NECESSARY AND SUFFICIENT CONDITIONS FOR LATENT SEPARABILITY

Size: px
Start display at page:

Download "NECESSARY AND SUFFICIENT CONDITIONS FOR LATENT SEPARABILITY"

Transcription

1 NECESSARY AND SUFFICIENT CONDITIONS FOR LATENT SEPARABILITY Ian Crawford THE INSTITUTE FOR FISCAL STUDIES DEPARTMENT OF ECONOMICS, UCL cemmap working paper CWP02/04

2 Neceary and Sufficien Condiion for Laen Separabiliy Ian A. Crawford Iniue for Fical Sudie Abrac Thi paper exend he nonparameric mehod developed by Samuelon (1948), Houhakker (1950), Afria (1973), Diewer (1973) and Varian (1982, 1983) o laenly eparable model. I preen neceary and ufficien empirical condiion under which daa on he marke behaviour of a price-aking conumer, and a hypoheied allocaion acro laen group are nonparamerically conien wih laen eparabiliy (Gorman (1968, 1978), Blundell and Robin (2000)). I conider homoheic laen eparabiliy and weak eparabiliy a pecial cae. Acknowledgemen Financial uppor from he ESRC Cenre for he Microeconomic Analyi of Public Policy and Leverhulme Cenre for Microdaa Mehod and Pracice i graefully acknowledged. The auhor i graeful o Richard Blundell for helpful commen, bu i reponible for all error. Wha are he obervable conequence of a model of conumer behaviour in which he conumer uiliy funcion i laenly eparable? The noion of laen eparabiliy wa inroduced in Gorman (1968) and (1978) and horoughly developed in Blundell and Robin (2000). So far he characeriaion of he condiion for laen eparabiliy ha been parameric. Thi paper eek neceary and ufficien nonparameric condiion for laen eparabiliy. Definiion 1. (Blundell and Robin, 2000) A direc uiliy funcion U : q R K + U (q) R i aid o aify laen eparabiliy if ( U (q) = max u v 1 eq 1,..., v M ) eq M MX eq m = q q 1,..., q M R K + where u, v 1 eq 1,..., v M eq M are regular uiliy funcion. Under a laenly eparable funcional rucure he conumer allocaion problem i a follow max u v 1 eq 1,..., v M eq M q 1,..., q M R K + ubjec o MX p 0 eqm = x m=1 in oher word hey chooe boh he oal quaniy vecor q and he laen allocaion {eq m } m=1,...,m in order o maximie heir uiliy ubjec o a budge conrain. Suppoe ha here are T obervaion (indexed =1,..., T )onk vecor of price and correponding demand {p, q }. Le {eq m } m=1,...,m where P M m=1 eqm = q denoe a hypoheied allocaion of hee quaniy vecor acro M laen group. When can hee daa and hypoheied allocaion be raionalied by a laenly eparable rucure? The following definiion make clear wha i mean by raionalie in hi conex. m=1

3 Definiion 2. A laenly eparable uiliy funcion raionalie he daa {p, q } and he allocaion {eq m } m=1,...,m if u v 1 eq 1,..., v M eq M u v 1 eq 1,..., v M eq M for all alernaive allocaion {eq m } m=1,...,m uch ha p 0 q P M m=1 p0 eqm. The fir Theorem preen he condiion under which here exi a laenly eparable model of conumer preference which raionalie he daa and he hypoheied allocaion. Theorem 1. The following aemen are equivalen: (U) There exi a laenly eparable uiliy funcion, where u (v) and v m (eq m ) are nonaiaed, monoonic, concave and coninuou funcion, which raionalie he daa {p, q } and he allocaion {eq m } m=1,...,m. (A) There exi number {U,λ } and M vecor {V, ρ } uch ha for all,, m U U + λ ρ 0 (V V ) (A.1) V m V m + 1 ρ m p 0 (eq m eq m ) (G) The daa {p, eq m } m=1,...,m aify he Generalied Axiom of Revealed Preference (GARP) and he daa {V, ρ } alo aify GARP for ome choice of {V, ρ } which aify Proof (U) (A) : Fir conider he implicaion of opimiing behaviour and he fir order condiion from he conumer problem. Coninuiy enure ha uiable ubgradien exi uch ha u (eq m ) λ p where u (eq m )= u(vm ) vm (eq m ). Define λ ρ m = u (v m ). Then v m (eq m ) (ρ m ) 1 p. Now conider he concaviy condiion for hi rucure u (v ) u (v )+ u(v ) 0 (v v ) v m (eq m ) v m (eq m )+ v m (eq m ) 0 (eq m eq m ) Subiuing in v m (eq m ) (ρ m ) 1 p and λ ρ m = u (v m ) preerve he inequaliie and give u (v ) u (v )+λ ρ 0 (v v ) v m (eq m ) v m (eq m )+ 1 ρ m p 0 (eq m eq m ) which are condiion (A.1) and. (A) (U) :Suppoewehavenumber{U,λ } and M vecor {V, ρ } uch ha condiion (A) hold. Conider ome arbirary {eq m } m=1,...,m uch ha p 0 q P M m=1 p0 eqm. We need o how ha here exi a laenly eparable uiliy funcion, wih he aed properie uch ha u v 1 eq 1,..., v M eq M u v 1 eq 1,..., v M eq M. Uing we can conruc T upper bound on v m (eq m ) and if we ake he minimum of hee a he funcion v m (eq m ) hen we have a piecewie linear, nonaiaed, monoonic, concave and coninuou uiliy funcion ½ v m (eq m )=min V m + 1 ¾ ρ m p 0 (eq m eq m ) V m + 1 ρ m p 0 (eq m eq m ) =1,...,T

