Semi-blind Channel Estimation for MIMO-OFDM Systems Based on Received Signal Reconstruction Weijia Cui 1, You Zhou 2, a 3, b,*

Size: px
Start display at page:

Download "Semi-blind Channel Estimation for MIMO-OFDM Systems Based on Received Signal Reconstruction Weijia Cui 1, You Zhou 2, a 3, b,*"

Transcription

1 Ieaial Cfeece Aumai, Mechaical Cl ad Cmuaial Egieeig (AMCCE 15) Semi-blid Chael Eimai f MIMO-OFDM Syem Baed Receied Sigal Recuci Weijia Cui 1, Yu Zhu, a 3, b,*, Sg Che 1 Ifmai Sciece ad echlgy Iiue, Zhegzhu, 451, Chia Ifmai Sciece ad echlgy Iiue, Zhegzhu, 451, Chia 3 Ifmai Sciece ad echlgy Iiue, Zhegzhu, 451, Chia a 39734@qq.cm, b wielemac@16.cm,*cedig auh Keywd: MIMO-OFDM; Blid chael eimai; Subace; Sigal ecuci; QR decmii; Gam-Schmid hgalizai; Abac. Blid chael eimai f MIMO-OFDM yem wa dicued, ad a ubace baed blid chael eimai algihm by e-cucig he eceied igal ad i imlified e wee ed. he algihm chaged he chael maix f he afe fuci i a blck eliz high maix exliig OFDM cyclic efix, ad he chael eimai chaaceiic equai wa baied wih he hgaliy bewee he igal ubace ad he ie ubace f he ecuced igal. I de elimiae he ifluece f iual caie, he igula alue decmii f he equiale ami igal wa imed. he imlified algihm exlied a QR decmii ad Gam-Schmid hgalizai ce aimig a educig he cmlexiy f baiig he ie ubace. Simulai eul illuae he efmace f he ed algihm ia umeical exeime cmaed wih he he e, ad i ieiie eeimae f he ue chael de. Iduci Chael eimai he e-cdii f chee deeci i MIMO-OFDM yem. adiial mehd i ie il i he amiig daa [1]. I de ime fequecy ecum efficiecy, blid chael eimai ha becme h ic i ece yea []~[7]. Amg he blid algihm, ubace baed algihm eceie gea aei becaue f i bee accuacy efmace [8]. A OFDM ubace algihm exliig CP i ed i [9]. Alhugh wih a gd accuacy efmace, i i alicable yem wih exiece f iual ub-caie. adiial OFDM ubace baed algihm i exaded MIMO-OFDM yem i [1] wih lw cegece ae. he ae ay aei fa emi-blid chael eimai i MIMO-OFDM yem wih exiece f iual ub-caie. Lea fm [9], a emi-blid algihm baed eceied igal ecuci ad i imlified e ae ed. Sme ai ae illuaed a fllw: (), () ad () ae aii, cjugae ad cjugae ae eeciely. I i ui maix. E[] i aiical aeage. x [1: k] i he f k eleme i x. X [:, k] ad X [ k,:] ae he k -h clum ad k -h w f X. X [: i jm, : ] i he ub-maix f X fm w i j ad clum m. a( X ) ad ak( X ) ae he clum ace f maix X ad i ak eeciely. ec( X) i ecizai f maix X. i l m. i Kecke duc. Defie w ex( j / ). C (, σ ) i cmlex Gauia diibui. MIMO-OFDM Syem Mdel Aume ha he umbe f amiig ad eceiig aea i MIMO-OFDM yem ae ad eeciely wih. hee ae ub-caie wih D daa ub-caie ad ( D) iual ub-caie. he idice f daa ub-caie ae deed by k k + D 1. CP ad OFDM legh ae P ad Q= + P 15. he auh - Publihed by Alai Pe 189

2 eeciely. Daa be amied i x ( k, ) = [ x1( k, ), x( k, ),..., x ( k, )], whee xi ( k, ) i he daa he k -h ub-caie f aea i i -h OFDM ymbl. Accdigly, he al -h daa be mdulaed ca be deed by x = [ x( k, ), x( k, + 1),..., x ( k, + D) ]. i he mdulaed daa afe iei f CP. Defie ( k, ) = [ ( k, ), ( k, ),..., ( k, )], whee ( k, ) he k -h daa afe IFF aea i. We hae 1 i = [ (, P),..., (, ), (,), (,1),..., (, ) ]. Defie: 1 ki ( k+ 1) i ( k+ D ( ) [,,..., 1) i F i = w w w ] F= [ F( P),..., F( ), F(), F(1),..., F( ) ] Γ = F I S we hae = Γx. Chael mdel bewee amiig ad eceiig aea i deed by FIR file, ad L i maximum chael de. he l -h chael cefficie i deed by h11() l h1() l h1 () l h1() l h() l h () l h() l = () h1() l h () () l h l We ake a he eceied igal. Defie ( k, ) = [ 1( k, ), ( k, ),..., ( k, )], whee j ( k, ) i he k -h eceied daa eceiig aea j i -h ymbl. Accdigly, we. Aume ha L P hae = [ (,),..., (,1),..., (, + P) ], he chael be eimaed i deed by h= [ h(), h(1),..., h ( P)]. Whei > L, h() i =. Defie h() h( P) h(1) =, 1 = h( P) h( P) h( P) h() (3) we hae = + 1 +, whee ~ C (, σ I ) i he cmlex whie Guaia ie. Q (1) Subace Algihm baed Receied Sigal Recuci A. Algihm Deduci Deide, ad i 3 ub-ec: = [ 1,, 3], = [ 1,, 3], = [ 1,, 3]. F ad, he dimei f he 1 ad he 3 d ub-ec i P 1, while f, he dimei i P 1. Defie 1 ( ) = [ ( ), ( )3, 1], ( ) = [ 1,, 3], ad ecuc he eceied igal accdig ( ) = 1( ) ( ). Exliig CP chaaceiic, we hae ( ) = ( ) + ( ), whee, ( ) ad ( ) ae deed a fllw: h() ( ) 1 ( ) 1 = h( P) h(), ( ) =, ( ) = ( )3 (4) ( )3 1 3 h( P) 1891

