, Unversté Le, F-59655, France () Mapesoft Let's consder

More information

On the Power Function of the Likelihood Ratio Test for MANOVA

On the Power Function of the Likelihood Ratio Test for MANOVA Journa of Mutvarate Anayss 8, 416 41 (00) do:10.1006/jmva.001.036 On the Power Functon of the Lkehood Rato Test for MANOVA Dua Kumar Bhaumk Unversty of South Aabama and Unversty of Inos at Chcago and Sanat

More information

Elastic Collisions. Definition: two point masses on which no external forces act collide without losing any energy.

Elastic Collisions. Definition: two point masses on which no external forces act collide without losing any energy. Elastc Collsons Defnton: to pont asses on hch no external forces act collde thout losng any energy v Prerequstes: θ θ collsons n one denson conservaton of oentu and energy occurs frequently n everyday

More information

Nonadditive thermostatistics and thermodynamics

Nonadditive thermostatistics and thermodynamics Journal of Physcs: Conference Seres Nonaddtve thermostatstcs and thermodynamcs To cte ths artcle: P Ván et al 2012 J. Phys.: Conf. Ser. 394 012002 Vew the artcle onlne for updates and enhancements. Related

More information

Numerical Investigation of Power Tunability in Two-Section QD Superluminescent Diodes

Numerical Investigation of Power Tunability in Two-Section QD Superluminescent Diodes Numerca Investgaton of Power Tunabty n Two-Secton QD Superumnescent Dodes Matta Rossett Paoo Bardea Ivo Montrosset POLITECNICO DI TORINO DELEN Summary 1. A smpfed mode for QD Super Lumnescent Dodes (SLD)

More information

10.40 Appendix Connection to Thermodynamics and Derivation of Boltzmann Distribution

10.40 Appendix Connection to Thermodynamics and Derivation of Boltzmann Distribution 10.40 Appendx Connecton to Thermodynamcs Dervaton of Boltzmann Dstrbuton Bernhardt L. Trout Outlne Cannoncal ensemble Maxmumtermmethod Most probable dstrbuton Ensembles contnued: Canoncal, Mcrocanoncal,

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

Not-for-Publication Appendix to Optimal Asymptotic Least Aquares Estimation in a Singular Set-up

Not-for-Publication Appendix to Optimal Asymptotic Least Aquares Estimation in a Singular Set-up Not-for-Publcaton Aendx to Otmal Asymtotc Least Aquares Estmaton n a Sngular Set-u Antono Dez de los Ros Bank of Canada dezbankofcanada.ca December 214 A Proof of Proostons A.1 Proof of Prooston 1 Ts roof

More information

Thermodynamics II. Department of Chemical Engineering. Prof. Kim, Jong Hak

Thermodynamics II. Department of Chemical Engineering. Prof. Kim, Jong Hak Thermodynamcs II Department o Chemca ngneerng ro. Km, Jong Hak .5 Fugacty & Fugacty Coecent : ure Speces µ > provdes undamenta crteron or phase equbrum not easy to appy to sove probem Lmtaton o gn (.9

More information

Non-Ideality Through Fugacity and Activity

Non-Ideality Through Fugacity and Activity Non-Idealty Through Fugacty and Actvty S. Patel Deartment of Chemstry and Bochemstry, Unversty of Delaware, Newark, Delaware 19716, USA Corresondng author. E-mal: saatel@udel.edu 1 I. FUGACITY In ths dscusson,

More information

Negative Birefraction of Acoustic Waves in a Sonic Crystal

Negative Birefraction of Acoustic Waves in a Sonic Crystal Negatve Brefracton of Acoustc Waves n a Sonc Crysta Mng-Hu Lu 1, Chao Zhang 1, Lang Feng 1, * Jun Zhao 1, Yan-Feng Chen 1, Y-We Mao 2, Jan Z 3, Yong-Yuan Zhu 1, Sh-Nng Zhu 1 and Na-Ben Mng 1 1 Natona Laboratory

More information

Isothermal vs. adiabatic compression

Isothermal vs. adiabatic compression Isothermal vs. adabatc comresson 1. One and a half moles of a datomc gas at temerature 5 C are comressed sothermally from a volume of 0.015 m to a volume of 0.0015 m. a. Sketch the rocess on a dagram and

More information

( ) r! t. Equation (1.1) is the result of the following two definitions. First, the bracket is by definition a scalar product.

