Series of New Information Divergences, Properties and Corresponding Series of Metric Spaces

Size: px
Start display at page:

Download "Series of New Information Divergences, Properties and Corresponding Series of Metric Spaces"

Transcription

1 Srs of Nw Iforao Dvrgcs, Proprs ad Corrspodg Srs of Mrc Spacs K.C.Ja, Praphull Chhabra Profssor, Dpar of Mahacs, Malavya Naoal Isu of Tchology, Japur (Rajasha), Ida Ph.d Scholar, Dpar of Mahacs, Malavya Naoal Isu of Tchology, Japur (Rajasha), Ida Absrac: Dvrgc asurs ar bascally asurs of dsac bw wo probably dsrbuos or hs ar usful for coparg wo probably dsrbuos. Dpdg o h aur of h probl, h dffr dvrgcs ar suabl. So s always dsrabl o cra a w dvrgc asur. Thr ar svral gralzd fucoal dvrgcs, such as: Csszar dvrgc, Ry- lk dvrgc, Brga dvrgc, Burba- Rao dvrgc c. all. I hs papr, w oba a srs of dvrgcs corrspodg o a srs of covx fucos by usg gralzd Csszar dvrgc. Furhr, w df h proprs of covx fucos ad dvrgcs, copar h dvrgcs ad lasly roduc h srs of rc spacs. Idx Trs: Srs of rc spacs, srs of w covx ad oralzd fucos, srs of dvrgc asurs, proprs of covx fucos ad dvrgcs. Mahacs Subjc Classfcao: 94A7, 6D5. L I. INTRODUCTION P p, p, p3..., p : p 0, p, p 0 for so,, 3,..., probably dsrbuos. If w ak b h s of all copl f dscr, h w hav o suppos ha 0 0 f 0 0 f 0. 0 Csszar [], gv h gralzd f- dvrgc asur, whch s gv by: p C f P, Q q f q (.) Whr f: (0,) R (s of ral o.) s ral, couous ad covx fuco ad P p, p, p3..., p, Q q, q, q3..., q Γ, whr p ad q ar probably ass fucos. May kow dvrgcs ca b obad fro hs gralzd asur by suably dfg h covx fuco f. So of hos ar as follows: If w ak f log, w g p K P, Q p log q = Kullback- Lblr dvrgc asur []. (.) Copyrgh o IJIRSET 4

2 f, w g If w ak PQ, p q = Ch- Squar dvrgc asur [3]. (.3) q If w ak f log, w g p F P, Q p log p q = Rlav JS Dvrgc [4]. (.4) If w ak f log, w g p q p q GP, Q log = Rlav AG Dvrgc [5]. (.5) p Slarly, w g ay ohrs dvrgcs as wll by dfg suabl covx fuco. May rsarch paprs hav b sudd of I.J. Taja, P. Kuar, S.S. Dragor, K.C. Ja ad ohrs, who gav h da of dvrgc asurs, hr proprs, hr bouds ad rlaos wh ohr asurs. Ths all ar vry usful bcaus dvrgc asurs ar appld vary of dscpls (od cocluso). W roducd a w for of hs asurs,.. rc spacs. W foud ha squar roo of all dvrgcs of Csszar s class, s a rc spac, whch s vry usful fucoal aalyss. W ca xd hs da fucoal aalyss. II. SERIES OF CONVEX FUNCTIONS AND THEIR PROPERTIES I hs sco, w shall dvlop so srs of covx fucos, ad wll sudy hr proprs. For hs, L f: (0, ) R (s of ral o.) b a appg, dfd as: Ad f,,,3,4... (.) / 6 f (.) / 4 3 / f ,,, Fro (.), w g h followg covx fucos a =,, 3, 4 rspcvly. 4 6 f, f /, f 3/ 3... (.4) 5/ Now by usg (.4), w g h followg srs of covx fucos as wll. 4 4 f, f f (.5) / 3/ 3/ (.3) Copyrgh o IJIRSET 5

3 f,3 f f3 (.6) 3/ 5/ 5/ I hs way, w ca wr: 3 4 f, f f (.7) / / / Whr, =,, 3, 4 Sc, w kow ha h lar cobao of covx fucos s also a covx fuco. s a covx fuco as wll, whr a, a, a 3... ar posv cosas... a f a f a f So, w g aohr srs of covx fucos by usg (.4), dfd as follows: Cas-I: f w ak log b log b 3 a, a log b, a3, a4..., b, h w hav! 3! 3 logb logb g f log b f f3 f4...! 3! 3 log b log b g log... / b 3/ 5/ 7/! 3! 4 3 log log 6 b b log... / b 3! 3! Cas-II: f w ak Copyrgh o IJIRSET 6 b, b (.8) / log b log b 3 a 0, a, a3 log b, a4, a5..., b, h w hav! 3! 3 log b log b g log... 3/ b 5/ 7/ 9/! 3! log log 6 b b log... 3/ b 3! 3! 4 b, b (.9) 3/ I hs way, w ca wr: g b, b ad,,3,4... (.0) / Spcal Cas: If w ak b.788, h fro (.0), w oba h followg srs:

4 g xp,,,3,4... / / Proprs of fucos dfd by (.), (.7) ad (.), ar as follows: a. Sc f f g 0 f, f ad g ach.,, (.) ar oralzd fucos for b. Sc f 0 0,,,3,4... f ar covx fucos ad so f g ar as wll.,, c. Sc f 0 a 0, ad f 0 a f ar ooocally dcrasg d. ooocally crasg,,, for ach valu of ad f 0. 0, ad Fgur : Graph of fucos f. ` Fgur : Graph of fucos f, Copyrgh o IJIRSET 7

5 f. Fgur 3: Graph of fucos g Fgur, ad 3 shows ha f, f ad g rspcvly., hav a sppr slop for crasg valus of III. CORRESPONDING SERIES OF DIVERGENCES AND PROPERTIES: I hs sco, w shall oba srs of dvrgc asurs corrspodg o covx fucos dfd sco, ad wll sudy h proprs. Th followg hor s wll kow lraur []. Thor : If h fuco f s covx ad oralzd,.., boh o-gav ad covx h par of probably dsrbuo Now, pu (.) (.), w g h followg dvrgcs:.. p q q f / q f 0, h, p C P, Q P, Q,,,3,4... C P Q ad s adjo C, PQ,. Copyrgh o IJIRSET 8 f f Q P ar (3.) 4 6 p q p q p q / 3/ (3.a) 5/ P, Q, P, Q, P, Q pq q pq q pq q Now, pu (.7) (.), w g h followg dvrgcs: p q p p q pq q f / pq q (3.) C P, Q P, Q,,, PQ, p q p p q pq q (3.a) 3/ 4 pq q 4 p q p p q pq q PQ,... (3.b) 5/ 6 pq q Now, pu (.) (.), w g h followg dvrgcs:

6 p q p q / 3 p q q pq C f P, Q P, Q xp,,, PQ p q p q, xp / 3 pq q pq (3.3) (3.3a) 4 p q p q PQ 3/ 4 3 pq q pq, xp... (3.3b) Proprs of dvrgcs dfd by (3.), (3.) ad (3.3), ar as follows: a. I vw of hor, w ca say ha P Q P Q P Q probably dsrbuo PQ,.,,,,, 0 ad ar covx h par of b. c. Sc P, Q Q, P, P, Q Q, P, P, Q Q, P P, Q, P, Q, P, Q ar o- syrc dvrgc asurs. d. P, Q P, Q P, Q 0 f P Q or p q (Aas s u valu) a Fgur 4: Coparso of dvrgcs Fgur 4 shows h bhavor of P, Q, P, Q, K P, Q ad P, Q p a, a, q a, a, whr a 0, PQ, has sppr slop for crasg valus of ad has a spr slop ha K P, Q ad P, Q Kullback- Llbr dv. (.) Ch-squar dv (.3) Nw dv. a = (3.a) Nw dv. a = (3.a). W hav cosdrd. I s clar fro fgur 4 ha h w pararc dvrgc. Copyrgh o IJIRSET 9