3 Aaely, i a Q ak h () =. R = E[ ( ) ( ) ], R = E[()()] ad R = E[ ( ) ( ) ] ae caiace maixe f ( ), ( ) ad ( ) eeciely. Aume ha he ie ad amiig igal ae muual ideede wih each he, we hae R = R + R (5) full clum ak eliz high maix wih ( ) Defie F1 = [ F(), F(1),..., F( ) ] F = [ F( P),..., F( ), F(), F(1),..., F( P) ] We hae ( ) = ( F I ) x ( F I ) x 1 Aume ha all he amiig daa i muual ideede, we hae Rx = E[ xx ] = I D, he R = E[()()] = ( FF + FF ) I D SVD R 1 1 R = AΛ A (9) Whee Λ i he diagal maix cmed by -ze eigealue f R, A i he cedig eigeec. he algihm i alicable yem wih exiece f iual ub-caie wih hi decmii. A i a fixed maix wih he ame, P ad, which mea ly a mall amu f addiial calculai i equied. Mee, IP I P R = E[ ( ) ( ) ] = σ I( P) (1) IP I P I ca be ee ha ( ) i cl ie. Aaely, R i a iie defiie maix which ca be whieed hugh Chleky decmii R = σ ww, whee w i a lwe iagula maix wih iie diagal eleme. Al, w i a fixed maix wih he ame, P ad, which mea eal-ime calculai f he maix i equied. I ca be baied ha R = w Rw = ( w A) Λ σ( w A) + σ IQ M (11) Λ i a full ak maix, ad ak( w A) = ak( A). Wih cai ak( h ()) =, eigealue decme equai (11) R = Λ + (1) Whee he dimei f eeciely. ad w A = Λ, ad ae igal ad ie ace f ae D D R (7) (8) (6), Q D ad Q ( Q D) eeciely. Al (13) he abe equai i he chaaceiic equai f he chael eimai. Defie = [ ()[:, i], (1)[:, i],..., ( P)[:, i] ],1 i = [ h, h,..., h ] ad h = ec( ). he hi h h h, 1 diffeece bewee h ad he acual chael i a ieible ca maix which ca be baied hugh iei f mall amu f il [1]. B. Algihm Decii R i eimaed by Q D C( ) = Vˆ [:, k] A k = 1 b ˆ = ( ( ) ( ) )/ = R, ad i al a eimaed maix. Defie c fuci wih Vˆ = w b ˆ ˆ. Accdig equai(13), eimaed Ĥ i he alue which 189

4 ca miimize C( ). Equally Diide V ˆ [:, k] i Q egme ad deed ( ) ( ) ( ) by ˆ ˆ k [:, ] [( ),( ˆ k ),...,( ˆ k V k = V V V ) ]. Defie he fllwig maix: κ k 1 Q ˆ ( k) ˆ ( k) ˆ ( k) V V1 V Q P ˆ ( k) ˆ ( k) ˆ ( k) V1 V VQ P = ˆ ( k) ˆ ( k) ˆ ( k) VP VP+ 1 VQ 1 Q D ( k ) ( ) k k = 1 Θ = κ I AA κ I w, C( ) ca be ewie a C( ) = h Θh.I de aid all ze lui, add a limiai f h i = 1. Defie h h h ˆ = ag mi h Θh, whee he eimaed h i he liea, he eimai ca be accmlihed by ( ) hi = 1 cmbiai f eigeec cedig he miimum eigealue. C. Simlified Algihm Calculae he ie ace i a ieaie mae. If Φ ( ) i a ca maix, we hae [13] ( ) = Φ( ) Q( 1), ( ) = Q( ) R ( ) (15) Fially Q( ) will cege he eigeec cedig he mai eigealue f Φ ( ) R i accmlihed a fllw: R( ) = αr( 1) + (1 α) w ( ) ( ) w Whee α i he fgeig fac. Subiue Φ ( ) i equai (15) wih R ( ) aximai[14] ( w ) ( ) α ( 1) + (1 α) w ( ) Q ( ) ( ) (14). he udaig f (16), we hae he fllwig (17) Ad Q ( ) will fially cege. he cmlexiy i abu O( QD ) [14]. ca be calculaed by Schmid hgalizai exliig he hgaliy bewee ad. Make ( 1) hgal Q ( ) ia Schimid hgalizai, ad he ceed ec will be eaed a he ie ace f he cue ieai. Fially ( ) will cege. he cmlexiy i abuo( Q( Q D)). Simulai ad Aalyi le hewie ed, we che =, =, = 16, D = 16, P = 3, L = 3, b = 1, l hij ()~ l C (, σ l ) wih σ /1 l = ae, l =,..., L, a i we malizai fac[11]. Simulai 1: Pefmace f he ed algihm ad algihm i [1] i cmaed i Fig.1 chig J = i [1]. he accuacy ad cegece efmace ae hw i (a) ad (b) eeciely. he ed algihm ha bee efmace bh way. 1893