( ) r! t. Equation (1.1) is the result of the following two definitions. First, the bracket is by definition a scalar product. Chapter. Quantum Mechancs Notes: Most of the matera presented n ths chapter s taken from Cohen-Tannoudj, Du, and Laoë, Chap. 3, and from Bunker and Jensen 5), Chap... The Postuates of Quantum Mechancs..

More information

Lecture 12: Discrete Laplacian

Lecture 12: Discrete Laplacian Lecture 12: Dscrete Laplacan Scrbe: Tanye Lu Our goal s to come up wth a dscrete verson of Laplacan operator for trangulated surfaces, so that we can use t n practce to solve related problems We are mostly

More information

The Degree Distribution of Random Birth-and-Death Network with Network Size Decline

The Degree Distribution of Random Birth-and-Death Network with Network Size Decline The Degree Dstrbuton of Random Brth-and-Death etwork wth etwork Sze Declne Xaojun Zhang *, Hulan Yang School of Mathematcal Scences, Unversty of Electronc Scence and Technology of Chna, Chengdu 673, P.R.

More information

Applied Stochastic Processes

Applied Stochastic Processes STAT455/855 Fall 23 Appled Stochastc Processes Fnal Exam, Bref Solutons 1. (15 marks) (a) (7 marks) The dstrbuton of Y s gven by ( ) ( ) y 2 1 5 P (Y y) for y 2, 3,... The above follows because each of

More information

Note On Some Identities of New Combinatorial Integers

Note On Some Identities of New Combinatorial Integers Apped Mathematcs & Informaton Scences 5(3 (20, 500-53 An Internatona Journa c 20 NSP Note On Some Identtes of New Combnatora Integers Adem Kııçman, Cenap Öze 2 and Ero Yımaz 3 Department of Mathematcs

More information

A Fluid-Based Model of Time-Limited TCP Flows 1

A Fluid-Based Model of Time-Limited TCP Flows 1 A Fud-Based Mode of Tme-Lmted TCP Fows Maro Barbera DIIT - Unversty of Catana V.e A. Dora 6 9525 Catana -Itay hone: +39 95 7382375 fax: +39 95 33828 mbarbera@.unct.t Afo Lombardo DIIT - Unversty of Catana

More information

UNIT 7. THE FUNDAMENTAL EQUATIONS OF HYPERSURFACE THEORY

UNIT 7. THE FUNDAMENTAL EQUATIONS OF HYPERSURFACE THEORY UNIT 7. THE FUNDAMENTAL EQUATIONS OF HYPERSURFACE THEORY ================================================================================================================================================================================================================================================

More information

Controller Design of Nonlinear TITO Systems with Uncertain Delays via Neural Networks and Error Entropy Minimization

Controller Design of Nonlinear TITO Systems with Uncertain Delays via Neural Networks and Error Entropy Minimization Controer Desgn of Nonnear TITO Systes wth Uncertan Deays va Neura Networs Error Entroy Mnzaton J. H. Zhang A. P. Wang* H. Wang** Deartent of Autoaton North Chna Eectrc Power Unversty Bejng 6 P. R. Chna

More information

More metrics on cartesian products

More metrics on cartesian products More metrcs on cartesan products If (X, d ) are metrc spaces for 1 n, then n Secton II4 of the lecture notes we defned three metrcs on X whose underlyng topologes are the product topology The purpose of

More information

n α j x j = 0 j=1 has a nontrivial solution. Here A is the n k matrix whose jth column is the vector for all t j=0

n α j x j = 0 j=1 has a nontrivial solution. Here A is the n k matrix whose jth column is the vector for all t j=0 MODULE 2 Topcs: Lnear ndependence, bass and dmenson We have seen that f n a set of vectors one vector s a lnear combnaton of the remanng vectors n the set then the span of the set s unchanged f that vector

More information

Boundary Value Problems. Lecture Objectives. Ch. 27

Boundary Value Problems. Lecture Objectives. Ch. 27 Boundar Vaue Probes Ch. 7 Lecture Obectves o understand the dfference between an nta vaue and boundar vaue ODE o be abe to understand when and how to app the shootng ethod and FD ethod. o understand what

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 II LECTURE - GENERAL LINEAR HYPOTHESIS AND ANALYSIS OF VARIANCE Dr. Shalabh Deartment of Mathematcs and Statstcs Indan Insttute of Technology Kanur 3.