4 Summing hi inequaliy over m give ρ 0 V p 0 q ρ 0 V p 0 eq where V = 0, V 1,..., V M V = V 1,...,V M 0, (V m = v m (eq m ))andρ = ρ 1,...ρ M. Then ince p 0 q p 0 eq we have ρ0 V ρ 0 V. Uing (A.3) we can imilarly conruc he following macro-uiliy funcion U (V) =min{u + λ ρ 0 (V V )} =1,...,T U + λ ρ 0 (V V ) Since λ ρ 0 (V V ) 0 we have U (V) U a required. (A) (G) : Follow from Afria Theorem. One pecial cae of paricular empirical inere i he one in which he laen uiliy funcion v (eq m ) are homoheic (Gorman (1968), Blundell and Robin (2000)). Theorem 2. The following aemen are equivalen: (U) There exi a homoheically laenly eparable uiliy funcion, where u (v) and v m (eq m ) are nonaiaed, monoonic, concave and coninuou funcion and v m (eq m ) are homoheic, which raionalie he daa {p, q } and he allocaion {eq m } m=1,...,m. (A) There exi number {U,λ } and M vecor {V, ρ } uch ha for all,, m U U + λ ρ 0 (V V ) (A.1) V m V m + 1 ρ m p 0 (eq m eq m ) ρ m V m = p 0 eqm (A.3) (G) The daa {p, eq m }m=1,...,m aify he Homoheic Axiom of Revealed Preference (HARP) and he daa {V, ρ } alo aify GARP for ome choice of {V, ρ } which aify and (A.3) Proof Analogou o Theorem 1 noing ha and (A.3) are neceary and ufficien for he exience of M homoheic uiliy funcion V m (eq m ) uch ha for any eq m wih ha p 0 eqm p 0 eqm hen V m (eq m ) V m (eq m ) (Varian (1983), Theorem 2). Anoher pecial cae concern he iuaion when he allocaion of good acro laen uiliie i excluive a hi correpond o weak eparabiliy. Theorem 3. When he hypoheied allocaion are uch ha eq k,m = q k for all k and and ome m (ha i he allocaion o laen group are excluive and conan over obervaion), hen he condiion in Theorem 1 and 2 are equivalen o hoe for weak eparabiliy and homoheic weak eparabiliy repecively.

5 Proof Obviou from a comparion wih Varian (1983) Theorem 3 and 5. I canno hink of any way in which eiher he number or he compoiion of he laen group can be nonparamerically idenified from he oberved daa. Inead he Theorem preened are imply a way of eing he daa and any hypoheied allocaion for coniency wih he model. In hi repec he reul here are imilar o Varian (1983) for weak eparabiliy, where he number and makeup of eparable ubgroup are no idenified from daa, bu where he condiion under which any hypoheied grouping are raionaliable wih weak eparabiliy are e ou. Noe ha he reul here can alo be applied o he analyi of producion funcion wih a uiable change in he inerpreaion of he noaion and by requiring he op-level daa o aify he weak axiom of profi maximiaion raher han GARP (ee Varian (1984), Theorem 9, for he condiion for weak eparabiliy in producion funcion). Reference [1] Afria, S.N. (1973), On a yem of inequaliie in demand analyi: An exenion of he claical mehod, Inernaional Economic Review, 14, [2] Blundell, R. W. and J-M Robin (2000), Laen eparabiliy: grouping good wihou weak eparabiliy, Economerica, 68, [3] Diewer, W.E. (1973), Afria and revealed preference heory, Review of Economic Sudie, 40, [4] Gorman, W. M. (1968), Meauring he quaniie of fixed facor, in Value Capial and Growh: Eay in Honour of Sir John Hick, ed. by J,N, Wolfe. Edinburgh: Edinburgh Univeriy Pre. Alo in Separabiliy and Aggregaion, Vol 1, Colleced Work of W. M. Gorman, C. Blackorby and A. Shorrock (ed.), Oxford: Clarendon Pre. [5] Gorman, W. M. (1978), More meaure for fixed facor,, in Separabiliy and Aggregaion, Vol1,CollecedWorkofW.M.Gorman, C. Blackorby and A. Shorrock (ed.), Oxford: Clarendon Pre. [6] Houhakker, H. S. (1950), Revealed preference and he uiliy funcion, Economica, May, [7] Samuelon, P. (1948), Conumpion heory in erm of revealed preference, Economica, November, [8] Varian, H. (1982), The nonparameric approach o demand analyi, Economerica, 50, [9] Varian, H. (1983), Nonparameric e of conumer behaviour, Review of Economic Sudie, L, [10] Varian, H. (1984), The nonparameric approach o producion analyi", Economerica, 52,

Laplace Transform. Inverse Laplace Transform. e st f(t)dt. (2)

Laplace Transform. Inverse Laplace Transform. e st f(t)dt. (2) Laplace Tranform Maoud Malek The Laplace ranform i an inegral ranform named in honor of mahemaician and aronomer Pierre-Simon Laplace, who ued he ranform in hi work on probabiliy heory. I i a powerful

More information

, the. L and the L. x x. max. i n. It is easy to show that these two norms satisfy the following relation: x x n x = (17.3) max

, the. L and the L. x x. max. i n. It is easy to show that these two norms satisfy the following relation: x x n x = (17.3) max ecure 8 7. Sabiliy Analyi For an n dimenional vecor R n, he and he vecor norm are defined a: = T = i n i (7.) I i eay o how ha hee wo norm aify he following relaion: n (7.) If a vecor i ime-dependen, hen

More information

FIXED POINTS AND STABILITY IN NEUTRAL DIFFERENTIAL EQUATIONS WITH VARIABLE DELAYS

FIXED POINTS AND STABILITY IN NEUTRAL DIFFERENTIAL EQUATIONS WITH VARIABLE DELAYS PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY Volume 136, Number 3, March 28, Page 99 918 S 2-9939(7)989-2 Aricle elecronically publihed on November 3, 27 FIXED POINTS AND STABILITY IN NEUTRAL DIFFERENTIAL

More information

1 Motivation and Basic Definitions

1 Motivation and Basic Definitions CSCE : Deign and Analyi of Algorihm Noe on Max Flow Fall 20 (Baed on he preenaion in Chaper 26 of Inroducion o Algorihm, 3rd Ed. by Cormen, Leieron, Rive and Sein.) Moivaion and Baic Definiion Conider

More information

Flow networks. Flow Networks. A flow on a network. Flow networks. The maximum-flow problem. Introduction to Algorithms, Lecture 22 December 5, 2001

Flow networks. Flow Networks. A flow on a network. Flow networks. The maximum-flow problem. Introduction to Algorithms, Lecture 22 December 5, 2001 CS 545 Flow Nework lon Efra Slide courey of Charle Leieron wih mall change by Carola Wenk Flow nework Definiion. flow nework i a direced graph G = (V, E) wih wo diinguihed verice: a ource and a ink. Each

More information

Lecture 26. Lucas and Stokey: Optimal Monetary and Fiscal Policy in an Economy without Capital (JME 1983) t t

Lecture 26. Lucas and Stokey: Optimal Monetary and Fiscal Policy in an Economy without Capital (JME 1983) t t Lecure 6. Luca and Sokey: Opimal Moneary and Fical Policy in an Economy wihou Capial (JME 983. A argued in Kydland and Preco (JPE 977, Opimal governmen policy i likely o be ime inconien. Fiher (JEDC 98

More information

Lower and Upper Approximation of Fuzzy Ideals in a Semiring

Lower and Upper Approximation of Fuzzy Ideals in a Semiring nernaional Journal of Scienific & Engineering eearch, Volume 3, ue, January-0 SSN 9-558 Lower and Upper Approximaion of Fuzzy deal in a Semiring G Senhil Kumar, V Selvan Abrac n hi paper, we inroduce he

More information

Problem Set If all directed edges in a network have distinct capacities, then there is a unique maximum flow.