5 1 RMSE db 3dB 1-3 4dB b (a) Accuacy efmace (b) Cegece efmace Fig.1 Pefmace camai Simulai : he accuacy efmace wih diffee iual ub-caie i hw i Fig.. We ca ee ha he ed algihm ca wk well wih diffee iual ub-caie. Simulai 3: he accuacy efmace f he ed algihm wih diffee eceiig aea i hw i Fig.3. he efmace ime gadually wih he iceae f eceiig aea. he ea i ha he umbe f he ie ace bai iceae wih he iceaig f eceiig aea, which mea a bee ai-iefeece abiliy f he ed algihm D= D=1 D= = =3 =4 RMSE 1 - RMSE SR(dB) SR(dB) Fig. Pefmace wih diffee Fig.3 Pefmace wih diffee iual ubcaie eceiig aea Simulai 4: he accuacy efmace wih diffee CP i hw i Fig. 4. We ake he CP legh a chael de, he umbe f chael cefficie be eimaed iceae wih he iceaig f CP. Alhugh he efmace degade lighly wih lg CP, he algihm ill wk well, which mea i i bu chael de eeimai. Simulai 5: he accuacy efmace f imlified algihm i hw i Fig. 5, whee SR=4 db, J =. Alhugh he imlified algihm accuacy deceae lighly, i ill ha bee efmace cmaed wih algihm i [1]. he cmlexiy f algihm i [1], SVD ad he imlified e ae O (343), O (5487) ad O (584) eeciely. 1894

6 1 1-1 P=3 P=4 P=8 RMSE SR(dB) Fig.4 Pefmace wih diffee CP Fig.5 Pefmace f imlified algihm Cclui Exliig he chaaceiic f CP, he ed algihm ecuc he eceied igal ad chage he chael maix i eliz high maix. Alhugh addiial ie whieig ad SVD decmii ae equied, hey ae all yem aamee elaed, which mea eal-ime calculai i eeded. he imlified algihm ca effeciely educe he cmlexiy hugh a ieaie mehd. Simulai hw ha he ed algihm ha bee accuacy ad cegece efmace, ad i eiie chael de. Refeece [1] Lae, M.D.. Pefmace bud f MIMO-OFDM chael eimai [J]. IEEE aaci Sigal Pceig, 9, 57(5): [] Miyajima,., Zhi Dig. Subcaie ullig algihm f chael heig i ulik OFDMA yem [J]. IEEE aaci Sigal Pceig, 1, 6(5): [3] Feg Wa, Wei-Pig Zhu, Swamy, M..S.. Semiblid ae chael eimai f MIMO- OFDM yem [J]. IEEE aaci Vehicula echlgy, 11, 6(6): [4] Al-affui,.Y., Dahma, A.A., Shail, M.S., e al.. Lw-cmlexiy blid equalizai f OFDM yem wih geeal cellai [J]. IEEE aaci Sigal Pceig, 1, 6(1): [5] Al-Bayai, A.K.S.. Subace-baed blid chael eimai i ealy auaed dwlik mulicaie cde diii mulile acce yem [J]. IE Cmmuicai, 1, 6(4): [6] Zha Zhi-ji, Wag Bai-chua, Shag Ju-a, e al.. A eimai algihm f MIMO-OFDM chael baed RS [J]. Jual f Elecic & Ifmai echlgy, 33(): [7] Feg Wa, Wei-Pig Zhu, M.. S. Swamy. Semiblid ae chael eimai f MIMO- OFDM yem [J]. IEEE aaci Vehicula echlgy, 11, 6(6): [8] Zhag Lig, Zhag Xia-da. A eiew f blid chael eimai algihm f MIMO- OFDM yem [J]. ACA Elecic Siica, 7, 35(6A): 1-6. [9] uag Xue-ju. Blid chael eimai algihm i OFDM yem [D]. Shaghai Jiag ieiy,

7 [1] Chagyg Shi, Rbe W. eah, J., e al.. Blid chael eimai f MIMO-OFDM yem [J]. IEEE aaci Vehicula echlgy, 7, 56(): [11] Wei-Chieh uag, Chu-ie Pa, Chih-Peg Li, e al.. Subace-baed emi-blid chael eimai i ulik OFDMA yem [J]. IEEE aaci Badcaig, 1, 56(1): [1] Y. Zeg,. S. g. A emi-blid chael eimai mehd f muliue muliaea OFDM yem [J]. IEEE aaci Sigal Pceig, 4, 5(5): [13] G.. Glub, C. F. Va La. Maix Cmuai, Secd edii [M]. Balime, MD: Jh ki ieiy Pe, [14] Pee Sbach. Lw-Rak adaie file [J]. IEEE aaci Sigal Pceig, 1996, 44(1):

Neutron Slowing Down Distances and Times in Hydrogenous Materials. Erin Boyd May 10, 2005

Neutron Slowing Down Distances and Times in Hydrogenous Materials. Erin Boyd May 10, 2005 Neu Slwig Dw Disaces ad Times i Hydgeus Maeials i Byd May 0 005 Oulie Backgud / Lecue Maeial Neu Slwig Dw quai Flux behavi i hydgeus medium Femi eame f calculaig slwig dw disaces ad imes. Bief deivai f

More information

Lecture 4. Electrons and Holes in Semiconductors

Lecture 4. Electrons and Holes in Semiconductors ecue 4 lec ad Hle i Semicduc I hi lecue yu will lea: eeai-ecmbiai i emicduc i me deail The baic e f euai gveig he behavi f elec ad hle i emicduc Shcley uai Quai-eualiy i cducive maeial C 35 Sig 2005 Faha