More information

Lower bounds for the Crossing Number of the Cartesian Product of a Vertex-transitive Graph with a Cycle

Lower bounds for the Crossing Number of the Cartesian Product of a Vertex-transitive Graph with a Cycle Lower bounds for the Crossng Number of the Cartesan Product of a Vertex-transtve Graph wth a Cyce Junho Won MIT-PRIMES December 4, 013 Abstract. The mnmum number of crossngs for a drawngs of a gven graph

More information

we have E Y x t ( ( xl)) 1 ( xl), e a in I( Λ ) are as follows:

we have E Y x t ( ( xl)) 1 ( xl), e a in I( Λ ) are as follows: APPENDICES Aendx : the roof of Equaton (6 For j m n we have Smary from Equaton ( note that j '( ( ( j E Y x t ( ( x ( x a V ( ( x a ( ( x ( x b V ( ( x b V x e d ( abx ( ( x e a a bx ( x xe b a bx By usng

More information

PARTIAL QUOTIENTS AND DISTRIBUTION OF SEQUENCES. Department of Mathematics University of California Riverside, CA

PARTIAL QUOTIENTS AND DISTRIBUTION OF SEQUENCES. Department of Mathematics University of California Riverside, CA PARTIAL QUOTIETS AD DISTRIBUTIO OF SEQUECES 1 Me-Chu Chang Deartment of Mathematcs Unversty of Calforna Rversde, CA 92521 mcc@math.ucr.edu Abstract. In ths aer we establsh average bounds on the artal quotents

More information

APPENDIX A Some Linear Algebra

APPENDIX A Some Linear Algebra APPENDIX A Some Lnear Algebra The collecton of m, n matrces A.1 Matrces a 1,1,..., a 1,n A = a m,1,..., a m,n wth real elements a,j s denoted by R m,n. If n = 1 then A s called a column vector. Smlarly,

More information

On an Extension of Stochastic Approximation EM Algorithm for Incomplete Data Problems. Vahid Tadayon 1

On an Extension of Stochastic Approximation EM Algorithm for Incomplete Data Problems. Vahid Tadayon 1 On an Extenson of Stochastc Approxmaton EM Algorthm for Incomplete Data Problems Vahd Tadayon Abstract: The Stochastc Approxmaton EM (SAEM algorthm, a varant stochastc approxmaton of EM, s a versatle tool

More information

A General Class of Selection Procedures and Modified Murthy Estimator

A General Class of Selection Procedures and Modified Murthy Estimator ISS 684-8403 Journal of Statstcs Volume 4, 007,. 3-9 A General Class of Selecton Procedures and Modfed Murthy Estmator Abdul Bast and Muhammad Qasar Shahbaz Abstract A new selecton rocedure for unequal

More information

Physics 181. Particle Systems

Physics 181. Particle Systems Physcs 181 Partcle Systems Overvew In these notes we dscuss the varables approprate to the descrpton of systems of partcles, ther defntons, ther relatons, and ther conservatons laws. We consder a system

More information

6.3.4 Modified Euler s method of integration

6.3.4 Modified Euler s method of integration 6.3.4 Modfed Euler s method of ntegraton Before dscussng the applcaton of Euler s method for solvng the swng equatons, let us frst revew the basc Euler s method of numercal ntegraton. Let the general from

More information

A Dissimilarity Measure Based on Singular Value and Its Application in Incremental Discounting

A Dissimilarity Measure Based on Singular Value and Its Application in Incremental Discounting A Dssmarty Measure Based on Snguar Vaue and Its Appcaton n Incrementa Dscountng KE Xaou Department of Automaton, Unversty of Scence and Technoogy of Chna, Hefe, Chna Ema: kxu@ma.ustc.edu.cn MA Lyao Department

More information

Cyclic Codes BCH Codes

Cyclic Codes BCH Codes Cycc Codes BCH Codes Gaos Feds GF m A Gaos fed of m eements can be obtaned usng the symbos 0,, á, and the eements beng 0,, á, á, á 3 m,... so that fed F* s cosed under mutpcaton wth m eements. The operator