7 IV. SERIES OF METRIC SPACES (DISTANCE MEASURES): Sc, PQ, =,, 3, Bu h su of PQ, s a o- syrc ad pararc dvrgc wh parar or srs of dvrgcs wh ad s adjo s syrc, so p q q p P, Q Q, P P, Q / / PQ p, = q p q,,,3,4... Or W ca s ha, PQ, p q q q p p 6 (4.) / pq s syrc pararc dvrgc asur. Now, wh h hlp of hor ad quao (4.), w ca say h followgs: P, Q 0 P, Q. P, Q 0 ff P Q or p q,,3..., whr P, Q. P, Q Q, P PQ, Now, f h ragl qualy s sasfd by PQ, hav o prov h followg hor, whch s sad as: Thor : L s syrc, for ach N x p, q : R R R,,,3... b dfd as, p q p q pq 6 /., h hs wll bco rc spacs ovr R. For hs, w x p, q,,,3..., (4.) I vw of (4.), w ca wr Th P, Q x p, q (4.3) x p, q x p, r x r, q ragl qualy p, q, r R. (4.4) Proof: To prov h rsul (4.4), frs l us cosdr,, X r x p r x r q (4.5) pq Th, Copyrgh o IJIRSET 30 d x p, r x r, q X pq r X pq r (4.6) dr x p, r x r, q Now fro (4.) (afr pug q x p, r r ), w g p r p r pr 6 / (4.7)

8 Ad afr dffrg (4.7) w.r. r, w g h followg: (4.8) 6 6 r p r p r p x p, r / / p r p r p Pu p r,.. R (4.8), w g r 6 x p, r k / 6 pr Fro (4.7), w ca wr x, Fro (4.7) ad (4.0), w hav h followg rlao (4.0) 6 /,, x p r r x r l (4.) Whr, w ar assug x, l Now, dffra (4.9) w.r., w g Copyrgh o IJIRSET 3 (4.9) (4.) ,,,3, (4.3) k s, 0, l (4.4) 4 k 4 / Now, l w df a fuco Fro (4.0) ad (4.3), w coclud ha l x, 0 ad k 0 0, ad N... k s ooocally dcrasg fuco ad k 0, so s wll b dcrasg as wll s 0 or h aur of s dpds o h aur of k. Thrfor, w coclud ha chags h sg a =, ad s Now, suppos s 0, 0, q q q p u R u R, so (4.6) ca b wr as: p r p r pq 0, wh (4.5) r X r s s u (4.6) Now, w hav wo cass o u, as follows: Cas I: f w ar akg u or q p, h (by cosdrg ha s s dcrasg fuco):

9 For s ad s u s s u For s 0 ad s u 0 s s u s s u 0 u. For s 0 ad su 0 u s su.. X pq r chags h sg a or r p, so Xpq r aas s u valu a r or r p. Cas II: hs cas for u or q p, ca b do a slar ar. Slarly, rpag h abov procdur by cosdrg q p p p q s su R ad u R u R, h w g ha X pq r chags h r q r q r r sg a or r q X r aas s u valu a or r q., so pq Thrfor, rgh had sd of (4.4) has s u valu a p q r, p, q, r R. Hc proof h rsul (4.4) or hor. I vw of hs proof, w coclud ha h w pararc syrc dvrgc asur PQ, asur. Or, w g h srs of dsac asurs, as follows: P Q P Q P Q P Q P Q P Q Copyrgh o IJIRSET 3 s a dsac,,,,,,,,,,,... (4.7) Or, w g h srs of rc spacs ovr R, as follows: R R R R R,,,,,,,,,... V. CONCLUDING REMARKS (4.8) Dvrgc asurs hav b appld a vary of dscpls such as ahropology, gcs, fac, coocs ad polcal scc, bology, aalyss of cogcy abls, approxao of probably dsrbuos, sgal procssg ad par rcogo. I hs papr, w roducd a w srs of covx fucos, w srs of dvrgc asurs ad w srs of rc spacs. Th bouds of pararc dvrgc asur PQ, dscussd x papr. ad rlao wh ohr sadard dvrgc asurs wll b REFERENCES [] Csszar, I., Iforao yp asurs of dffrcs of probably dsrbuo ad drc obsrvaos, Suda Mah. Hugarca, Vol., pp , 967. [] Kullback S. ad Lblr R.A., O Iforao ad Suffccy, A. Mah. Sas., Vol., pp , 95. [3] Parso K., O h Crro ha a gv sys of dvaos fro h probabl h cas of corrlad sys of varabls s such ha ca b rasoabl supposd o hav ars fro rado saplg, Phl. Mag., Vol. 50, pp. 57-7, 900. [4] Sbso R., Iforao radus, Z. Wahrs. Udvrw. Gb., Vol. 4, pp , 969. [5] Taja I.J., Nw dvlops gralzd forao asurs, Chapr : Advacs Iagg ad Elcro Physcs, Ed. P.W. Hawks, Vol. 9, pp , 995.

Available online Journal of Scientific and Engineering Research, 2014, 1(1): Research Article

Available online  Journal of Scientific and Engineering Research, 2014, 1(1): Research Article Avalable ole wwwjsaercom Joural o Scec ad Egeerg Research, 0, ():0-9 Research Arcle ISSN: 39-630 CODEN(USA): JSERBR NEW INFORMATION INEUALITIES ON DIFFERENCE OF GENERALIZED DIVERGENCES AND ITS APPLICATION

More information

Inference on Curved Poisson Distribution Using its Statistical Curvature

Inference on Curved Poisson Distribution Using its Statistical Curvature Rsarch Joural of Mahacal ad Sascal Sccs ISSN 3 647 ol. 5 6-6 Ju 3 Rs. J. Mahacal ad Sascal Sc. Ifrc o Curvd Posso Dsrbuo Usg s Sascal Curvaur Absrac Sal Babulal ad Sadhu Sachaya Dpar of sascs Th Uvrsy

More information

Dr. Junchao Xia Center of Biophysics and Computational Biology. Fall /21/2016 1/23

Dr. Junchao Xia Center of Biophysics and Computational Biology. Fall /21/2016 1/23 BIO53 Bosascs Lcur 04: Cral Lm Thorm ad Thr Dsrbuos Drvd from h Normal Dsrbuo Dr. Juchao a Cr of Bophyscs ad Compuaoal Bology Fall 06 906 3 Iroduco I hs lcur w wll alk abou ma cocps as lsd blow, pcd valu

More information

CHAPTER: 3 INVERSE EXPONENTIAL DISTRIBUTION: DIFFERENT METHOD OF ESTIMATIONS

CHAPTER: 3 INVERSE EXPONENTIAL DISTRIBUTION: DIFFERENT METHOD OF ESTIMATIONS CHAPTER: 3 INVERSE EXPONENTIAL DISTRIBUTION: DIFFERENT METHOD OF ESTIMATIONS 3. INTRODUCTION Th Ivrs Expoal dsrbuo was roducd by Kllr ad Kamah (98) ad has b sudd ad dscussd as a lfm modl. If a radom varabl

More information

Mathematical Statistics. Chapter VIII Sampling Distributions and the Central Limit Theorem