Problem Set If all directed edges in a network have distinct capacities, then there is a unique maximum flow. CSE 202: Deign and Analyi of Algorihm Winer 2013 Problem Se 3 Inrucor: Kamalika Chaudhuri Due on: Tue. Feb 26, 2013 Inrucion For your proof, you may ue any lower bound, algorihm or daa rucure from he ex

More information

Introduction to Congestion Games

Introduction to Congestion Games Algorihmic Game Theory, Summer 2017 Inroducion o Congeion Game Lecure 1 (5 page) Inrucor: Thoma Keelheim In hi lecure, we ge o know congeion game, which will be our running example for many concep in game

More information

Notes on cointegration of real interest rates and real exchange rates. ρ (2)

Notes on cointegration of real interest rates and real exchange rates. ρ (2) Noe on coinegraion of real inere rae and real exchange rae Charle ngel, Univeriy of Wiconin Le me ar wih he obervaion ha while he lieraure (mo prominenly Meee and Rogoff (988) and dion and Paul (993))

More information

Generalized Orlicz Spaces and Wasserstein Distances for Convex-Concave Scale Functions

Generalized Orlicz Spaces and Wasserstein Distances for Convex-Concave Scale Functions Generalized Orlicz Space and Waerein Diance for Convex-Concave Scale Funcion Karl-Theodor Surm Abrac Given a ricly increaing, coninuou funcion ϑ : R + R +, baed on he co funcional ϑ (d(x, y dq(x, y, we

More information

EECE 301 Signals & Systems Prof. Mark Fowler

EECE 301 Signals & Systems Prof. Mark Fowler EECE 31 Signal & Syem Prof. Mark Fowler Noe Se #27 C-T Syem: Laplace Tranform Power Tool for yem analyi Reading Aignmen: Secion 6.1 6.3 of Kamen and Heck 1/18 Coure Flow Diagram The arrow here how concepual

More information

FLAT CYCLOTOMIC POLYNOMIALS OF ORDER FOUR AND HIGHER

FLAT CYCLOTOMIC POLYNOMIALS OF ORDER FOUR AND HIGHER #A30 INTEGERS 10 (010), 357-363 FLAT CYCLOTOMIC POLYNOMIALS OF ORDER FOUR AND HIGHER Nahan Kaplan Deparmen of Mahemaic, Harvard Univeriy, Cambridge, MA nkaplan@mah.harvard.edu Received: 7/15/09, Revied:

More information

FUZZY n-inner PRODUCT SPACE

FUZZY n-inner PRODUCT SPACE Bull. Korean Mah. Soc. 43 (2007), No. 3, pp. 447 459 FUZZY n-inner PRODUCT SPACE Srinivaan Vijayabalaji and Naean Thillaigovindan Reprined from he Bullein of he Korean Mahemaical Sociey Vol. 43, No. 3,

More information

Investment-specific Technology Shocks, Neutral Technology Shocks and the Dunlop-Tarshis Observation: Theory and Evidence

Investment-specific Technology Shocks, Neutral Technology Shocks and the Dunlop-Tarshis Observation: Theory and Evidence Invemen-pecific Technology Shock, Neural Technology Shock and he Dunlop-Tarhi Obervaion: Theory and Evidence Moren O. Ravn, European Univeriy Iniue and he CEPR Saverio Simonelli, European Univeriy Iniue

More information

Stability in Distribution for Backward Uncertain Differential Equation

Stability in Distribution for Backward Uncertain Differential Equation Sabiliy in Diribuion for Backward Uncerain Differenial Equaion Yuhong Sheng 1, Dan A. Ralecu 2 1. College of Mahemaical and Syem Science, Xinjiang Univeriy, Urumqi 8346, China heng-yh12@mail.inghua.edu.cn

More information

T-Rough Fuzzy Subgroups of Groups

T-Rough Fuzzy Subgroups of Groups Journal of mahemaic and compuer cience 12 (2014), 186-195 T-Rough Fuzzy Subgroup of Group Ehagh Hoeinpour Deparmen of Mahemaic, Sari Branch, Ilamic Azad Univeriy, Sari, Iran. hoienpor_a51@yahoo.com Aricle

More information

CSC 364S Notes University of Toronto, Spring, The networks we will consider are directed graphs, where each edge has associated with it

CSC 364S Notes University of Toronto, Spring, The networks we will consider are directed graphs, where each edge has associated with it CSC 36S Noe Univeriy of Torono, Spring, 2003 Flow Algorihm The nework we will conider are direced graph, where each edge ha aociaed wih i a nonnegaive capaciy. The inuiion i ha if edge (u; v) ha capaciy

More information

CHAPTER 7: SECOND-ORDER CIRCUITS

CHAPTER 7: SECOND-ORDER CIRCUITS EEE5: CI RCUI T THEORY CHAPTER 7: SECOND-ORDER CIRCUITS 7. Inroducion Thi chaper conider circui wih wo orage elemen. Known a econd-order circui becaue heir repone are decribed by differenial equaion ha

More information

18 Extensions of Maximum Flow

18 Extensions of Maximum Flow Who are you?" aid Lunkwill, riing angrily from hi ea. Wha do you wan?" I am Majikhie!" announced he older one. And I demand ha I am Vroomfondel!" houed he younger one. Majikhie urned on Vroomfondel. I

More information

Fractional Ornstein-Uhlenbeck Bridge

Fractional Ornstein-Uhlenbeck Bridge WDS'1 Proceeding of Conribued Paper, Par I, 21 26, 21. ISBN 978-8-7378-139-2 MATFYZPRESS Fracional Ornein-Uhlenbeck Bridge J. Janák Charle Univeriy, Faculy of Mahemaic and Phyic, Prague, Czech Republic.