More information

LECTURE 21 Mohr s Method for Calculation of General Displacements. 1 The Reciprocal Theorem

LECTURE 21 Mohr s Method for Calculation of General Displacements. 1 The Reciprocal Theorem V. DEMENKO MECHANICS OF MATERIALS 05 LECTURE Mohr s Method for Cacuaton of Genera Dspacements The Recproca Theorem The recproca theorem s one of the genera theorems of strength of materas. It foows drect

More information

Modelli Clamfim Equazioni differenziali 7 ottobre 2013

Modelli Clamfim Equazioni differenziali 7 ottobre 2013 CLAMFIM Bologna Modell 1 @ Clamfm Equazon dfferenzal 7 ottobre 2013 professor Danele Rtell danele.rtell@unbo.t 1/18? Ordnary Dfferental Equatons A dfferental equaton s an equaton that defnes a relatonshp

More information

Predicting Model of Traffic Volume Based on Grey-Markov

Predicting Model of Traffic Volume Based on Grey-Markov Vo. No. Modern Apped Scence Predctng Mode of Traffc Voume Based on Grey-Marov Ynpeng Zhang Zhengzhou Muncpa Engneerng Desgn & Research Insttute Zhengzhou 5005 Chna Abstract Grey-marov forecastng mode of

More information

Physics 5153 Classical Mechanics. D Alembert s Principle and The Lagrangian-1

Physics 5153 Classical Mechanics. D Alembert s Principle and The Lagrangian-1 P. Guterrez Physcs 5153 Classcal Mechancs D Alembert s Prncple and The Lagrangan 1 Introducton The prncple of vrtual work provdes a method of solvng problems of statc equlbrum wthout havng to consder the

More information

D hh ν. Four-body charm semileptonic decay. Jim Wiss University of Illinois

D hh ν. Four-body charm semileptonic decay. Jim Wiss University of Illinois Four-body charm semeptonc decay Jm Wss Unversty of Inos D hh ν 1 1. ector domnance. Expected decay ntensty 3. SU(3) apped to D s φν 4. Anaytc forms for form factors 5. Non-parametrc form factors 6. Future

More information

Quality-of-Service Routing in Heterogeneous Networks with Optimal Buffer and Bandwidth Allocation

Quality-of-Service Routing in Heterogeneous Networks with Optimal Buffer and Bandwidth Allocation Purdue Unversty Purdue e-pubs ECE Technca Reorts Eectrca and Comuter Engneerng -6-007 Quaty-of-Servce Routng n Heterogeneous Networs wth Otma Buffer and Bandwdth Aocaton Waseem Sheh Purdue Unversty, waseem@urdue.edu

More information

Module 2. Random Processes. Version 2 ECE IIT, Kharagpur

Module 2. Random Processes. Version 2 ECE IIT, Kharagpur Module Random Processes Lesson 6 Functons of Random Varables After readng ths lesson, ou wll learn about cdf of functon of a random varable. Formula for determnng the pdf of a random varable. Let, X be

More information

Remark: Positive work is done on an object when the point of application of the force moves in the direction of the force.

Remark: Positive work is done on an object when the point of application of the force moves in the direction of the force. Unt 5 Work and Energy 5. Work and knetc energy 5. Work - energy theore 5.3 Potenta energy 5.4 Tota energy 5.5 Energy dagra o a ass-sprng syste 5.6 A genera study o the potenta energy curve 5. Work and

More information

ON A DETERMINATION OF THE INITIAL FUNCTIONS FROM THE OBSERVED VALUES OF THE BOUNDARY FUNCTIONS FOR THE SECOND-ORDER HYPERBOLIC EQUATION

ON A DETERMINATION OF THE INITIAL FUNCTIONS FROM THE OBSERVED VALUES OF THE BOUNDARY FUNCTIONS FOR THE SECOND-ORDER HYPERBOLIC EQUATION Advanced Mathematcal Models & Applcatons Vol.3, No.3, 2018, pp.215-222 ON A DETERMINATION OF THE INITIAL FUNCTIONS FROM THE OBSERVED VALUES OF THE BOUNDARY FUNCTIONS FOR THE SECOND-ORDER HYPERBOLIC EUATION