Mathematical Statistics. Chapter VIII Sampling Distributions and the Central Limit Theorem Mahmacal ascs 8 Chapr VIII amplg Dsrbos ad h Cral Lm Thorm Fcos of radom arabls ar sall of rs sascal applcao Cosdr a s of obsrabl radom arabls L For ampl sppos h arabls ar a radom sampl of s from a poplao

More information

A NOVEL DIFFERENCE EQUATION REPRESENTATION FOR AUTOREGRESSIVE TIME SERIES

A NOVEL DIFFERENCE EQUATION REPRESENTATION FOR AUTOREGRESSIVE TIME SERIES Joural of Thorcal ad Appld Iformao Tchology h Spmbr 4. Vol. 67 No. 5-4 JATIT & LLS. All rghs rsrvd. ISSN: 99-8645 www.a.org E-ISSN: 87-395 A NOVEL DIFFERENCE EQUATION REPRESENTATION FOR AUTOREGRESSIVE

More information

Control Systems (Lecture note #6)

Control Systems (Lecture note #6) 6.5 Corol Sysms (Lcur o #6 Las Tm: Lar algbra rw Lar algbrac quaos soluos Paramrzao of all soluos Smlary rasformao: compao form Egalus ad gcors dagoal form bg pcur: o brach of h cours Vcor spacs marcs

More information

Two-Dimensional Quantum Harmonic Oscillator

Two-Dimensional Quantum Harmonic Oscillator D Qa Haroc Oscllaor Two-Dsoal Qa Haroc Oscllaor 6 Qa Mchacs Prof. Y. F. Ch D Qa Haroc Oscllaor D Qa Haroc Oscllaor ch5 Schrödgr cosrcd h cohr sa of h D H.O. o dscrb a classcal arcl wh a wav ack whos cr

More information

MECE 3320 Measurements & Instrumentation. Static and Dynamic Characteristics of Signals

MECE 3320 Measurements & Instrumentation. Static and Dynamic Characteristics of Signals MECE 330 MECE 330 Masurms & Isrumao Sac ad Damc Characrscs of Sgals Dr. Isaac Chouapall Dparm of Mchacal Egrg Uvrs of Txas Pa Amrca MECE 330 Sgal Cocps A sgal s h phscal formao abou a masurd varabl bg

More information

Chap 2: Reliability and Availability Models

Chap 2: Reliability and Availability Models Chap : lably ad valably Modls lably = prob{s s fully fucog [,]} Suppos from [,] m prod, w masur ou of N compos, of whch N : # of compos oprag corrcly a m N f : # of compos whch hav fald a m rlably of h

More information

Reliability of time dependent stress-strength system for various distributions

Reliability of time dependent stress-strength system for various distributions IOS Joural of Mathmatcs (IOS-JM ISSN: 78-578. Volum 3, Issu 6 (Sp-Oct., PP -7 www.osrjourals.org lablty of tm dpdt strss-strgth systm for varous dstrbutos N.Swath, T.S.Uma Mahswar,, Dpartmt of Mathmatcs,

More information

Almost unbiased exponential estimator for the finite population mean

Almost unbiased exponential estimator for the finite population mean Almos ubasd poal smaor for f populao ma Rajs Sg, Pakaj aua, ad rmala Saa, Scool of Sascs, DAVV, Idor (M.P., Ida (rsgsa@aoo.com Flor Smaradac ar of Dparm of Mamacs, Uvrs of Mco, Gallup, USA (smarad@um.du

More information

A Simple Representation of the Weighted Non-Central Chi-Square Distribution

A Simple Representation of the Weighted Non-Central Chi-Square Distribution SSN: 9-875 raoa Joura o ovav Rarch Scc grg a Tchoogy (A S 97: 7 Cr rgaao) Vo u 9 Sbr A S Rrao o h Wgh No-Cra Ch-Squar Drbuo Dr ay A hry Dr Sahar A brah Dr Ya Y Aba Proor D o Mahaca Sac u o Saca Su a Rarch

More information

Algorithms to Solve Singularly Perturbed Volterra Integral Equations

Algorithms to Solve Singularly Perturbed Volterra Integral Equations Avalabl a hp://pvamudu/aam Appl Appl Mah ISSN: 9-9 Vol Issu Ju pp 9-8 Prvousl Vol Issu pp Applcaos ad Appld Mahmacs: A Iraoal Joural AAM Algorhms o Solv Sgularl Prurbd Volrra Igral Equaos Marwa Tasr Alqura

More information

Improved Exponential Estimator for Population Variance Using Two Auxiliary Variables

Improved Exponential Estimator for Population Variance Using Two Auxiliary Variables Improvd Epoal Emaor for Populao Varac Ug Two Aular Varabl Rajh gh Dparm of ac,baara Hdu Uvr(U.P., Ida (rgha@ahoo.com Pakaj Chauha ad rmala awa chool of ac, DAVV, Idor (M.P., Ida Flor maradach Dparm of

More information

8. Queueing systems. Contents. Simple teletraffic model. Pure queueing system

8. Queueing systems. Contents. Simple teletraffic model. Pure queueing system 8. Quug sysms Cos 8. Quug sysms Rfrshr: Sml lraffc modl Quug dscl M/M/ srvr wag lacs Alcao o ack lvl modllg of daa raffc M/M/ srvrs wag lacs lc8. S-38.45 Iroduco o Tlraffc Thory Srg 5 8. Quug sysms 8.

More information

Gauge Theories. Elementary Particle Physics Strong Interaction Fenomenology. Diego Bettoni Academic year

Gauge Theories. Elementary Particle Physics Strong Interaction Fenomenology. Diego Bettoni Academic year Gau Thors Elmary Parcl Physcs Sro Iraco Fomoloy o Bo cadmc yar - Gau Ivarac Gau Ivarac Whr do Laraas or Hamloas com from? How do w kow ha a cra raco should dscrb a acual hyscal sysm? Why s h lcromac raco

More information

ASYMPTOTIC BEHAVIOR OF FINITE-TIME RUIN PROBABILITY IN A BY-CLAIM RISK MODEL WITH CONSTANT INTEREST RATE

ASYMPTOTIC BEHAVIOR OF FINITE-TIME RUIN PROBABILITY IN A BY-CLAIM RISK MODEL WITH CONSTANT INTEREST RATE Joural of Mahmacs ad Sascs 3: 339-357 4 ISSN: 549-3644 4 Scc Publcaos do:.3844/mssp.4.339.357 Publshd Ol 3 4 hp://www.hscpub.com/mss.oc ASYMPTOTIC BEHAVIOR OF FINITE-TIME RUIN PROBABILITY IN A BY-CLAIM

More information

Lecture 12: Introduction to nonlinear optics II.