More information

ANSWERS TO ODD NUMBERED EXERCISES IN CHAPTER

ANSWERS TO ODD NUMBERED EXERCISES IN CHAPTER John Riley 6 December 200 NWER TO ODD NUMBERED EXERCIE IN CHPTER 7 ecion 7 Exercie 7-: m m uppoe ˆ, m=,, M (a For M = 2, i i eay o how ha I implie I From I, for any probabiliy vecor ( p, p 2, 2 2 ˆ ( p,

More information

Let. x y. denote a bivariate time series with zero mean.

Let. x y. denote a bivariate time series with zero mean. Linear Filer Le x y : T denoe a bivariae ime erie wih zero mean. Suppoe ha he ime erie {y : T} i conruced a follow: y a x The ime erie {y : T} i aid o be conruced from {x : T} by mean of a Linear Filer.

More information

Price of Stability and Introduction to Mechanism Design

Price of Stability and Introduction to Mechanism Design Algorihmic Game Theory Summer 2017, Week 5 ETH Zürich Price of Sabiliy and Inroducion o Mechanim Deign Paolo Penna Thi i he lecure where we ar deigning yem which involve elfih player. Roughly peaking,

More information

6.8 Laplace Transform: General Formulas

6.8 Laplace Transform: General Formulas 48 HAP. 6 Laplace Tranform 6.8 Laplace Tranform: General Formula Formula Name, ommen Sec. F() l{ f ()} e f () d f () l {F()} Definiion of Tranform Invere Tranform 6. l{af () bg()} al{f ()} bl{g()} Lineariy

More information

Network Flows: Introduction & Maximum Flow

Network Flows: Introduction & Maximum Flow CSC 373 - lgorihm Deign, nalyi, and Complexiy Summer 2016 Lalla Mouaadid Nework Flow: Inroducion & Maximum Flow We now urn our aenion o anoher powerful algorihmic echnique: Local Search. In a local earch

More information

CHAPTER 7: UNCERTAINTY

CHAPTER 7: UNCERTAINTY Eenial Microeconomic - ecion 7-3, 7-4 CHPTER 7: UNCERTINTY Fir and econd order ochaic dominance 2 Mean preerving pread 8 Condiional ochaic Dominance 0 Monoone Likelihood Raio Propery 2 Coninuou diribuion

More information

Intermediate Macro In-Class Problems

Intermediate Macro In-Class Problems Inermediae Macro In-Class Problems Exploring Romer Model June 14, 016 Today we will explore he mechanisms of he simply Romer model by exploring how economies described by his model would reac o exogenous

More information

Macroeconomics 1. Ali Shourideh. Final Exam

Macroeconomics 1. Ali Shourideh. Final Exam 4780 - Macroeconomic 1 Ali Shourideh Final Exam Problem 1. A Model of On-he-Job Search Conider he following verion of he McCall earch model ha allow for on-he-job-earch. In paricular, uppoe ha ime i coninuou

More information

Randomized Perfect Bipartite Matching

Randomized Perfect Bipartite Matching Inenive Algorihm Lecure 24 Randomized Perfec Biparie Maching Lecurer: Daniel A. Spielman April 9, 208 24. Inroducion We explain a randomized algorihm by Ahih Goel, Michael Kapralov and Sanjeev Khanna for

More information

arxiv:math/ v2 [math.fa] 30 Jul 2006

arxiv:math/ v2 [math.fa] 30 Jul 2006 ON GÂTEAUX DIFFERENTIABILITY OF POINTWISE LIPSCHITZ MAPPINGS arxiv:mah/0511565v2 [mah.fa] 30 Jul 2006 JAKUB DUDA Abrac. We prove ha for every funcion f : X Y, where X i a eparable Banach pace and Y i a

More information

Suggested Solutions to Midterm Exam Econ 511b (Part I), Spring 2004

Suggested Solutions to Midterm Exam Econ 511b (Part I), Spring 2004 Suggeed Soluion o Miderm Exam Econ 511b (Par I), Spring 2004 1. Conider a compeiive equilibrium neoclaical growh model populaed by idenical conumer whoe preference over conumpion ream are given by P β

More information

To become more mathematically correct, Circuit equations are Algebraic Differential equations. from KVL, KCL from the constitutive relationship

To become more mathematically correct, Circuit equations are Algebraic Differential equations. from KVL, KCL from the constitutive relationship Laplace Tranform (Lin & DeCarlo: Ch 3) ENSC30 Elecric Circui II The Laplace ranform i an inegral ranformaion. I ranform: f ( ) F( ) ime variable complex variable From Euler > Lagrange > Laplace. Hence,

More information

Inequality measures for intersecting Lorenz curves: an alternative weak ordering

Inequality measures for intersecting Lorenz curves: an alternative weak ordering h Inernaional Scienific Conference Financial managemen of Firms and Financial Insiuions Osrava VŠB-TU of Osrava, Faculy of Economics, Deparmen of Finance 7 h 8 h Sepember 25 Absrac Inequaliy measures for

More information

Introduction to SLE Lecture Notes

Introduction to SLE Lecture Notes Inroducion o SLE Lecure Noe May 13, 16 - The goal of hi ecion i o find a ufficien condiion of λ for he hull K o be generaed by a imple cure. I urn ou if λ 1 < 4 hen K i generaed by a imple curve. We will

More information

Algorithmic Discrete Mathematics 6. Exercise Sheet

Algorithmic Discrete Mathematics 6. Exercise Sheet Algorihmic Dicree Mahemaic. Exercie Shee Deparmen of Mahemaic SS 0 PD Dr. Ulf Lorenz 7. and 8. Juni 0 Dipl.-Mah. David Meffer Verion of June, 0 Groupwork Exercie G (Heap-Sor) Ue Heap-Sor wih a min-heap

More information

4/12/12. Applications of the Maxflow Problem 7.5 Bipartite Matching. Bipartite Matching. Bipartite Matching. Bipartite matching: the flow network

4/12/12. Applications of the Maxflow Problem 7.5 Bipartite Matching. Bipartite Matching. Bipartite Matching. Bipartite matching: the flow network // Applicaion of he Maxflow Problem. Biparie Maching Biparie Maching Biparie maching. Inpu: undireced, biparie graph = (, E). M E i a maching if each node appear in a mo one edge in M. Max maching: find

More information

Problem Set #3: AK models

Problem Set #3: AK models Universiy of Warwick EC9A2 Advanced Macroeconomic Analysis Problem Se #3: AK models Jorge F. Chavez December 3, 2012 Problem 1 Consider a compeiive economy, in which he level of echnology, which is exernal

More information

What is maximum Likelihood? History Features of ML method Tools used Advantages Disadvantages Evolutionary models