More information

Estimation: Part 2. Chapter GREG estimation

Estimation: Part 2. Chapter GREG estimation Chapter 9 Estmaton: Part 2 9. GREG estmaton In Chapter 8, we have seen that the regresson estmator s an effcent estmator when there s a lnear relatonshp between y and x. In ths chapter, we generalzed the

More information

An LSB Data Hiding Technique Using Prime Numbers

An LSB Data Hiding Technique Using Prime Numbers An LSB Data Hdng Technque Usng Prme Numbers Sandan Dey (), Aj Abraham (), Sugata Sanya (3) Anshn Software Prvate Lmted, Kokata 79 Centre for Quantfabe Quaty of Servce n Communcaton Systems Norwegan Unversty

More information

Numerical Heat and Mass Transfer

Numerical Heat and Mass Transfer Master degree n Mechancal Engneerng Numercal Heat and Mass Transfer 06-Fnte-Dfference Method (One-dmensonal, steady state heat conducton) Fausto Arpno f.arpno@uncas.t Introducton Why we use models and

More information

Economics 101. Lecture 4 - Equilibrium and Efficiency

Economics 101. Lecture 4 - Equilibrium and Efficiency Economcs 0 Lecture 4 - Equlbrum and Effcency Intro As dscussed n the prevous lecture, we wll now move from an envronment where we looed at consumers mang decsons n solaton to analyzng economes full of

More information

The Finite Element Method: A Short Introduction

The Finite Element Method: A Short Introduction Te Fnte Element Metod: A Sort ntroducton Wat s FEM? Te Fnte Element Metod (FEM) ntroduced by engneers n late 50 s and 60 s s a numercal tecnque for solvng problems wc are descrbed by Ordnary Dfferental

More information

Supplementary Material for Spectral Clustering based on the graph p-laplacian

Supplementary Material for Spectral Clustering based on the graph p-laplacian Sulementary Materal for Sectral Clusterng based on the grah -Lalacan Thomas Bühler and Matthas Hen Saarland Unversty, Saarbrücken, Germany {tb,hen}@csun-sbde May 009 Corrected verson, June 00 Abstract

More information

The Schultz Polynomial of Zigzag Polyhex Nanotubes

The Schultz Polynomial of Zigzag Polyhex Nanotubes Asan Journal of Chemstry Vol, No (9, 9-9 The Schultz Polynomal of Zgzag Polyhe Nanotubes MEHDI ELIASI and BIJAN TAERI* Deartment of Mathematcal Scences, Isfahan Unversty of Technology, Isfahan 86-8, Iran

More information

arxiv: v1 [cond-mat.stat-mech] 14 Mar 2018

arxiv: v1 [cond-mat.stat-mech] 14 Mar 2018 The statstcs of mesoscopc systems and the physcal nterpretaton of extensve and non-extensve entropes D. V. Anghel 1 and A. S. Parvan 1,2,3 1 Insttutul Natonal de Fzca s Ingnere Nucleara Hora Hulube, Magurele,

More information

Lectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix

Lectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix Lectures - Week 4 Matrx norms, Condtonng, Vector Spaces, Lnear Independence, Spannng sets and Bass, Null space and Range of a Matrx Matrx Norms Now we turn to assocatng a number to each matrx. We could

More information

Journal of Multivariate Analysis

Journal of Multivariate Analysis Journal of Multvarate Analyss 07 (202) 232 243 Contents lsts avalable at ScVerse ScenceDrect Journal of Multvarate Analyss journal homeage: www.elsever.com/locate/jmva James Sten tye estmators of varances

More information

ANSWERS. Problem 1. and the moment generating function (mgf) by. defined for any real t. Use this to show that E( U) var( U)

ANSWERS. Problem 1. and the moment generating function (mgf) by. defined for any real t. Use this to show that E( U) var( U) Econ 413 Exam 13 H ANSWERS Settet er nndelt 9 deloppgaver, A,B,C, som alle anbefales å telle lkt for å gøre det ltt lettere å stå. Svar er gtt . Unfortunately, there s a prntng error n the hnt of

More information

Robustness of the Second Law of Thermodynamics under Generalizations of the Maximum Entropy Method

Robustness of the Second Law of Thermodynamics under Generalizations of the Maximum Entropy Method Robustness of the Second Law of Thermodynamcs under Generalzatons of the Maxmum Entropy Method Sumyosh Abe Stefan Thurner SFI WORKING PAPER: 2007-08-023 SFI Workng Papers contan accounts of scentfc work

More information

NTRU Modulo p Flaw. Anas Ibrahim, Alexander Chefranov Computer Engineering Department Eastern Mediterranean University Famagusta, North Cyprus.