Lecture 12: Introduction to nonlinear optics II. Lcur : Iroduco o olar opcs II r Kužl ropagao of srog opc sgals propr olar ffcs Scod ordr ffcs! Thr-wav mxg has machg codo! Scod harmoc grao! Sum frqucy grao! aramrc grao Thrd ordr ffcs! Four-wav mxg! Opcal

More information

Major: All Engineering Majors. Authors: Autar Kaw, Luke Snyder

Major: All Engineering Majors. Authors: Autar Kaw, Luke Snyder Nolr Rgrsso Mjor: All Egrg Mjors Auhors: Aur Kw, Luk Sydr hp://urclhodsgusfdu Trsforg Nurcl Mhods Educo for STEM Udrgrdus 3/9/5 hp://urclhodsgusfdu Nolr Rgrsso hp://urclhodsgusfdu Nolr Rgrsso So populr

More information

Almost Unbiased Exponential Estimator for the Finite Population Mean

Almost Unbiased Exponential Estimator for the Finite Population Mean Rajs Sg, Pakaj aua, rmala Saa Scool of Sascs, DAVV, Idor (M.P., Ida Flor Smaradac Uvrs of Mco, USA Almos Ubasd Epoal Esmaor for F Populao Ma Publsd : Rajs Sg, Pakaj aua, rmala Saa, Flor Smaradac (Edors

More information

Improved Exponential Estimator for Population Variance Using Two Auxiliary Variables

Improved Exponential Estimator for Population Variance Using Two Auxiliary Variables Rajh gh Dparm of ac,baara Hdu Uvr(U.P.), Ida Pakaj Chauha, rmala awa chool of ac, DAVV, Idor (M.P.), Ida Flor maradach Dparm of Mahmac, Uvr of w Mco, Gallup, UA Improvd Epoal Emaor for Populao Varac Ug

More information

Reliability analysis of time - dependent stress - strength system when the number of cycles follows binomial distribution

Reliability analysis of time - dependent stress - strength system when the number of cycles follows binomial distribution raoal Joural of Sascs ad Ssms SSN 97-675 Volum, Numbr 7,. 575-58 sarch da Publcaos h://www.rublcao.com labl aalss of m - dd srss - srgh ssm wh h umbr of ccls follows bomal dsrbuo T.Sumah Umamahswar, N.Swah,

More information

Asymptotic Behavior of Finite-Time Ruin Probability in a By-Claim Risk Model with Constant Interest Rate

Asymptotic Behavior of Finite-Time Ruin Probability in a By-Claim Risk Model with Constant Interest Rate Th Uvrsy of Souhr Msssspp Th Aqula Dgal Commuy Sud ublcaos 8-5-4 Asympoc Bhavor of F-Tm Ru robably a By-Clam Rs Modl wh Cosa Irs Ra L Wag Uvrsy of Souhr Msssspp Follow hs ad addoal wors a: hps://aqula.usm.du/sud_pubs

More information

3.4 Properties of the Stress Tensor

3.4 Properties of the Stress Tensor cto.4.4 Proprts of th trss sor.4. trss rasformato Lt th compots of th Cauchy strss tsor a coordat systm wth bas vctors b. h compots a scod coordat systm wth bas vctors j,, ar gv by th tsor trasformato

More information

Periodic Solutions of Periodic Delay Lotka Volterra Equations and Systems

Periodic Solutions of Periodic Delay Lotka Volterra Equations and Systems Joural of ahacal Aalyss ad Applcaos 255, 2628 Ž 2 do:6aa27248, avalabl ol a hp:wwwdalbraryco o Prodc Soluos of Prodc Dlay LokaVolrra Equaos ad Syss Yogku L Dpar of ahacs, Yua Ursy, Kug, Yua 659, Popl s

More information

Consider a system of 2 simultaneous first order linear equations

Consider a system of 2 simultaneous first order linear equations Soluon of sysms of frs ordr lnar quaons onsdr a sysm of smulanous frs ordr lnar quaons a b c d I has h alrna mar-vcor rprsnaon a b c d Or, n shorhand A, f A s alrady known from con W know ha h abov sysm

More information

On the Class of New Better than Used. of Life Distributions

On the Class of New Better than Used. of Life Distributions Appld Mahacal Sccs, Vol. 6, 22, o. 37, 689-687 O h Class of Nw Br ha Usd of Lf Dsrbos Zohd M. Nofal Dpar of Sascs Mahacs ad Israc Facl of Corc Bha Uvrs, Egp dr_zofal@hoal.co Absrac So w rsls abo NBU3 class

More information

Existence of Nonoscillatory Solutions for a Class of N-order Neutral Differential Systems

Existence of Nonoscillatory Solutions for a Class of N-order Neutral Differential Systems Vo 3 No Mod Appd Scc Exsc of Nooscaoy Souos fo a Cass of N-od Nua Dffa Sysms Zhb Ch & Apg Zhag Dpam of Ifomao Egg Hua Uvsy of Tchoogy Hua 4 Cha E-ma: chzhbb@63com Th sach s facd by Hua Povc aua sccs fud

More information

Asymptotic Behavior of Solutions of Nonlinear Delay Differential Equations With Impulse

Asymptotic Behavior of Solutions of Nonlinear Delay Differential Equations With Impulse P a g e Vol Issue7Ver,oveber Global Joural of Scece Froer Research Asypoc Behavor of Soluos of olear Delay Dffereal Equaos Wh Ipulse Zhag xog GJSFR Classfcao - F FOR 3 Absrac Ths paper sudes he asypoc

More information

Complex Numbers. Prepared by: Prof. Sunil Department of Mathematics NIT Hamirpur (HP)

Complex Numbers. Prepared by: Prof. Sunil Department of Mathematics NIT Hamirpur (HP) th Topc Compl Nmbrs Hyprbolc fctos ad Ivrs hyprbolc fctos, Rlato btw hyprbolc ad crclar fctos, Formla of hyprbolc fctos, Ivrs hyprbolc fctos Prpard by: Prof Sl Dpartmt of Mathmatcs NIT Hamrpr (HP) Hyprbolc

More information

Improvement of the Reliability of a Series-Parallel System Subject to Modified Weibull Distribution with Fuzzy Parameters

Improvement of the Reliability of a Series-Parallel System Subject to Modified Weibull Distribution with Fuzzy Parameters Joural of Mahmacs ad Sascs Rsarch Arcls Improvm of h Rlably of a Srs-Paralll Sysm Subjc o Modfd Wbull Dsrbuo wh Fuzzy Paramrs Nama Salah Youssf Tmraz Mahmacs Dparm, Faculy of Scc, Taa Uvrsy, Taa, Egyp

More information

Akpan s Algorithm to Determine State Transition Matrix and Solution to Differential Equations with Mixed Initial and Boundary Conditions

Akpan s Algorithm to Determine State Transition Matrix and Solution to Differential Equations with Mixed Initial and Boundary Conditions IOSR Joural o Elcrcal ad Elcrocs Egrg IOSR-JEEE -ISSN: 78-676,p-ISSN: 3-333, Volu, Issu 5 Vr. III Sp - Oc 6, PP 9-96 www.osrourals.org kpa s lgorh o Dr Sa Traso Marx ad Soluo o Dral Euaos wh Mxd Ial ad

More information

Department of Mathematics and Statistics Indian Institute of Technology Kanpur MSO202A/MSO202 Assignment 3 Solutions Introduction To Complex Analysis

Department of Mathematics and Statistics Indian Institute of Technology Kanpur MSO202A/MSO202 Assignment 3 Solutions Introduction To Complex Analysis Dpartmt of Mathmatcs ad Statstcs Ida Isttut of Tchology Kapur MSOA/MSO Assgmt 3 Solutos Itroducto To omplx Aalyss Th problms markd (T) d a xplct dscusso th tutoral class. Othr problms ar for hacd practc..