What is maximum Likelihood? History Features of ML method Tools used Advantages Disadvantages Evolutionary models Wha i maximum Likelihood? Hiory Feaure of ML mehod Tool ued Advanage Diadvanage Evoluionary model Maximum likelihood mehod creae all he poible ree conaining he e of organim conidered, and hen ue he aiic

More information

Chapter 6. Laplace Transforms

Chapter 6. Laplace Transforms Chaper 6. Laplace Tranform Kreyzig by YHLee;45; 6- An ODE i reduced o an algebraic problem by operaional calculu. The equaion i olved by algebraic manipulaion. The reul i ranformed back for he oluion of

More information

CSE 521: Design & Analysis of Algorithms I

CSE 521: Design & Analysis of Algorithms I CSE 52: Deign & Analyi of Algorihm I Nework Flow Paul Beame Biparie Maching Given: A biparie graph G=(V,E) M E i a maching in G iff no wo edge in M hare a verex Goal: Find a maching M in G of maximum poible

More information

Syntactic Complexity of Suffix-Free Languages. Marek Szykuła

Syntactic Complexity of Suffix-Free Languages. Marek Szykuła Inroducion Upper Bound on Synacic Complexiy of Suffix-Free Language Univeriy of Wrocław, Poland Join work wih Januz Brzozowki Univeriy of Waerloo, Canada DCFS, 25.06.2015 Abrac Inroducion Sae and ynacic

More information

Physics 240: Worksheet 16 Name

Physics 240: Worksheet 16 Name Phyic 4: Workhee 16 Nae Non-unifor circular oion Each of hee proble involve non-unifor circular oion wih a conan α. (1) Obain each of he equaion of oion for non-unifor circular oion under a conan acceleraion,

More information

Reminder: Flow Networks

Reminder: Flow Networks 0/0/204 Ma/CS 6a Cla 4: Variou (Flow) Execie Reminder: Flow Nework A flow nework i a digraph G = V, E, ogeher wih a ource verex V, a ink verex V, and a capaciy funcion c: E N. Capaciy Source 7 a b c d

More information

Graphs III - Network Flow

Graphs III - Network Flow Graph III - Nework Flow Flow nework eup graph G=(V,E) edge capaciy w(u,v) 0 - if edge doe no exi, hen w(u,v)=0 pecial verice: ource verex ; ink verex - no edge ino and no edge ou of Aume every verex v

More information

The generalized deniion allow u for inance o deal wih parial averaging of yem wih diurbance (for ome claical reul on parial averaging ee [3, pp

The generalized deniion allow u for inance o deal wih parial averaging of yem wih diurbance (for ome claical reul on parial averaging ee [3, pp Averaging wih repec o arbirary cloed e: cloene of oluion for yem wih diurbance A.R.Teel 1, Dep. of Elec. and Comp. Eng., Univeriy of California, Sana Barbara, CA, 93106-9560 D.Neic Dep. of Elec. and Elecronic

More information

IMPLICIT AND INVERSE FUNCTION THEOREMS PAUL SCHRIMPF 1 OCTOBER 25, 2013

IMPLICIT AND INVERSE FUNCTION THEOREMS PAUL SCHRIMPF 1 OCTOBER 25, 2013 IMPLICI AND INVERSE FUNCION HEOREMS PAUL SCHRIMPF 1 OCOBER 25, 213 UNIVERSIY OF BRIISH COLUMBIA ECONOMICS 526 We have exensively sudied how o solve sysems of linear equaions. We know how o check wheher

More information

About the Pricing Equation in Finance

About the Pricing Equation in Finance Abou he Pricing Equaion in Finance Séphane Crépey Déparemen de Mahémaique Univerié d Évry Val d Eonne 91025 Évry Cedex, France Thi verion: July 10, 2007 1 Inroducion In [16], we conruced a raher generic

More information

Stat13 Homework 7. Suggested Solutions

Stat13 Homework 7. Suggested Solutions Sa3 Homework 7 hp://www.a.ucla.edu/~dinov/coure_uden.hml Suggeed Soluion Queion 7.50 Le denoe infeced and denoe noninfeced. H 0 : Malaria doe no affec red cell coun (µ µ ) H A : Malaria reduce red cell

More information

Classification of 3-Dimensional Complex Diassociative Algebras

Classification of 3-Dimensional Complex Diassociative Algebras Malayian Journal of Mahemaical Science 4 () 41-54 (010) Claificaion of -Dimenional Complex Diaociaive Algebra 1 Irom M. Rihiboev, Iamiddin S. Rahimov and Wiriany Bari 1,, Iniue for Mahemaical Reearch,,

More information

Convergence of the gradient algorithm for linear regression models in the continuous and discrete time cases

Convergence of the gradient algorithm for linear regression models in the continuous and discrete time cases Convergence of he gradien algorihm for linear regreion model in he coninuou and dicree ime cae Lauren Praly To cie hi verion: Lauren Praly. Convergence of he gradien algorihm for linear regreion model

More information

Math 2142 Exam 1 Review Problems. x 2 + f (0) 3! for the 3rd Taylor polynomial at x = 0. To calculate the various quantities:

Math 2142 Exam 1 Review Problems. x 2 + f (0) 3! for the 3rd Taylor polynomial at x = 0. To calculate the various quantities: Mah 4 Eam Review Problems Problem. Calculae he 3rd Taylor polynomial for arcsin a =. Soluion. Le f() = arcsin. For his problem, we use he formula f() + f () + f ()! + f () 3! for he 3rd Taylor polynomial

More information

Algorithms and Data Structures 2011/12 Week 9 Solutions (Tues 15th - Fri 18th Nov)

Algorithms and Data Structures 2011/12 Week 9 Solutions (Tues 15th - Fri 18th Nov) Algorihm and Daa Srucure 2011/ Week Soluion (Tue 15h - Fri 18h No) 1. Queion: e are gien 11/16 / 15/20 8/13 0/ 1/ / 11/1 / / To queion: (a) Find a pair of ube X, Y V uch ha f(x, Y) = f(v X, Y). (b) Find

More information

AN ANALYTICAL METHOD OF SOLUTION FOR SYSTEMS OF BOOLEAN EQUATIONS

AN ANALYTICAL METHOD OF SOLUTION FOR SYSTEMS OF BOOLEAN EQUATIONS CHAPTER 5 AN ANALYTICAL METHOD OF SOLUTION FOR SYSTEMS OF BOOLEAN EQUATIONS 51 APPLICATIONS OF DE MORGAN S LAWS A we have een in Secion 44 of Chaer 4, any Boolean Equaion of ye (1), (2) or (3) could be