NTRU Modulo p Flaw. Anas Ibrahim, Alexander Chefranov Computer Engineering Department Eastern Mediterranean University Famagusta, North Cyprus. Internatonal Journal for Informaton Securty Research (IJISR), Volume 6, Issue 3, Setember 016 TRU Modulo Flaw Anas Ibrahm, Alexander Chefranov Comuter Engneerng Deartment Eastern Medterranean Unversty

More information

Advanced Circuits Topics - Part 1 by Dr. Colton (Fall 2017)

Advanced Circuits Topics - Part 1 by Dr. Colton (Fall 2017) Advanced rcuts Topcs - Part by Dr. olton (Fall 07) Part : Some thngs you should already know from Physcs 0 and 45 These are all thngs that you should have learned n Physcs 0 and/or 45. Ths secton s organzed

More information

Limited Dependent Variables

Limited Dependent Variables Lmted Dependent Varables. What f the left-hand sde varable s not a contnuous thng spread from mnus nfnty to plus nfnty? That s, gven a model = f (, β, ε, where a. s bounded below at zero, such as wages

More information

MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.265/15.070J Fall 2013 Lecture 12 10/21/2013. Martingale Concentration Inequalities and Applications

MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.265/15.070J Fall 2013 Lecture 12 10/21/2013. Martingale Concentration Inequalities and Applications MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.65/15.070J Fall 013 Lecture 1 10/1/013 Martngale Concentraton Inequaltes and Applcatons Content. 1. Exponental concentraton for martngales wth bounded ncrements.

More information

APPENDIX F A DISPLACEMENT-BASED BEAM ELEMENT WITH SHEAR DEFORMATIONS. Never use a Cubic Function Approximation for a Non-Prismatic Beam

APPENDIX F A DISPLACEMENT-BASED BEAM ELEMENT WITH SHEAR DEFORMATIONS. Never use a Cubic Function Approximation for a Non-Prismatic Beam APPENDIX F A DISPACEMENT-BASED BEAM EEMENT WITH SHEAR DEFORMATIONS Never use a Cubc Functon Approxmaton for a Non-Prsmatc Beam F. INTRODUCTION { XE "Shearng Deformatons" }In ths appendx a unque development

More information

k p theory for bulk semiconductors

k p theory for bulk semiconductors p theory for bu seconductors The attce perodc ndependent partce wave equaton s gven by p + V r + V p + δ H rψ ( r ) = εψ ( r ) (A) 4c In Eq. (A) V ( r ) s the effectve attce perodc potenta caused by the

More information

Thermodynamics and statistical mechanics in materials modelling II

Thermodynamics and statistical mechanics in materials modelling II Course MP3 Lecture 8/11/006 (JAE) Course MP3 Lecture 8/11/006 Thermodynamcs and statstcal mechancs n materals modellng II A bref résumé of the physcal concepts used n materals modellng Dr James Ellott.1

More information

Open Systems: Chemical Potential and Partial Molar Quantities Chemical Potential

Open Systems: Chemical Potential and Partial Molar Quantities Chemical Potential Open Systems: Chemcal Potental and Partal Molar Quanttes Chemcal Potental For closed systems, we have derved the followng relatonshps: du = TdS pdv dh = TdS + Vdp da = SdT pdv dg = VdP SdT For open systems,

More information

ON CERTAIN SUMS INVOLVING THE LEGENDRE SYMBOL. Borislav Karaivanov Sigma Space Inc., Lanham, Maryland