More information

k of the incident wave) will be greater t is too small to satisfy the required kinematics boundary condition, (19)

k of the incident wave) will be greater t is too small to satisfy the required kinematics boundary condition, (19) TOTAL INTRNAL RFLTION Kmacs pops Sc h vcos a coplaa, l s cosd h cd pla cocds wh h X pla; hc 0. y y y osd h cas whch h lgh s cd fom h mdum of hgh dx of faco >. Fo cd agls ga ha h ccal agl s 1 ( /, h hooal

More information

The Method of Steepest Descent for Feedforward Artificial Neural Networks

The Method of Steepest Descent for Feedforward Artificial Neural Networks IOSR Joural o Mahac (IOSR-JM) -ISSN: 78-578, p-issn:39-765x. Volu, Iu Vr. II. (F. 4), PP 53-6.oroural.org Th Mhod o Sp Dc or Fdorard Arcal Nural Nor Muhaad Ha, Md. Jah Udd ad Md Adul Al 3 Aoca Proor, Dpar

More information

Let's revisit conditional probability, where the event M is expressed in terms of the random variable. P Ax x x = =

Let's revisit conditional probability, where the event M is expressed in terms of the random variable. P Ax x x = = L's rvs codol rol whr h v M s rssd rs o h rdo vrl. L { M } rrr v such h { M } Assu. { } { A M} { A { } } M < { } { } A u { } { } { A} { A} ( A) ( A) { A} A A { A } hs llows us o cosdr h cs wh M { } [ (

More information

COMPLEX NUMBERS AND ELEMENTARY FUNCTIONS OF COMPLEX VARIABLES

COMPLEX NUMBERS AND ELEMENTARY FUNCTIONS OF COMPLEX VARIABLES COMPLEX NUMBERS AND ELEMENTARY FUNCTIONS OF COMPLEX VARIABLES DEFINITION OF A COMPLEX NUMBER: A umbr of th form, whr = (, ad & ar ral umbrs s calld a compl umbr Th ral umbr, s calld ral part of whl s calld

More information

Fractal diffusion retrospective problems

Fractal diffusion retrospective problems Iraoa ora o App Mahac croc a Copr Avac Tchoo a Scc ISSN: 47-8847-6799 wwwaccor/iamc Ora Rarch Papr Fraca o rropcv prob O Yaro Rcv 6 h Ocobr 3 Accp 4 h aar 4 Abrac: I h arc w h rropcv vr prob Th rropcv

More information

Numerical Method: Finite difference scheme

Numerical Method: Finite difference scheme Numrcal Mthod: Ft dffrc schm Taylor s srs f(x 3 f(x f '(x f ''(x f '''(x...(1! 3! f(x 3 f(x f '(x f ''(x f '''(x...(! 3! whr > 0 from (1, f(x f(x f '(x R Droppg R, f(x f(x f '(x Forward dffrcg O ( x from

More information

Least squares and motion. Nuno Vasconcelos ECE Department, UCSD

Least squares and motion. Nuno Vasconcelos ECE Department, UCSD Las squars ad moo uo Vascoclos ECE Dparm UCSD Pla for oda oda w wll dscuss moo smao hs s rsg wo was moo s vr usful as a cu for rcogo sgmao comprsso c. s a gra ampl of las squars problm w wll also wrap

More information

Frequency Response. Response of an LTI System to Eigenfunction

Frequency Response. Response of an LTI System to Eigenfunction Frquncy Rsons Las m w Rvsd formal dfnons of lnary and m-nvaranc Found an gnfuncon for lnar m-nvaran sysms Found h frquncy rsons of a lnar sysm o gnfuncon nu Found h frquncy rsons for cascad, fdbac, dffrnc

More information

Summary: Solving a Homogeneous System of Two Linear First Order Equations in Two Unknowns

Summary: Solving a Homogeneous System of Two Linear First Order Equations in Two Unknowns Summary: Solvng a Homognous Sysm of Two Lnar Frs Ordr Equaons n Two Unknowns Gvn: A Frs fnd h wo gnvalus, r, and hr rspcv corrspondng gnvcors, k, of h coffcn mar A Dpndng on h gnvalus and gnvcors, h gnral

More information

Anouncements. Conjugate Gradients. Steepest Descent. Outline. Steepest Descent. Steepest Descent

Anouncements. Conjugate Gradients. Steepest Descent. Outline. Steepest Descent. Steepest Descent oucms Couga Gas Mchal Kazha (6.657) Ifomao abou h Sma (6.757) hav b pos ol: hp://www.cs.hu.u/~msha Tch Spcs: o M o Tusay afoo. o Two paps scuss ach w. o Vos fo w s caa paps u by Thusay vg. Oul Rvw of Sps

More information

Chapter 4. Continuous Time Markov Chains. Babita Goyal

Chapter 4. Continuous Time Markov Chains. Babita Goyal Chapr 4 Couous Tm Markov Chas Baba Goyal Ky words: Couous m sochasc procsss, Posso procss, brh procss, dah procss, gralzd brh-dah procss, succssv occurrcs, r-arrval m. Suggsd radgs:. Mdh, J. (996, Sochasc

More information

14. Poisson Processes

14. Poisson Processes 4. Posso Processes I Lecure 4 we roduced Posso arrvals as he lmg behavor of Bomal radom varables. Refer o Posso approxmao of Bomal radom varables. From he dscusso here see 4-6-4-8 Lecure 4 " arrvals occur

More information

1- I. M. ALGHROUZ: A New Approach To Fractional Derivatives, J. AOU, V. 10, (2007), pp

1- I. M. ALGHROUZ: A New Approach To Fractional Derivatives, J. AOU, V. 10, (2007), pp Jourl o Al-Qus Op Uvrsy or Rsrch Sus - No.4 - Ocobr 8 Rrcs: - I. M. ALGHROUZ: A Nw Approch To Frcol Drvvs, J. AOU, V., 7, pp. 4-47 - K.S. Mllr: Drvvs o or orr: Mh M., V 68, 995 pp. 83-9. 3- I. PODLUBNY:

More information

Total Prime Graph. Abstract: We introduce a new type of labeling known as Total Prime Labeling. Graphs which admit a Total Prime labeling are

Total Prime Graph. Abstract: We introduce a new type of labeling known as Total Prime Labeling. Graphs which admit a Total Prime labeling are Itratoal Joural Of Computatoal Egrg Rsarch (crol.com) Vol. Issu. 5 Total Prm Graph M.Rav (a) Ramasubramaa 1, R.Kala 1 Dpt.of Mathmatcs, Sr Shakth Isttut of Egrg & Tchology, Combator 641 06. Dpt. of Mathmatcs,

More information

The probability of Riemann's hypothesis being true is. equal to 1. Yuyang Zhu 1

The probability of Riemann's hypothesis being true is. equal to 1. Yuyang Zhu 1 Th robablty of Ra's hyothss bg tru s ual to Yuyag Zhu Abstract Lt P b th st of all r ubrs P b th -th ( ) lt of P ascdg ordr of sz b ostv tgrs ad s a rutato of wth Th followg rsults ar gv ths ar: () Th

More information

Phys Nov. 3, 2017 Today s Topics. Continue Chapter 2: Electromagnetic Theory, Photons, and Light Reading for Next Time

Phys Nov. 3, 2017 Today s Topics. Continue Chapter 2: Electromagnetic Theory, Photons, and Light Reading for Next Time Phys 31. No. 3, 17 Today s Topcs Cou Chap : lcomagc Thoy, Phoos, ad Lgh Radg fo Nx Tm 1 By Wdsday: Radg hs Wk Fsh Fowls Ch. (.3.11 Polazao Thoy, Jos Macs, Fsl uaos ad Bws s Agl Homwok hs Wk Chap Homwok

More information

Phys463.nb Conductivity. Another equivalent definition of the Fermi velocity is

Phys463.nb Conductivity. Another equivalent definition of the Fermi velocity is 39 Anohr quival dfiniion of h Fri vlociy is pf vf (6.4) If h rgy is a quadraic funcion of k H k L, hs wo dfiniions ar idical. If is NOT a quadraic funcion of k (which could happ as will b discussd in h

More information

Solution of Impulsive Differential Equations with Boundary Conditions in Terms of Integral Equations