More information

Lecture 4. Electrons and Holes in Semiconductors

Lecture 4. Electrons and Holes in Semiconductors Lecue 4 lec ad Hle i Semicduc I hi lecue yu will lea: Geeai-ecmbiai i emicduc i me deail The baic e f euai gveig he behavi f elec ad hle i emicduc Shckley uai Quai-eualiy i cducive maeial C 35 Sig 2005

More information

dm dt = 1 V The number of moles in any volume is M = CV, where C = concentration in M/L V = liters. dcv v

dm dt = 1 V The number of moles in any volume is M = CV, where C = concentration in M/L V = liters. dcv v Mg: Pcess Aalyss: Reac ae s defed as whee eac ae elcy lue M les ( ccea) e. dm he ube f les ay lue s M, whee ccea M/L les. he he eac ae beces f a hgeeus eac, ( ) d Usually s csa aqueus eeal pcesses eac,

More information

Chapter 1 Electromagnetic Field Theory

Chapter 1 Electromagnetic Field Theory hpe ecgeic Fie The - ecic Fie ecic Dipe Gu w f : S iegece he ε = 6 fee pce. F q fie pi q q 9 F/ i he. ue e f icee chge: qk k k k ue uce ρ Sufce uce ρ S ie uce ρ qq qq g. Shw h u w F whee. q Pf F q S q

More information

Scratch Ticket Game Closing Analysis SUMMARY REPORT

Scratch Ticket Game Closing Analysis SUMMARY REPORT TEXAS LTTERY ISSI Scach Tice Game lsig Aalysis SUARY REPRT Scach Tice Ifmai mpleed 1/ 3/ 216 Game# 16891 fimed Pacs 4, 613 Game ame Lucy Bucsl Acive Pacs 3, 29 Quaiy Pied 11, 21, 1 aehuse Pacs 1, 222 Pice

More information

β A Constant-G m Biasing

β A Constant-G m Biasing p 2002 EE 532 Anal IC Des II Pae 73 Cnsan-G Bas ecall ha us a PTAT cuen efeence (see p f p. 66 he nes) bas a bpla anss pes cnsan anscnucance e epeaue (an als epenen f supply lae an pcess). Hw h we achee

More information

Algebra 2A. Algebra 2A- Unit 5

Algebra 2A. Algebra 2A- Unit 5 Algeba 2A Algeba 2A- Ui 5 ALGEBRA 2A Less: 5.1 Name: Dae: Plymial fis O b j e i! I a evalae plymial fis! I a ideify geeal shapes f gaphs f plymial fis Plymial Fi: ly e vaiable (x) V a b l a y a :, ze a

More information

Modelling and Solution for Assignment Problem

Modelling and Solution for Assignment Problem Mdellig ad Slui f Assigme Pblem Liyig Yag Mighg Nie Zhewei Wu ad Yiyg Nie Absac I his pape he mixed-iege liea pgammig (MILP) f mii assigme is fmed ad a slui called Opeais Maix is peseed ad cmpaed wih he

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

The Non-Truncated Bulk Arrival Queue M x /M/1 with Reneging, Balking, State-Dependent and an Additional Server for Longer Queues

The Non-Truncated Bulk Arrival Queue M x /M/1 with Reneging, Balking, State-Dependent and an Additional Server for Longer Queues Alied Maheaical Sciece Vol. 8 o. 5 747-75 The No-Tucaed Bul Aival Queue M x /M/ wih Reei Bali Sae-Deede ad a Addiioal Seve fo Loe Queue A. A. EL Shebiy aculy of Sciece Meofia Uiveiy Ey elhebiy@yahoo.co

More information

CHATTERJEA CONTRACTION MAPPING THEOREM IN CONE HEPTAGONAL METRIC SPACE

CHATTERJEA CONTRACTION MAPPING THEOREM IN CONE HEPTAGONAL METRIC SPACE Fameal Joal of Mahemaic a Mahemaical Sciece Vol. 7 Ie 07 Page 5- Thi pape i aailable olie a hp://.fi.com/ Pblihe olie Jaa 0 07 CHATTERJEA CONTRACTION MAPPING THEOREM IN CONE HEPTAGONAL METRIC SPACE Caolo

More information

Lecture 14. Time Harmonic Fields

Lecture 14. Time Harmonic Fields Lcu 4 Tim amic Filds I his lcu u will la: Cmpl mahmaics f im-hamic filds Mawll s quais f im-hamic filds Cmpl Pig vc C 303 Fall 007 Faha aa Cll Uivsi Tim-amic Filds ad -filds f a pla wav a (fm las lcu:

More information

Research & Reviews: Journal of Statistics and Mathematical Sciences

Research & Reviews: Journal of Statistics and Mathematical Sciences Research & Reviews: Jural f Saisics ad Mahemaical Scieces iuus Depedece f he Slui f A Schasic Differeial Equai Wih Nlcal diis El-Sayed AMA, Abd-El-Rahma RO, El-Gedy M Faculy f Sciece, Alexadria Uiversiy,

More information

Copyright Birkin Cars (Pty) Ltd

Copyright Birkin Cars (Pty) Ltd E GROU TWO STEERING AND EDAS - R.H.D Aemble clue : K360 043AD STEERING OUMN I u: - : K360 04A STEERING RAK :3 K360 045A EDA OX K360043AD STEERING O UMN Tl eque f embl f u: - mm Alle Ke 3mm Se 6mm Alle