More information

On the Benney Lin and Kawahara Equations

On the Benney Lin and Kawahara Equations JOURNAL OF MATEMATICAL ANALYSIS AND APPLICATIONS 11, 13115 1997 ARTICLE NO AY975438 On he BenneyLin and Kawahara Equaion A Biagioni* Deparmen of Mahemaic, UNICAMP, 1381-97, Campina, Brazil and F Linare

More information

CS4445/9544 Analysis of Algorithms II Solution for Assignment 1

CS4445/9544 Analysis of Algorithms II Solution for Assignment 1 Conider he following flow nework CS444/944 Analyi of Algorihm II Soluion for Aignmen (0 mark) In he following nework a minimum cu ha capaciy 0 Eiher prove ha hi aemen i rue, or how ha i i fale Uing he

More information

Exercises, Part IV: THE LONG RUN

Exercises, Part IV: THE LONG RUN Exercie, Par IV: THE LOG RU 4. The olow Growh Model onider he olow rowh model wihou echnoloy prore and wih conan populaion. a) Define he eady ae condiion and repreen i raphically. b) how he effec of chane

More information

Flow Networks. Ma/CS 6a. Class 14: Flow Exercises

Flow Networks. Ma/CS 6a. Class 14: Flow Exercises 0/0/206 Ma/CS 6a Cla 4: Flow Exercie Flow Nework A flow nework i a digraph G = V, E, ogeher wih a ource verex V, a ink verex V, and a capaciy funcion c: E N. Capaciy Source 7 a b c d e Sink 0/0/206 Flow

More information

Analysis of a Non-Autonomous Non-Linear Operator-Valued Evolution Equation to Diagonalize Quadratic Operators in Boson Quantum Field Theory

Analysis of a Non-Autonomous Non-Linear Operator-Valued Evolution Equation to Diagonalize Quadratic Operators in Boson Quantum Field Theory 1 Analyi of a Non-Auonomou Non-Linear Operaor-Valued Evoluion Equaion o Diagonalize Quadraic Operaor in Boon Quanum Field Theory Volker Bach and Jean-Bernard Bru Abrac. We udy a non auonomou, non-linear

More information

ANALYSIS OF SOME SAFETY ASSESSMENT STANDARD ON GROUNDING SYSTEMS

ANALYSIS OF SOME SAFETY ASSESSMENT STANDARD ON GROUNDING SYSTEMS ANAYSIS OF SOME SAFETY ASSESSMENT STANDARD ON GROUNDING SYSTEMS Shang iqun, Zhang Yan, Cheng Gang School of Elecrical and Conrol Engineering, Xi an Univeriy of Science & Technology, 710054, Xi an, China,

More information

5.1 - Logarithms and Their Properties

5.1 - Logarithms and Their Properties Chaper 5 Logarihmic Funcions 5.1 - Logarihms and Their Properies Suppose ha a populaion grows according o he formula P 10, where P is he colony size a ime, in hours. When will he populaion be 2500? We

More information

EE Control Systems LECTURE 2

EE Control Systems LECTURE 2 Copyrigh F.L. Lewi 999 All righ reerved EE 434 - Conrol Syem LECTURE REVIEW OF LAPLACE TRANSFORM LAPLACE TRANSFORM The Laplace ranform i very ueful in analyi and deign for yem ha are linear and ime-invarian

More information

CHAPTER 7. Definition and Properties. of Laplace Transforms

CHAPTER 7. Definition and Properties. of Laplace Transforms SERIES OF CLSS NOTES FOR 5-6 TO INTRODUCE LINER ND NONLINER PROBLEMS TO ENGINEERS, SCIENTISTS, ND PPLIED MTHEMTICINS DE CLSS NOTES COLLECTION OF HNDOUTS ON SCLR LINER ORDINRY DIFFERENTIL EQUTIONS (ODE")

More information

ESTIMATES FOR THE DERIVATIVE OF DIFFUSION SEMIGROUPS

ESTIMATES FOR THE DERIVATIVE OF DIFFUSION SEMIGROUPS Elec. Comm. in Probab. 3 (998) 65 74 ELECTRONIC COMMUNICATIONS in PROBABILITY ESTIMATES FOR THE DERIVATIVE OF DIFFUSION SEMIGROUPS L.A. RINCON Deparmen of Mahemaic Univeriy of Wale Swanea Singleon Par

More information

Research Article An Upper Bound on the Critical Value β Involved in the Blasius Problem

Research Article An Upper Bound on the Critical Value β Involved in the Blasius Problem Hindawi Publihing Corporaion Journal of Inequaliie and Applicaion Volume 2010, Aricle ID 960365, 6 page doi:10.1155/2010/960365 Reearch Aricle An Upper Bound on he Criical Value Involved in he Blaiu Problem

More information

Intermediate Solutions for Emden Fowler Type Equations: Continuous Versus Discrete 1

Intermediate Solutions for Emden Fowler Type Equations: Continuous Versus Discrete 1 Advance in Dynamical Syem and Applicaion. ISSN 973-5321 Volume 3 Number 1 (28), pp. 161 176 Reearch India Publicaion hp://www.ripublicaion.com/ada.hm Inermediae Soluion for Emden Fowler Type Equaion: Coninuou

More information

The multisubset sum problem for finite abelian groups

The multisubset sum problem for finite abelian groups Alo available a hp://amc-journal.eu ISSN 1855-3966 (prined edn.), ISSN 1855-3974 (elecronic edn.) ARS MATHEMATICA CONTEMPORANEA 8 (2015) 417 423 The muliube um problem for finie abelian group Amela Muraović-Ribić

More information

On certain subclasses of close-to-convex and quasi-convex functions with respect to k-symmetric points

On certain subclasses of close-to-convex and quasi-convex functions with respect to k-symmetric points J. Mah. Anal. Appl. 322 26) 97 6 www.elevier.com/locae/jmaa On cerain ubclae o cloe-o-convex and quai-convex uncion wih repec o -ymmeric poin Zhi-Gang Wang, Chun-Yi Gao, Shao-Mou Yuan College o Mahemaic

More information

Explaining Total Factor Productivity. Ulrich Kohli University of Geneva December 2015

Explaining Total Factor Productivity. Ulrich Kohli University of Geneva December 2015 Explaining Toal Facor Produciviy Ulrich Kohli Universiy of Geneva December 2015 Needed: A Theory of Toal Facor Produciviy Edward C. Presco (1998) 2 1. Inroducion Toal Facor Produciviy (TFP) has become

More information

Algorithm Design and Analysis

Algorithm Design and Analysis Algorihm Deign and Analyi LECTURE 0 Nework Flow Applicaion Biparie maching Edge-dijoin pah Adam Smih 0//0 A. Smih; baed on lide by E. Demaine, C. Leieron, S. Rakhodnikova, K. Wayne La ime: Ford-Fulkeron

More information

CHAPTER. Forced Equations and Systems { } ( ) ( ) 8.1 The Laplace Transform and Its Inverse. Transforms from the Definition.