Solution of Impulsive Differential Equations with Boundary Conditions in Terms of Integral Equations Joural of aheacs ad copuer Scece (4 39-38 Soluo of Ipulsve Dffereal Equaos wh Boudary Codos Ters of Iegral Equaos Arcle hsory: Receved Ocober 3 Acceped February 4 Avalable ole July 4 ohse Rabba Depare

More information

Comparisons of the Variance of Predictors with PPS sampling (update of c04ed26.doc) Ed Stanek

Comparisons of the Variance of Predictors with PPS sampling (update of c04ed26.doc) Ed Stanek Coparo o th Varac o Prdctor wth PPS aplg (updat o c04d6doc Ed Sta troducto W copar prdctor o a PSU a or total bad o PPS aplg Th tratgy to ollow that o Sta ad Sgr (JASA, 004 whr w xpr th prdctor a a lar

More information

Correlation in tree The (ferromagnetic) Ising model

Correlation in tree The (ferromagnetic) Ising model 5/3/00 :\ jh\slf\nots.oc\7 Chaptr 7 Blf propagato corrlato tr Corrlato tr Th (frromagtc) Isg mol Th Isg mol s a graphcal mol or par ws raom Markov fl cosstg of a urct graph wth varabls assocat wth th vrtcs.

More information

The Variance-Covariance Matrix

The Variance-Covariance Matrix Th Varanc-Covaranc Marx Our bggs a so-ar has bn ng a lnar uncon o a s o daa by mnmzng h las squars drncs rom h o h daa wh mnsarch. Whn analyzng non-lnar daa you hav o us a program l Malab as many yps o

More information

Homework: Introduction to Motion

Homework: Introduction to Motion Homwork: Inroducon o Moon Dsanc vs. Tm Graphs Nam Prod Drcons: Answr h foowng qusons n h spacs provdd. 1. Wha do you do o cra a horzona n on a dsancm graph? 2. How do you wak o cra a sragh n ha sops up?

More information

NHPP and S-Shaped Models for Testing the Software Failure Process

NHPP and S-Shaped Models for Testing the Software Failure Process Irol Jourl of Ls Trds Copug (E-ISSN: 45-5364 8 Volu, Issu, Dcr NHPP d S-Shpd Modls for Tsg h Sofwr Flur Procss Dr. Kr Arr Asss Profssor K.J. Soy Isu of Mg Suds & Rsrch Vdy Ngr Vdy Vhr Mu. Id. dshuh_3@yhoo.co/rrr@ssr.soy.du

More information

LECTURE 6 TRANSFORMATION OF RANDOM VARIABLES

LECTURE 6 TRANSFORMATION OF RANDOM VARIABLES LECTURE 6 TRANSFORMATION OF RANDOM VARIABLES TRANSFORMATION OF FUNCTION OF A RANDOM VARIABLE UNIVARIATE TRANSFORMATIONS TRANSFORMATION OF RANDOM VARIABLES If s a rv wth cdf F th Y=g s also a rv. If w wrt

More information

Ruin Probability in a Generalized Risk Process under Rates of Interest with Homogenous Markov Chain Claims

Ruin Probability in a Generalized Risk Process under Rates of Interest with Homogenous Markov Chain Claims ahmaca Ara, Vl 4, 4, 6, 6-63 Ru Prbably a Gralzd Rs Prcss udr Ras f Irs wh Hmgus arv Cha Clams Phug Duy Quag Dparm f ahmcs Frg Trad Uvrsy, 9- Chua Lag, Ha, V Nam Nguy Va Vu Tra Quc Tua Uvrsy Nguy Hg Nha

More information

1973 AP Calculus BC: Section I

1973 AP Calculus BC: Section I 97 AP Calculus BC: Scio I 9 Mius No Calculaor No: I his amiaio, l dos h aural logarihm of (ha is, logarihm o h bas ).. If f ( ) =, h f ( ) = ( ). ( ) + d = 7 6. If f( ) = +, h h s of valus for which f

More information

Simulation of coupled nonlinear electromagnetic heating with the Green element method

Simulation of coupled nonlinear electromagnetic heating with the Green element method Advacd Copuaoal Mhods Ha rasfr IX 77 Sulao of coupld olar lcroagc hag wh h Gr l hod A. E. agbu School of Cvl ad Evroal Egrg, Uvrs of h Wwarsrad, Johasburg, Souh Afrca Absrac h olar coupld dffral uaos ha

More information

Supplementary Figure 1. Experiment and simulation with finite qudit. anharmonicity. (a), Experimental data taken after a 60 ns three-tone pulse.

Supplementary Figure 1. Experiment and simulation with finite qudit. anharmonicity. (a), Experimental data taken after a 60 ns three-tone pulse. Supplmnar Fgur. Eprmn and smulaon wh fn qud anharmonc. a, Eprmnal daa akn afr a 6 ns hr-on puls. b, Smulaon usng h amlonan. Supplmnar Fgur. Phagoran dnamcs n h m doman. a, Eprmnal daa. Th hr-on puls s

More information

, R we have. x x. ) 1 x. R and is a positive bounded. det. International Journal of Basic & Applied Sciences IJBAS-IJENS Vol:10 No:06 11

, R we have. x x. ) 1 x. R and is a positive bounded. det. International Journal of Basic & Applied Sciences IJBAS-IJENS Vol:10 No:06 11 raioal Joral of asic & ppli Scics JS-JENS Vol: No:6 So Dirichl ors a Pso Diffrial Opraors wih Coiioall Epoial Cov cio aa. M. Kail Dpar of Mahaics; acl of Scic; Ki laziz Uivrsi Jah Sai raia Eail: fkail@ka..sa

More information

American International Journal of Research in Science, Technology, Engineering & Mathematics

American International Journal of Research in Science, Technology, Engineering & Mathematics Ara raoal oral of ar S oloy r & aa Avalabl ol a //wwwar SSN Pr 38-349 SSN Ol 38-358 SSN D-O 38-369 AS a rfr r-rvw llary a o a joral bl by raoal Aoao of Sf ovao a ar AS SA A Aoao fy S r a Al ar oy rao ra

More information

Unbalanced Panel Data Models

Unbalanced Panel Data Models Ubalacd Pal Data odls Chaptr 9 from Baltag: Ecoomtrc Aalyss of Pal Data 5 by Adrás alascs 4448 troducto balacd or complt pals: a pal data st whr data/obsrvatos ar avalabl for all crosssctoal uts th tr

More information

Aotomorphic Functions And Fermat s Last Theorem(4)

Aotomorphic Functions And Fermat s Last Theorem(4) otomorphc Fuctos d Frmat s Last Thorm(4) Chu-Xua Jag P. O. Box 94 Bg 00854 P. R. Cha agchuxua@sohu.com bsract 67 Frmat wrot: It s mpossbl to sparat a cub to two cubs or a bquadrat to two bquadrats or gral

More information

MINIMUM ENERGY CONTROL OF FRACTIONAL POSITIVE ELECTRICAL CIRCUITS. Tadeusz Kaczorek

MINIMUM ENERGY CONTROL OF FRACTIONAL POSITIVE ELECTRICAL CIRCUITS. Tadeusz Kaczorek MINIMUM ENEGY CONO OF FACIONA POSIIVE EECICA CICUIS ausz Kaczor alyso Uvrsy o chology Faculy o Elcrcal Egrg jsa 45D 5-5 alyso -al: aczor@sppwupl ASAC Mu rgy corol probl or h racoal posv lcrcal crcus s