More information

ADAPTIVE INVERSE CONTROL OF PIEZOELECTRIC ACTUATORS WITH HYSTERESIS OPERATORS

ADAPTIVE INVERSE CONTROL OF PIEZOELECTRIC ACTUATORS WITH HYSTERESIS OPERATORS ADAPIVE INVERSE CONROL OF PIEZOELECRIC ACUAORS WIH HYSERESIS OPERAORS K. Kuhe, H. Jaha Labay f Pe Aumai (LPA) Uiveiy f Saalad, Im Sadwald, Geb. 13 D-66123 Saabüke, Gemay fax: +49-681-302-2678 ad e-mail:

More information

M-ary Detection Problem. Lecture Notes 2: Detection Theory. Example 1: Additve White Gaussian Noise

M-ary Detection Problem. Lecture Notes 2: Detection Theory. Example 1: Additve White Gaussian Noise Hi ue Hi ue -ay Deecio Pole Coide he ole of decidig which of hyohei i ue aed o oevig a ado vaiale (veco). he efoace cieia we coide i he aveage eo oailiy. ha i he oailiy of decidig ayhig ece hyohei H whe

More information

ABSOLUTE INDEXED SUMMABILITY FACTOR OF AN INFINITE SERIES USING QUASI-F-POWER INCREASING SEQUENCES

ABSOLUTE INDEXED SUMMABILITY FACTOR OF AN INFINITE SERIES USING QUASI-F-POWER INCREASING SEQUENCES Available olie a h://sciog Egieeig Maheaics Lees 2 (23) No 56-66 ISSN 249-9337 ABSLUE INDEED SUMMABILIY FACR F AN INFINIE SERIES USING QUASI-F-WER INCREASING SEQUENCES SKAIKRAY * RKJAI 2 UKMISRA 3 NCSAH

More information

MODERN CONTROL SYSTEMS

MODERN CONTROL SYSTEMS MODERN CONTROL SYSTEMS Lecure 9, Sae Space Repreeaio Emam Fahy Deparme of Elecrical ad Corol Egieerig email: emfmz@aa.edu hp://www.aa.edu/cv.php?dip_ui=346&er=6855 Trafer Fucio Limiaio TF = O/P I/P ZIC

More information

t = s D Overview of Tests Two-Sample t-test: Independent Samples Independent Samples t-test Difference between Means in a Two-sample Experiment

t = s D Overview of Tests Two-Sample t-test: Independent Samples Independent Samples t-test Difference between Means in a Two-sample Experiment Overview of Te Two-Sample -Te: Idepede Sample Chaper 4 z-te Oe Sample -Te Relaed Sample -Te Idepede Sample -Te Compare oe ample o a populaio Compare wo ample Differece bewee Mea i a Two-ample Experime

More information

Secure Chaotic Spread Spectrum Systems

Secure Chaotic Spread Spectrum Systems Seue Chaoi Sea Seum Sysems Ji Yu WSEAB ECE Deame Seves siue of Tehology Hoboke J 73 Oulie ouio Chaoi SS sigals Seuiy/ efomae ee eeives Biay oelaig eeio Mismah oblem aile-fileig base aoah Dual-aea aoah

More information

EF 151 Exam #2 - Spring, 2014 Page 1 of 6

EF 151 Exam #2 - Spring, 2014 Page 1 of 6 EF 5 Exam # - Spring, 04 Page of 6 Name: Secion: Inrucion: Pu your name and ecion on he exam. Do no open he e unil you are old o do o. Wrie your final anwer in he box proided If you finih wih le han 5

More information

P a g e 5 1 of R e p o r t P B 4 / 0 9

P a g e 5 1 of R e p o r t P B 4 / 0 9 P a g e 5 1 of R e p o r t P B 4 / 0 9 J A R T a l s o c o n c l u d e d t h a t a l t h o u g h t h e i n t e n t o f N e l s o n s r e h a b i l i t a t i o n p l a n i s t o e n h a n c e c o n n e

More information

Graphing Square Roots - Class Work Graph the following equations by hand. State the domain and range of each using interval notation.

Graphing Square Roots - Class Work Graph the following equations by hand. State the domain and range of each using interval notation. Graphing quare Roots - lass Work Graph the following equations by hand. tate the domain and range of each using interval notation. 1. y = x + 2 2. f x = x 1. y = x + 4. g x = 2 x 1 5. y = x + 2 + 4 6.

More information

A PATRA CONFERINŢĂ A HIDROENERGETICIENILOR DIN ROMÂNIA,

A PATRA CONFERINŢĂ A HIDROENERGETICIENILOR DIN ROMÂNIA, A PATRA ONFERINŢĂ A HIDROENERGETIIENILOR DIN ROMÂNIA, Do Pael MODELLING OF SEDIMENTATION PROESS IN LONGITUDINAL HORIZONTAL TANK MODELAREA PROESELOR DE SEPARARE A FAZELOR ÎN DEANTOARE LONGITUDINALE Da ROBESU,

More information

Review - Week 10. There are two types of errors one can make when performing significance tests:

Review - Week 10. There are two types of errors one can make when performing significance tests: Review - Week Read: Chaper -3 Review: There are wo ype of error oe ca make whe performig igificace e: Type I error The ull hypohei i rue, bu we miakely rejec i (Fale poiive) Type II error The ull hypohei

More information

Pattern Distributions of Legendre Sequences

Pattern Distributions of Legendre Sequences IEEE TRASACTIOS O IFORMATIO THEORY, VOL., O., JULY 1998 1693 [9] J. E. Savage, Some imle elf-ychoizig digial daa camble, Bell Sy. Tech. J., vol., o.,. 9 87, Feb. 1967. [10] A. Paouli, Pobabiliy, Radom