CHAPTER. Forced Equations and Systems { } ( ) ( ) 8.1 The Laplace Transform and Its Inverse. Transforms from the Definition. CHAPTER 8 Forced Equaion and Syem 8 The aplace Tranform and I Invere Tranform from he Definiion 5 5 = b b {} 5 = 5e d = lim5 e = ( ) b {} = e d = lim e + e d b = (inegraion by par) = = = = b b ( ) ( )

More information

Essential Microeconomics : OPTIMAL CONTROL 1. Consider the following class of optimization problems

Essential Microeconomics : OPTIMAL CONTROL 1. Consider the following class of optimization problems Essenial Microeconomics -- 6.5: OPIMAL CONROL Consider he following class of opimizaion problems Max{ U( k, x) + U+ ( k+ ) k+ k F( k, x)}. { x, k+ } = In he language of conrol heory, he vecor k is he vecor

More information

Problem Set 5. Graduate Macro II, Spring 2017 The University of Notre Dame Professor Sims

Problem Set 5. Graduate Macro II, Spring 2017 The University of Notre Dame Professor Sims Problem Se 5 Graduae Macro II, Spring 2017 The Universiy of Nore Dame Professor Sims Insrucions: You may consul wih oher members of he class, bu please make sure o urn in your own work. Where applicable,

More information

On the Exponential Operator Functions on Time Scales

On the Exponential Operator Functions on Time Scales dvance in Dynamical Syem pplicaion ISSN 973-5321, Volume 7, Number 1, pp. 57 8 (212) hp://campu.m.edu/ada On he Exponenial Operaor Funcion on Time Scale laa E. Hamza Cairo Univeriy Deparmen of Mahemaic

More information

CONTROL SYSTEMS. Chapter 10 : State Space Response

CONTROL SYSTEMS. Chapter 10 : State Space Response CONTROL SYSTEMS Chaper : Sae Space Repone GATE Objecive & Numerical Type Soluion Queion 5 [GATE EE 99 IIT-Bombay : Mark] Conider a econd order yem whoe ae pace repreenaion i of he form A Bu. If () (),

More information

Do R&D subsidies necessarily stimulate economic growth?

Do R&D subsidies necessarily stimulate economic growth? MPR Munich Peronal RePEc rchive Do R&D ubidie necearily imulae economic growh? Ping-ho Chen and Hun Chu and Ching-Chong Lai Deparmen of Economic, Naional Cheng Chi Univeriy, Taiwan, Deparmen of Economic,

More information

Group C*-algebras A.K. Recall 1 that if G is a nonempty set, the linear space

Group C*-algebras A.K. Recall 1 that if G is a nonempty set, the linear space Group C*-algebra A.K. Recall 1 ha if G i a nonempy e, he linear pace c oo (G) = {f : G C : upp f finie } ha a Hamel bai coniing of he funcion {δ : G} where { 1, = δ () = 0, Thu every f c oo (G) i a finie

More information

Systems of nonlinear ODEs with a time singularity in the right-hand side

Systems of nonlinear ODEs with a time singularity in the right-hand side Syem of nonlinear ODE wih a ime ingulariy in he righ-hand ide Jana Burkoová a,, Irena Rachůnková a, Svaolav Saněk a, Ewa B. Weinmüller b, Sefan Wurm b a Deparmen of Mahemaical Analyi and Applicaion of

More information

Problem Set #1 - Answers

Problem Set #1 - Answers Fall Term 24 Page of 7. Use indifference curves and a curved ransformaion curve o illusrae a free rade equilibrium for a counry facing an exogenous inernaional price. Then show wha happens if ha exogenous

More information

Energy Equality and Uniqueness of Weak Solutions to MHD Equations in L (0,T; L n (Ω))

Energy Equality and Uniqueness of Weak Solutions to MHD Equations in L (0,T; L n (Ω)) Aca Mahemaica Sinica, Englih Serie May, 29, Vol. 25, No. 5, pp. 83 814 Publihed online: April 25, 29 DOI: 1.17/1114-9-7214-8 Hp://www.AcaMah.com Aca Mahemaica Sinica, Englih Serie The Ediorial Office of

More information

Note on Matuzsewska-Orlich indices and Zygmund inequalities

Note on Matuzsewska-Orlich indices and Zygmund inequalities ARMENIAN JOURNAL OF MATHEMATICS Volume 3, Number 1, 21, 22 31 Noe on Mauzewka-Orlic indice and Zygmund inequaliie N. G. Samko Univeridade do Algarve, Campu de Gambela, Faro,85 139, Porugal namko@gmail.com

More information

arxiv: v1 [cs.cg] 21 Mar 2013

arxiv: v1 [cs.cg] 21 Mar 2013 On he rech facor of he Thea-4 graph Lui Barba Proenji Boe Jean-Lou De Carufel André van Renen Sander Verdoncho arxiv:1303.5473v1 [c.cg] 21 Mar 2013 Abrac In hi paper we how ha he θ-graph wih 4 cone ha

More information

Optimal Devaluations

Optimal Devaluations USC FBE MACROECONOMICS AND INTERNATIONAL FINANCE WORKSHOP preened by Juan Pablo Nicolini FRIDAY, Feb. 24, 2006 3:30 pm 5:00 pm, Room: HOH-601K Opimal Devaluaion Conanino Hevia Univeriy of Chicago Juan

More information

Optimality Conditions for Unconstrained Problems

Optimality Conditions for Unconstrained Problems 62 CHAPTER 6 Opimaliy Condiions for Unconsrained Problems 1 Unconsrained Opimizaion 11 Exisence Consider he problem of minimizing he funcion f : R n R where f is coninuous on all of R n : P min f(x) x

More information

Index Number Concepts, Measures and Decompositions of Productivity Growth

Index Number Concepts, Measures and Decompositions of Productivity Growth C Journal of Produciviy Analyi, 9, 27 59, 2003 2003 Kluwer Academic Publiher. Manufacured in The Neherl. Inde Number Concep, Meaure Decompoiion of Produciviy Growh W. ERWIN DIEWERT diewer@econ.ubc.ca Deparmen