ON CERTAIN SUMS INVOLVING THE LEGENDRE SYMBOL. Borislav Karaivanov Sigma Space Inc., Lanham, Maryland #A14 INTEGERS 16 (2016) ON CERTAIN SUMS INVOLVING THE LEGENDRE SYMBOL Borisav Karaivanov Sigma Sace Inc., Lanham, Maryand borisav.karaivanov@sigmasace.com Tzvetain S. Vassiev Deartment of Comuter Science

More information

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X Statstcs 1: Probablty Theory II 37 3 EPECTATION OF SEVERAL RANDOM VARIABLES As n Probablty Theory I, the nterest n most stuatons les not on the actual dstrbuton of a random vector, but rather on a number

More information

Snce h( q^; q) = hq ~ and h( p^ ; p) = hp, one can wrte ~ h hq hp = hq ~hp ~ (7) the uncertanty relaton for an arbtrary state. The states that mnmze t

Snce h( q^; q) = hq ~ and h( p^ ; p) = hp, one can wrte ~ h hq hp = hq ~hp ~ (7) the uncertanty relaton for an arbtrary state. The states that mnmze t 8.5: Many-body phenomena n condensed matter and atomc physcs Last moded: September, 003 Lecture. Squeezed States In ths lecture we shall contnue the dscusson of coherent states, focusng on ther propertes

More information

A Unified Elementary Approach to the Dyson, Morris, Aomoto, and Forrester Constant Term Identities

A Unified Elementary Approach to the Dyson, Morris, Aomoto, and Forrester Constant Term Identities A Unfed Eementary Approach to the Dyson, Morrs, Aomoto, and Forrester Constant Term Identtes Ira M Gesse 1, Lun Lv, Guoce Xn 3, Yue Zhou 4 1 Department of Mathematcs Brandes Unversty, Watham, MA 0454-9110,

More information

Asymptotics of the Solution of a Boundary Value. Problem for One-Characteristic Differential. Equation Degenerating into a Parabolic Equation

Asymptotics of the Solution of a Boundary Value. Problem for One-Characteristic Differential. Equation Degenerating into a Parabolic Equation Nonl. Analyss and Dfferental Equatons, ol., 4, no., 5 - HIKARI Ltd, www.m-har.com http://dx.do.org/.988/nade.4.456 Asymptotcs of the Soluton of a Boundary alue Problem for One-Characterstc Dfferental Equaton

More information

( ) 2 ( ) ( ) Problem Set 4 Suggested Solutions. Problem 1

( ) 2 ( ) ( ) Problem Set 4 Suggested Solutions. Problem 1 Problem Set 4 Suggested Solutons Problem (A) The market demand functon s the soluton to the followng utlty-maxmzaton roblem (UMP): The Lagrangean: ( x, x, x ) = + max U x, x, x x x x st.. x + x + x y x,

More information

Lecture 6/7 (February 10/12, 2014) DIRAC EQUATION. The non-relativistic Schrödinger equation was obtained by noting that the Hamiltonian 2

Lecture 6/7 (February 10/12, 2014) DIRAC EQUATION. The non-relativistic Schrödinger equation was obtained by noting that the Hamiltonian 2 P470 Lecture 6/7 (February 10/1, 014) DIRAC EQUATION The non-relatvstc Schrödnger equaton was obtaned by notng that the Hamltonan H = P (1) m can be transformed nto an operator form wth the substtutons

More information

ON AUTOMATIC CONTINUITY OF DERIVATIONS FOR BANACH ALGEBRAS WITH INVOLUTION

ON AUTOMATIC CONTINUITY OF DERIVATIONS FOR BANACH ALGEBRAS WITH INVOLUTION European Journa of Mathematcs and Computer Scence Vo. No. 1, 2017 ON AUTOMATC CONTNUTY OF DERVATONS FOR BANACH ALGEBRAS WTH NVOLUTON Mohamed BELAM & Youssef T DL MATC Laboratory Hassan Unversty MORO CCO

More information

CHAPTER III Neural Networks as Associative Memory

CHAPTER III Neural Networks as Associative Memory CHAPTER III Neural Networs as Assocatve Memory Introducton One of the prmary functons of the bran s assocatve memory. We assocate the faces wth names, letters wth sounds, or we can recognze the people

More information

Mechanics Physics 151

Mechanics Physics 151 Mechancs Physcs 5 Lecture 0 Canoncal Transformatons (Chapter 9) What We Dd Last Tme Hamlton s Prncple n the Hamltonan formalsm Dervaton was smple δi δ p H(, p, t) = 0 Adonal end-pont constrants δ t ( )

More information

Chapter 6. Rotations and Tensors

Chapter 6. Rotations and Tensors Vector Spaces n Physcs 8/6/5 Chapter 6. Rotatons and ensors here s a speca knd of near transformaton whch s used to transforms coordnates from one set of axes to another set of axes (wth the same orgn).