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

Fresnel Dragging Explained

Fresnel Dragging Explained Fresel Draggig Explaied 07/05/008 Decla Traill Decla@espace.e.au The Fresel Draggig Coefficie required o explai he resul of he Fizeau experime ca be easily explaied by usig he priciples of Eergy Field

More information

Low-complexity Algorithms for MIMO Multiplexing Systems

Low-complexity Algorithms for MIMO Multiplexing Systems Low-complexiy Algoihms fo MIMO Muliplexing Sysems Ouline Inoducion QRD-M M algoihm Algoihm I: : o educe he numbe of suviving pahs. Algoihm II: : o educe he numbe of candidaes fo each ansmied signal. :

More information

Molecular Evolution and Phylogeny. Based on: Durbin et al Chapter 8

Molecular Evolution and Phylogeny. Based on: Durbin et al Chapter 8 Molecula Evoluion and hylogeny Baed on: Dubin e al Chape 8. hylogeneic Tee umpion banch inenal node leaf Topology T : bifucaing Leave - N Inenal node N+ N- Lengh { i } fo each banch hylogeneic ee Topology

More information

Thabet Abdeljawad 1. Çankaya Üniversitesi Fen-Edebiyat Fakültesi, Journal of Arts and Sciences Say : 9 / May s 2008

Thabet Abdeljawad 1. Çankaya Üniversitesi Fen-Edebiyat Fakültesi, Journal of Arts and Sciences Say : 9 / May s 2008 Çaaya Üiversiesi Fe-Edebiya Faülesi, Jural Ars ad Scieces Say : 9 / May s 008 A Ne e Cai Rule ime Scales abe Abdeljawad Absrac I is w, i eeral, a e cai rule eeral ime scale derivaives des beave well as

More information

Consider a Binary antipodal system which produces data of δ (t)

Consider a Binary antipodal system which produces data of δ (t) Modulaion Polem PSK: (inay Phae-hi keying) Conide a inay anipodal yem whih podue daa o δ ( o + δ ( o inay and epeively. Thi daa i paed o pule haping ile and he oupu o he pule haping ile i muliplied y o(

More information

Stability. Outline Stability Sab Stability of Digital Systems. Stability for Continuous-time Systems. system is its stability:

Stability. Outline Stability Sab Stability of Digital Systems. Stability for Continuous-time Systems. system is its stability: Oulie Sabiliy Sab Sabiliy of Digial Syem Ieral Sabiliy Exeral Sabiliy Example Roo Locu v ime Repoe Fir Orer Seco Orer Sabiliy e Jury e Rouh Crierio Example Sabiliy A very impora propery of a yamic yem

More information

f;g,7k ;! / C+!< 8R+^1 ;0$ Z\ \ K S;4 i!;g + 5 ;* \ C! 1+M, /A+1+> 0 /A+>! 8 J 4! 9,7 )F C!.4 ;* )F /0 u+\ 30< #4 8 J C!

f;g,7k ;! / C+!< 8R+^1 ;0$ Z\ \ K S;4 i!;g + 5 ;* \ C! 1+M, /A+1+> 0 /A+>! 8 J 4! 9,7 )F C!.4 ;* )F /0 u+\ 30< #4 8 J C! 393/09/0 393//07 :,F! ::!n> b]( a.q 5 O +D5 S ١ ; ;* :'!3Qi C+0;$ < "P 4 ; M V! M V! ; a 4 / ;0$ f;g,7k ;! / C+!< 8R+^ ;0$ Z\ \ K S;4 "* < 8c0 5 *

More information

Parts Manual. EPIC II Critical Care Bed REF 2031

Parts Manual. EPIC II Critical Care Bed REF 2031 EPIC II Critical Care Bed REF 2031 Parts Manual For parts or technical assistance call: USA: 1-800-327-0770 2013/05 B.0 2031-109-006 REV B www.stryker.com Table of Contents English Product Labels... 4

More information

Chapter 11 HYDROFORMING

Chapter 11 HYDROFORMING Mechaics f Shee Meal Fmig, Secd Edii, by Zdzislaw Maciiak, Jh Duca ad Jack Hu Publishe: Buewh-Heiema 00-06-5, ISBN: 075065000 Chae HYDROFORMING.. INTRODUCTION. I hydfmig, fluid essue fmig, shee is fmed

More information

Fun and Fascinating Bible Reference for Kids Ages 8 to 12. starts on page 3! starts on page 163!

Fun and Fascinating Bible Reference for Kids Ages 8 to 12. starts on page 3! starts on page 163! F a Faa R K 8 12 a a 3! a a 163! 2013 a P, I. ISN 978-1-62416-216-9. N a a a a a, a,. C a a a a P, a 500 a a aa a. W, : F G: K Fa a Q &, a P, I. U. L aa a a a Fa a Q & a. C a 2 (M) Ta H P M (K) Wa P a

More information

Ruled surfaces are one of the most important topics of differential geometry. The

Ruled surfaces are one of the most important topics of differential geometry. The CONSTANT ANGLE RULED SURFACES IN EUCLIDEAN SPACES Yuuf YAYLI Ere ZIPLAR Deparme of Mahemaic Faculy of Sciece Uieriy of Aara Tadoğa Aara Turey yayli@cieceaaraedur Deparme of Mahemaic Faculy of Sciece Uieriy

More information

α = normal pressure angle α = apparent pressure angle Tooth thickness measurement and pitch inspection

α = normal pressure angle α = apparent pressure angle Tooth thickness measurement and pitch inspection Tth thickess measuemet ad pitch ispecti Tth thickess measuemet Whe yu eshape a shavig cutte yu educe the chdal thickess f the teeth f a value icluded etwee 0.06 ad 0.10 mm. I fucti f this value yu have