More information

Mathematische Annalen

Mathematische Annalen Mah. Ann. 39, 33 339 (997) Mahemaiche Annalen c Springer-Verlag 997 Inegraion by par in loop pace Elon P. Hu Deparmen of Mahemaic, Norhweern Univeriy, Evanon, IL 628, USA (e-mail: elon@@mah.nwu.edu) Received:

More information

Matrix Versions of Some Refinements of the Arithmetic-Geometric Mean Inequality

Matrix Versions of Some Refinements of the Arithmetic-Geometric Mean Inequality Marix Versions of Some Refinemens of he Arihmeic-Geomeric Mean Inequaliy Bao Qi Feng and Andrew Tonge Absrac. We esablish marix versions of refinemens due o Alzer ], Carwrigh and Field 4], and Mercer 5]

More information

EE202 Circuit Theory II

EE202 Circuit Theory II EE202 Circui Theory II 2017-2018, Spring Dr. Yılmaz KALKAN I. Inroducion & eview of Fir Order Circui (Chaper 7 of Nilon - 3 Hr. Inroducion, C and L Circui, Naural and Sep epone of Serie and Parallel L/C

More information

INFERENTIAL THEORY FOR FACTOR MODELS OF LARGE DIMENSIONS. By Jushan Bai 1

INFERENTIAL THEORY FOR FACTOR MODELS OF LARGE DIMENSIONS. By Jushan Bai 1 Economerica, Vol. 7, o. January, 2003, 35 7 IFEREIAL HEORY FOR FACOR MODELS OF LARGE DIMESIOS By Juhan Bai hi paper develop an inferenial heory for facor model of large dimenion. he principal componen

More information

Network Flow. Data Structures and Algorithms Andrei Bulatov

Network Flow. Data Structures and Algorithms Andrei Bulatov Nework Flow Daa Srucure and Algorihm Andrei Bulao Algorihm Nework Flow 24-2 Flow Nework Think of a graph a yem of pipe We ue hi yem o pump waer from he ource o ink Eery pipe/edge ha limied capaciy Flow

More information

5.2 GRAPHICAL VELOCITY ANALYSIS Polygon Method

5.2 GRAPHICAL VELOCITY ANALYSIS Polygon Method ME 352 GRHICL VELCITY NLYSIS 52 GRHICL VELCITY NLYSIS olygon Mehod Velociy analyi form he hear of kinemaic and dynamic of mechanical yem Velociy analyi i uually performed following a poiion analyi; ie,

More information

FULLY COUPLED FBSDE WITH BROWNIAN MOTION AND POISSON PROCESS IN STOPPING TIME DURATION

FULLY COUPLED FBSDE WITH BROWNIAN MOTION AND POISSON PROCESS IN STOPPING TIME DURATION J. Au. Mah. Soc. 74 (23), 249 266 FULLY COUPLED FBSDE WITH BROWNIAN MOTION AND POISSON PROCESS IN STOPPING TIME DURATION HEN WU (Received 7 Ocober 2; revied 18 January 22) Communicaed by V. Sefanov Abrac

More information

arxiv: v7 [q-fin.pm] 20 Mar 2019

arxiv: v7 [q-fin.pm] 20 Mar 2019 Porfolio choice, porfolio liquidaion, and porfolio raniion under drif uncerainy arxiv:161107843v7 [q-finpm] 20 Mar 2019 Alexi Bimuh, Olivier Guéan, Jiang Pu Abrac hi paper preen everal model addreing opimal

More information

A Logic of Orthogonality

A Logic of Orthogonality A Logic of Orhogonaliy J. Adámek, M. Héber and L. Soua Sepember 3, 2006 Thi paper wa inpired by he hard-o-believe fac ha Jiří Roický i geing ixy. We are happy o dedicae our paper o Jirka on he occaion

More information

6.302 Feedback Systems Recitation : Phase-locked Loops Prof. Joel L. Dawson

6.302 Feedback Systems Recitation : Phase-locked Loops Prof. Joel L. Dawson 6.32 Feedback Syem Phae-locked loop are a foundaional building block for analog circui deign, paricularly for communicaion circui. They provide a good example yem for hi cla becaue hey are an excellen

More information

Hamilton- J acobi Equation: Weak S olution We continue the study of the Hamilton-Jacobi equation:

Hamilton- J acobi Equation: Weak S olution We continue the study of the Hamilton-Jacobi equation: M ah 5 7 Fall 9 L ecure O c. 4, 9 ) Hamilon- J acobi Equaion: Weak S oluion We coninue he sudy of he Hamilon-Jacobi equaion: We have shown ha u + H D u) = R n, ) ; u = g R n { = }. ). In general we canno

More information

Buckling of a structure means failure due to excessive displacements (loss of structural stiffness), and/or

Buckling of a structure means failure due to excessive displacements (loss of structural stiffness), and/or Buckling Buckling of a rucure mean failure due o exceive diplacemen (lo of rucural iffne), and/or lo of abiliy of an equilibrium configuraion of he rucure The rule of humb i ha buckling i conidered a mode

More information

Network Flows UPCOPENCOURSEWARE number 34414

Network Flows UPCOPENCOURSEWARE number 34414 Nework Flow UPCOPENCOURSEWARE number Topic : F.-Javier Heredia Thi work i licened under he Creaive Common Aribuion- NonCommercial-NoDeriv. Unpored Licene. To view a copy of hi licene, vii hp://creaivecommon.org/licene/by-nc-nd/./

More information

arxiv: v1 [math.gm] 5 Jan 2019

arxiv: v1 [math.gm] 5 Jan 2019 A FUNCTION OBSTRUCTION TO THE EXISTENCE OF COMPLEX STRUCTURES arxiv:1901.05844v1 [mah.gm] 5 Jan 2019 JUN LING Abrac. We conruc a funcion for almo-complex Riemannian manifold. Non-vanihing of he funcion

More information

Optimal State-Feedback Control Under Sparsity and Delay Constraints

Optimal State-Feedback Control Under Sparsity and Delay Constraints Opimal Sae-Feedback Conrol Under Spariy and Delay Conrain Andrew Lamperki Lauren Leard 2 3 rd IFAC Workhop on Diribued Eimaion and Conrol in Neworked Syem NecSy pp. 24 29, 22 Abrac Thi paper preen he oluion

More information