More information

Multi-fluid magnetohydrodynamics in the solar atmosphere

Multi-fluid magnetohydrodynamics in the solar atmosphere Mul-flud magohydrodyams h solar amoshr Tmuraz Zaqarashvl თეიმურაზ ზაქარაშვილი Sa Rsarh Isu of Ausra Aadmy of Ss Graz Ausra ISSI-orksho Parally ozd lasmas asrohyss 6 Jauary- Fbruary 04 ISSI-orksho Parally

More information

The Linear Regression Of Weighted Segments

The Linear Regression Of Weighted Segments The Lear Regresso Of Weghed Segmes George Dael Maeescu Absrac. We proposed a regresso model where he depede varable s made o up of pos bu segmes. Ths suao correspods o he markes hroughou he da are observed

More information

POSITIVITY AND REACHABILITY OF FRACTIONAL ELECTRICAL CIRCUITS

POSITIVITY AND REACHABILITY OF FRACTIONAL ELECTRICAL CIRCUITS asz Kaczo Posy a achably o Facoal Elccal cs POSIIVIY ND EHIIY OF FION EEI IUIS asz KZOEK* *Facly o Elccal Egg ałyso Usy o chology l Wsa D - ałyso aczo@sppwpl bsac: oos o h posy o acoal la lccal ccs copos

More information

Quantum Harmonic Oscillator

Quantum Harmonic Oscillator Quu roc Oscllor Quu roc Oscllor 6 Quu Mccs Prof. Y. F. C Quu roc Oscllor Quu roc Oscllor D S..O.:lr rsorg forc F k, k s forc cos & prbolc pol. V k A prcl oscllg roc pol roc pol s u po of sbly sys 6 Quu

More information

Overview. Introduction Building Classifiers (2) Introduction Building Classifiers. Introduction. Introduction to Pattern Recognition and Data Mining

Overview. Introduction Building Classifiers (2) Introduction Building Classifiers. Introduction. Introduction to Pattern Recognition and Data Mining Ovrv Iroduco o ar Rcogo ad Daa Mg Lcur 4: Lar Dcra Fuco Irucor: Dr. Gova Dpar of Copur Egrg aa Clara Uvry Iroduco Approach o uldg clafr Lar dcra fuco: dfo ad urfac Lar paral ca rcpro crra Ohr hod Lar Dcra

More information

On Estimation of Unknown Parameters of Exponential- Logarithmic Distribution by Censored Data

On Estimation of Unknown Parameters of Exponential- Logarithmic Distribution by Censored Data saqartvlos mcrbata rovul akadms moamb, t 9, #2, 2015 BULLETIN OF THE GEORGIAN NATIONAL ACADEMY OF SCIENCES, vol 9, o 2, 2015 Mathmatcs O Estmato of Ukow Paramtrs of Epotal- Logarthmc Dstrbuto by Csord

More information

Chapter 8. Second-Harmonic Generation and Parametric Oscillation

Chapter 8. Second-Harmonic Generation and Parametric Oscillation Chapr 8 Sco-Haroc Grao a ararc Oscao 8 Irouco Sco-Haroc grao : ararc Oscao : Rfrc : RW Boy Noar Opcs Chapr Th oar Opca Suscpby Noar Opcs ab Hayag Uv Th Noar Opca Suscpby Gra for of uc poarao : whr : ar

More information

Chain DOUBLE PITCH TYPE RS TYPE RS POLY-STEEL TYPE

Chain DOUBLE PITCH TYPE RS TYPE RS POLY-STEEL TYPE d Fr Flw OULE IC YE YE OLY-EEL YE Oubard wh d s (d ) s usd fr fr flw vya. Usually w srads ar usd h qupm. d s basd sadard rllr ha wh sd rllrs salld xdd ps. hr ar hr yps f bas ha: (1) ubl ph rllr ha wh sadard

More information

Nuclear Chemistry -- ANSWERS

Nuclear Chemistry -- ANSWERS Hoor Chstry Mr. Motro 5-6 Probl St Nuclar Chstry -- ANSWERS Clarly wrt aswrs o sparat shts. Show all work ad uts.. Wrt all th uclar quatos or th radoactv dcay srs o Urau-38 all th way to Lad-6. Th dcay

More information

A note on Turán number Tk ( 1, kn, )

A note on Turán number Tk ( 1, kn, ) A oe o Turá umber T (,, ) L A-Pg Beg 00085, P.R. Cha apl000@sa.com Absrac: Turá umber s oe of prmary opcs he combaorcs of fe ses, hs paper, we wll prese a ew upper boud for Turá umber T (,, ). . Iroduco

More information

Advanced Queueing Theory. M/G/1 Queueing Systems

Advanced Queueing Theory. M/G/1 Queueing Systems Advand Quung Thory Ths slds ar rad by Dr. Yh Huang of Gorg Mason Unvrsy. Sudns rgsrd n Dr. Huang's ourss a GMU an ma a sngl mahn-radabl opy and prn a sngl opy of ah sld for hr own rfrn, so long as ah sld

More information

rather basic, using double extensions of analytic and harmonic functions.

rather basic, using double extensions of analytic and harmonic functions. REFUTATIO OF THE RIEMA HYPOTHESIS By Hr Brocch Absrac W rov ha h Ra hyohss for h Raς fco s fas W rov v ha h ra ar of o rva zros of ς ads ad for accao os Th roof s rahr basc, sg dob sos of aayc ad haroc

More information

Linear Perturbation Bounds of the Continuous-Time LMI-Based H Quadratic Stability Problem for Descriptor Systems

Linear Perturbation Bounds of the Continuous-Time LMI-Based H Quadratic Stability Problem for Descriptor Systems UGRN DE OF ENE ERNE ND NFORON EHNOOGE Volu No 4 ofa a ubao ouds of h ouous- -asd H uadac ably obl fo Dscpo yss dy ochv chcal Uvsy of ofa Faculy of uoacs Dpa of yss ad ool 756 ofa Eal ayochv@u-sofa.bg bsac

More information

Some Properties of Exponentiated Weibull-Generalized Exponential Distribution

Some Properties of Exponentiated Weibull-Generalized Exponential Distribution J. Sa. App. Pro. 4 No. 3 475-486 (25) 475 Joura of Sass Appaos & Probaby A Iraoa Joura hp://d.do.or/.2785/jsap/435 So Proprs of poad Wbu-Grad poa Dsrbuo Surya Jab * ad T. R Ja. P.G Dpar of Sass Uvrsy of

More information

S.Y. B.Sc. (IT) : Sem. III. Applied Mathematics. Q.1 Attempt the following (any THREE) [15]

S.Y. B.Sc. (IT) : Sem. III. Applied Mathematics. Q.1 Attempt the following (any THREE) [15] S.Y. B.Sc. (IT) : Sm. III Applid Mahmaics Tim : ½ Hrs.] Prlim Qusion Papr Soluion [Marks : 75 Q. Amp h following (an THREE) 3 6 Q.(a) Rduc h mari o normal form and find is rank whr A 3 3 5 3 3 3 6 Ans.:

More information

A L A BA M A L A W R E V IE W

A L A BA M A L A W R E V IE W A L A BA M A L A W R E V IE W Volume 52 Fall 2000 Number 1 B E F O R E D I S A B I L I T Y C I V I L R I G HT S : C I V I L W A R P E N S I O N S A N D TH E P O L I T I C S O F D I S A B I L I T Y I N

More information

Boyce/DiPrima 9 th ed, Ch 7.6: Complex Eigenvalues

Boyce/DiPrima 9 th ed, Ch 7.6: Complex Eigenvalues BocDPm 9 h d Ch 7.6: Compl Egvlus Elm Dffl Equos d Boud Vlu Poblms 9 h do b Wllm E. Boc d Rchd C. DPm 9 b Joh Wl & Sos Ic. W cosd g homogous ssm of fs od l quos wh cos l coffcs d hus h ssm c b w s ' A