More information

, University. 1and. y T. since. g g

, University. 1and. y T. since. g g UADPhilEc, Dp. f Ecmics,, Uivsi f Ahss Lcu: Nichlas J. hcaakis Dcmb 2 Ec Advacd Maccmic h I: Mdul : Gwh G ad Ccls Basic wh mah im vaiabls. 2. Disc vaiabls Scks (a a pi f im,.. labu fc) ad Flws ( i a pid

More information

Optical flow equation

Optical flow equation Opical Flow Sall oio: ( ad ae le ha piel) H() I(++) Be foce o poible ppoe we ake he Talo eie epaio of I: (Sei) Opical flow eqaio Cobiig hee wo eqaio I he lii a ad go o eo hi becoe eac (Sei) Opical flow

More information

Sums of Involving the Harmonic Numbers and the Binomial Coefficients

Sums of Involving the Harmonic Numbers and the Binomial Coefficients Ameica Joual of Computatioal Mathematics 5 5 96-5 Published Olie Jue 5 i SciRes. http://www.scip.og/oual/acm http://dx.doi.og/.46/acm.5.58 Sums of Ivolvig the amoic Numbes ad the Biomial Coefficiets Wuyugaowa

More information

Progression. CATsyllabus.com. CATsyllabus.com. Sequence & Series. Arithmetic Progression (A.P.) n th term of an A.P.

Progression. CATsyllabus.com. CATsyllabus.com. Sequence & Series. Arithmetic Progression (A.P.) n th term of an A.P. Pogessio Sequece & Seies A set of umbes whose domai is a eal umbe is called a SEQUENCE ad sum of the sequece is called a SERIES. If a, a, a, a 4,., a, is a sequece, the the expessio a + a + a + a 4 + a

More information

hw)th twrbq Kivrot Hata avah (Gräber der Begierde)

hw)th twrbq Kivrot Hata avah (Gräber der Begierde) Dáiel Pée Bió hw)h wbq Kio Haa aah (Gäbe de Begiede) (00 0) ü Bal öe o ba l ue The Comoiio i baed o he ollowig Hebew ex om Numbe ce :. A wid we oh om he Lod ad we quail om he ea ad ead hem oe he cam abou

More information

CS 326e F2002 Lab 1. Basic Network Setup & Ethereal Time: 2 hrs

CS 326e F2002 Lab 1. Basic Network Setup & Ethereal Time: 2 hrs CS 326 F2002 Lab 1. Bai Nwk Sup & Ehal Tim: 2 h Tak: 1 (10 mi) Vify ha TCP/IP i iall ah f h mpu 2 (10 mi) C h mpu gh via a wih 3 (10 mi) Obv h figuai f ah f h NIC f ah mpu 4 (10 mi) Saially figu a IP a

More information

OKANOGAN COUNTY COMMISSIONERS RESOLUTION

OKANOGAN COUNTY COMMISSIONERS RESOLUTION KG T MMISSIRS RSTI 43-16 WHRS, pusu RW 36. 1. 11, he egislie uhi f eh u, wih he ie ssise f he u R giee, pusu e e publi heigs hee, shll pepe p pehesie pg iluig ppse, bige, ph il sui pjes, he speifie pil

More information

Lesson 5. Chapter 7. Wiener Filters. Bengt Mandersson. r k s r x LTH. September Prediction Error Filter PEF (second order) from chapter 4

Lesson 5. Chapter 7. Wiener Filters. Bengt Mandersson. r k s r x LTH. September Prediction Error Filter PEF (second order) from chapter 4 Optimal Sigal oceig Leo 5 Capte 7 Wiee Filte I ti capte we will ue te model ow below. Te igal ito te eceie i ( ( iga. Nomally, ti igal i ditubed by additie wite oie (. Te ifomatio i i (. Alo, we ofte ued

More information

11. HAFAT İş-Enerji Power of a force: Power in the ability of a force to do work

11. HAFAT İş-Enerji Power of a force: Power in the ability of a force to do work MÜHENDİSLİK MEKNİĞİ. HFT İş-Eneji Pwe f a fce: Pwe in he abiliy f a fce d wk F: The fce applied n paicle Q P = F v = Fv cs( θ ) F Q v θ Pah f Q v: The velciy f Q ÖRNEK: İŞ-ENERJİ ω µ k v Calculae he pwe

More information

Introduction to Hypothesis Testing

Introduction to Hypothesis Testing Noe for Seember, Iroducio o Hyohei Teig Scieific Mehod. Sae a reearch hyohei or oe a queio.. Gaher daa or evidece (obervaioal or eerimeal) o awer he queio. 3. Summarize daa ad e he hyohei. 4. Draw a cocluio.

More information

Single Platform Emitter Location

Single Platform Emitter Location Sigle Plarm Emier Lcai AOADF FOA Ierermeery TOA SBI LBI Emier Lcai is Tw Esimai Prblems i Oe: Esimae Sigal Parameers a Deed Emier s Lcai: a Time--Arrival TOA Pulses b Pase Ierermeery: Pase is measured

More information

T h e C S E T I P r o j e c t

T h e C S E T I P r o j e c t T h e P r o j e c t T H E P R O J E C T T A B L E O F C O N T E N T S A r t i c l e P a g e C o m p r e h e n s i v e A s s es s m e n t o f t h e U F O / E T I P h e n o m e n o n M a y 1 9 9 1 1 E T

More information

F 1 F n kx. Keywords: entropy; independent assortment; random match; Hardy-Weinberg equilibrium; ternary tree algorithm