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

SOME NOISELESS CODING THEOREM CONNECTED WITH HAVRDA AND CHARVAT AND TSALLIS S ENTROPY. 1. Introduction

SOME NOISELESS CODING THEOREM CONNECTED WITH HAVRDA AND CHARVAT AND TSALLIS S ENTROPY. 1. Introduction Kragujevac Journal of Mathematcs Volume 35 Number (20, Pages 7 SOME NOISELESS COING THEOREM CONNECTE WITH HAVRA AN CHARVAT AN TSALLIS S ENTROPY SATISH KUMAR AN RAJESH KUMAR 2 Abstract A new measure L,

More information

n-step cycle inequalities: facets for continuous n-mixing set and strong cuts for multi-module capacitated lot-sizing problem

n-step cycle inequalities: facets for continuous n-mixing set and strong cuts for multi-module capacitated lot-sizing problem n-step cyce nequates: facets for contnuous n-mxng set and strong cuts for mut-modue capactated ot-szng probem Mansh Bansa and Kavash Kanfar Department of Industra and Systems Engneerng, Texas A&M Unversty,

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

Solutions to exam in SF1811 Optimization, Jan 14, 2015

Solutions to exam in SF1811 Optimization, Jan 14, 2015 Solutons to exam n SF8 Optmzaton, Jan 4, 25 3 3 O------O -4 \ / \ / The network: \/ where all lnks go from left to rght. /\ / \ / \ 6 O------O -5 2 4.(a) Let x = ( x 3, x 4, x 23, x 24 ) T, where the varable

More information

Signal Processing 142 (2018) Contents lists available at ScienceDirect. Signal Processing. journal homepage:

Signal Processing 142 (2018) Contents lists available at ScienceDirect. Signal Processing. journal homepage: Sgna Processng 142 (218) 32 329 Contents sts avaabe at ScenceDrect Sgna Processng ourna homepage: www.esever.com/ocate/sgpro Sepan-Bangs-type formuas the reated Msspecfed Cramér-Rao Bounds for Compex Eptcay

More information

The Dirac Equation. Elementary Particle Physics Strong Interaction Fenomenology. Diego Bettoni Academic year

The Dirac Equation. Elementary Particle Physics Strong Interaction Fenomenology. Diego Bettoni Academic year The Drac Equaton Eleentary artcle hyscs Strong Interacton Fenoenology Dego Betton Acadec year - D Betton Fenoenologa Interazon Fort elatvstc equaton to descrbe the electron (ncludng ts sn) Conservaton

More information

Multispectral Remote Sensing Image Classification Algorithm Based on Rough Set Theory

Multispectral Remote Sensing Image Classification Algorithm Based on Rough Set Theory Proceedngs of the 2009 IEEE Internatona Conference on Systems Man and Cybernetcs San Antono TX USA - October 2009 Mutspectra Remote Sensng Image Cassfcaton Agorthm Based on Rough Set Theory Yng Wang Xaoyun

More information

MATH 281A: Homework #6

MATH 281A: Homework #6 MATH 28A: Homework #6 Jongha Ryu Due date: November 8, 206 Problem. (Problem 2..2. Soluton. If X,..., X n Bern(p, then T = X s a complete suffcent statstc. Our target s g(p = p, and the nave guess suggested

More information

Note 2. Ling fong Li. 1 Klein Gordon Equation Probablity interpretation Solutions to Klein-Gordon Equation... 2

Note 2. Ling fong Li. 1 Klein Gordon Equation Probablity interpretation Solutions to Klein-Gordon Equation... 2 Note 2 Lng fong L Contents Ken Gordon Equaton. Probabty nterpretaton......................................2 Soutons to Ken-Gordon Equaton............................... 2 2 Drac Equaton 3 2. Probabty nterpretaton.....................................

More information