More information

Extension Formulas of Lauricella s Functions by Applications of Dixon s Summation Theorem

Extension Formulas of Lauricella s Functions by Applications of Dixon s Summation Theorem Avll t http:pvu.u Appl. Appl. Mth. ISSN: 9-9466 Vol. 0 Issu Dr 05 pp. 007-08 Appltos Appl Mthts: A Itrtol Jourl AAM Etso oruls of Lurll s utos Appltos of Do s Suto Thor Ah Al Atsh Dprtt of Mthts A Uvrst

More information

The rise of neural networks. Deep networks. Why many layers? Why many layers? Why many layers? 24/03/2017

The rise of neural networks. Deep networks. Why many layers? Why many layers? Why many layers? 24/03/2017 Th rs of ural ors I h md-s, hr has b a rsurgc of ural ors, mal du o rasos: hgh compuaoal por bcam avalabl a lo cos va gral-purpos graphcs procssg us (GPGPUs). maor plars l Googl, crosof, ad Facboo, dd

More information

Mellin Transform Method for the Valuation of the American Power Put Option with Non-Dividend and Dividend Yields

Mellin Transform Method for the Valuation of the American Power Put Option with Non-Dividend and Dividend Yields Joural of Mahmacal Fac, 5, 5, 49-7 Publshd Ol Augus 5 ScRs. h://www.scr.org/joural/jmf h://dx.do.org/.436/jmf.5.533 Mll Trasform Mhod for h Valuao of h Amrca Powr Pu Oo wh No-Dvdd ad Dvdd Ylds Suday Emmaul

More information

Independent Domination in Line Graphs

Independent Domination in Line Graphs Itratoal Joural of Sctfc & Egrg Rsarch Volum 3 Issu 6 Ju-1 1 ISSN 9-5518 Iddt Domato L Grahs M H Muddbhal ad D Basavarajaa Abstract - For ay grah G th l grah L G H s th trscto grah Thus th vrtcs of LG

More information

Fourier Series: main points

Fourier Series: main points BIOEN 3 Lcur 6 Fourir rasforms Novmbr 9, Fourir Sris: mai pois Ifii sum of sis, cosis, or boh + a a cos( + b si( All frqucis ar igr mulipls of a fudamal frqucy, o F.S. ca rprs ay priodic fucio ha w ca

More information

Continous system: differential equations

Continous system: differential equations /6/008 Coious sysm: diffrial quaios Drmiisic modls drivaivs isad of (+)-( r( compar ( + ) R( + r ( (0) ( R ( 0 ) ( Dcid wha hav a ffc o h sysm Drmi whhr h paramrs ar posiiv or gaiv, i.. giv growh or rducio

More information

Key words: Fractional difference equation, oscillatory solutions,

Key words: Fractional difference equation, oscillatory solutions, OSCILLATION PROPERTIES OF SOLUTIONS OF FRACTIONAL DIFFERENCE EQUATIONS Musafa BAYRAM * ad Ayd SECER * Deparme of Compuer Egeerg, Isabul Gelsm Uversy Deparme of Mahemacal Egeerg, Yldz Techcal Uversy * Correspodg

More information

STRUCTURAL FAULT DETECTION OF BRIDGES BASED ON LINEAR SYSTEM PARAMETER AND MTS METHOD

STRUCTURAL FAULT DETECTION OF BRIDGES BASED ON LINEAR SYSTEM PARAMETER AND MTS METHOD Joural of JSCE, Vol., 3-43, 03 STRUCTURAL FAULT DETECTION OF BRIDGES BASED ON LINEAR SYSTEM PARAMETER AND MTS METHOD Chul-Woo KIM, Ro ISEMOTO, Kuomo SUGIURA 3 ad Msuo KAWATANI 4 Mmbr of JSCE, Profssor,

More information

On the Existence and uniqueness for solution of system Fractional Differential Equations

On the Existence and uniqueness for solution of system Fractional Differential Equations OSR Jourl o Mhms OSR-JM SSN: 78-578. Volum 4 ssu 3 Nov. - D. PP -5 www.osrjourls.org O h Es d uquss or soluo o ssm rol Drl Equos Mh Ad Al-Wh Dprm o Appld S Uvrs o holog Bghdd- rq Asr: hs ppr w d horm o

More information

Comparison of the Bayesian and Maximum Likelihood Estimation for Weibull Distribution

Comparison of the Bayesian and Maximum Likelihood Estimation for Weibull Distribution Joural of Mahemacs ad Sascs 6 (2): 1-14, 21 ISSN 1549-3644 21 Scece Publcaos Comarso of he Bayesa ad Maxmum Lkelhood Esmao for Webull Dsrbuo Al Omar Mohammed Ahmed, Hadeel Salm Al-Kuub ad Noor Akma Ibrahm

More information

Chapter 5 Transient Analysis

Chapter 5 Transient Analysis hpr 5 rs Alyss Jsug Jg ompl rspos rs rspos y-s rspos m os rs orr co orr Dffrl Equo. rs Alyss h ffrc of lyss of crcus wh rgy sorg lms (ucors or cpcors) & m-ryg sgls wh rss crcus s h h quos rsulg from r

More information

Wave Phenomena Physics 15c

Wave Phenomena Physics 15c Wv hnon hyscs 5c cur 4 Coupl Oscllors! H& con 4. Wh W D s T " u forc oscllon " olv h quon of oon wh frcon n foun h sy-s soluon " Oscllon bcos lr nr h rsonnc frquncy " hs chns fro 0 π/ π s h frquncy ncrss

More information

CHAPTER 7. X and 2 = X

CHAPTER 7. X and 2 = X CHATR 7 Sco 7-7-. d r usd smors o. Th vrcs r d ; comr h S vrc hs cs / / S S Θ Θ Sc oh smors r usd mo o h vrcs would coclud h s h r smor wh h smllr vrc. 7-. [ ] Θ 7 7 7 7 7 7 [ ] Θ ] [ 7 6 Boh d r usd sms

More information

Some Probability Inequalities for Quadratic Forms of Negatively Dependent Subgaussian Random Variables

Some Probability Inequalities for Quadratic Forms of Negatively Dependent Subgaussian Random Variables Joural of Sceces Islamc epublc of Ira 6(: 63-67 (005 Uvers of ehra ISSN 06-04 hp://scecesuacr Some Probabl Iequales for Quadrac Forms of Negavel Depede Subgaussa adom Varables M Am A ozorga ad H Zare 3

More information

FINITE GROUPS OCCURRING AS GROUPS OF INTEGER MATRICES

FINITE GROUPS OCCURRING AS GROUPS OF INTEGER MATRICES FINITE ROUPS OCCURRIN S ROUPS OF INTEER MTRICES - Paa Bra IISER Pu I h roc w udy rou of arc I arcular w ry ad dr h obl ordr of arc of f ordr h rou L h rou of arc wh dra ro cra rul du o Mow rard h oro of

More information

( A) ( B) ( C) ( D) ( E)

( A) ( B) ( C) ( D) ( E) d Smsr Fial Exam Worksh x 5x.( NC)If f ( ) d + 7, h 4 f ( ) d is 9x + x 5 6 ( B) ( C) 0 7 ( E) divrg +. (NC) Th ifii sris ak has h parial sum S ( ) for. k Wha is h sum of h sris a? ( B) 0 ( C) ( E) divrgs

More information