F 1 F n kx. Keywords: entropy; independent assortment; random match; Hardy-Weinberg equilibrium; ternary tree algorithm HEREDITAS (Beijig) 007 8, 9(8): 07 0 ISSN 05-977 www.chiagee.c w DOI: 0.60/yc-007-07 F F kx,,,, 545006 : e k w  r, p @ Âg k m k, gw k @, e m k  e k  m ; k m, Âd F p F r m, k F o, F r, q k  @ k hq @

More information

EEC 483 Computer Organization

EEC 483 Computer Organization EEC 8 Compuer Orgaizaio Chaper. Overview of Pipeliig Chau Yu Laudry Example Laudry Example A, Bria, Cahy, Dave each have oe load of clohe o wah, dry, ad fold Waher ake 0 miue A B C D Dryer ake 0 miue Folder

More information

The analysis of the method on the one variable function s limit Ke Wu

The analysis of the method on the one variable function s limit Ke Wu Ieraioal Coferece o Advaces i Mechaical Egieerig ad Idusrial Iformaics (AMEII 5) The aalysis of he mehod o he oe variable fucio s i Ke Wu Deparme of Mahemaics ad Saisics Zaozhuag Uiversiy Zaozhuag 776

More information

STRONG DEVIATION THEOREMS FOR THE SEQUENCE OF CONTINUOUS RANDOM VARIABLES AND THE APPROACH OF LAPLACE TRANSFORM

STRONG DEVIATION THEOREMS FOR THE SEQUENCE OF CONTINUOUS RANDOM VARIABLES AND THE APPROACH OF LAPLACE TRANSFORM Joural of Statitic: Advace i Theory ad Applicatio Volume, Number, 9, Page 35-47 STRONG DEVIATION THEORES FOR THE SEQUENCE OF CONTINUOUS RANDO VARIABLES AND THE APPROACH OF LAPLACE TRANSFOR School of athematic

More information

Work, Energy, and Power. AP Physics C

Work, Energy, and Power. AP Physics C k, Eneg, and Pwe AP Phsics C Thee ae man diffeent TYPES f Eneg. Eneg is expessed in JOULES (J) 4.19 J = 1 calie Eneg can be expessed me specificall b using the tem ORK() k = The Scala Dt Pduct between

More information

A B CDE F B FD D A C AF DC A F

A B CDE F B FD D A C AF DC A F International Journal of Arts & Sciences, CD-ROM. ISSN: 1944-6934 :: 4(20):121 131 (2011) Copyright c 2011 by InternationalJournal.org A B CDE F B FD D A C A BC D EF C CE C A D ABC DEF B B C A E E C A

More information

CSE 202: Design and Analysis of Algorithms Lecture 16

CSE 202: Design and Analysis of Algorithms Lecture 16 CSE 202: Desig ad Aalysis of Algorihms Lecure 16 Isrucor: Kamalia Chaudhuri Iequaliy 1: Marov s Iequaliy Pr(X=x) Pr(X >= a) 0 x a If X is a radom variable which aes o-egaive values, ad a > 0, he Pr[X a]

More information

APPLICATION OF A Z-TRANSFORMS METHOD FOR INVESTIGATION OF MARKOV G-NETWORKS

APPLICATION OF A Z-TRANSFORMS METHOD FOR INVESTIGATION OF MARKOV G-NETWORKS Joa of Aed Mahema ad Comaoa Meha 4 3( 6-73 APPLCATON OF A Z-TRANSFORMS METHOD FOR NVESTGATON OF MARKOV G-NETWORKS Mha Maay Vo Nameo e of Mahema Ceohowa Uey of Tehoogy Cęohowa Poad Fay of Mahema ad Come

More information

Copyright Birkin Cars (Pty) Ltd

Copyright Birkin Cars (Pty) Ltd e f u:- 5: K360 98AA RADIATOR 5: K360 053AA SEAT MOUNTING GROU 5:3 K360 06A WIER MOTOR GROU 5:4 K360 0A HANDRAKE 5:5 K360 0A ENTRE ONSOE 5:6 K360 05AA RO AGE 5:7 K360 48AA SARE WHEE RADE 5:8 K360 78AA

More information

PRICING AMERICAN PUT OPTION WITH DIVIDENDS ON VARIATIONAL INEQUALITY

PRICING AMERICAN PUT OPTION WITH DIVIDENDS ON VARIATIONAL INEQUALITY Joual of Mahemaical cieces: Aaces a Applicaios olume 37 06 Pages 9-36 Aailable a hp://scieificaacescoi DOI: hp://oiog/0864/msaa_700609 PRICIG AMERICA PUT OPTIO ITH DIIDED O ARIATIOAL IEQUALITY XIAOFAG

More information

Journal of Measurement & Educational Evaluation Studies Vol. 7, No. 17, Spring 2017 #$ % &' () & *+!,- .; :$ 5; :? # ' QI; ; E5?

Journal of Measurement & Educational Evaluation Studies Vol. 7, No. 17, Spring 2017 #$ % &' () & *+!,- .; :$ 5; :? # ' QI; ; E5? Journal of Measurement & Educational Evaluation Studies Vol. 7, No. 17, Spring 2017 109-131+, 1396 ' 17 $!"# 95/07/11: /08/24: 95 1! #$ % &' () & *+!,- ; : ; 9 #25 678 /0 1#23 4# 1A ; @.; 8 # ; 7?8 1#23

More information

TELEMATICS LINK LEADS

TELEMATICS LINK LEADS EEAICS I EADS UI CD PHOE VOICE AV PREIU I EADS REQ E E A + A + I A + I E B + E + I B + E + I B + E + H B + I D + UI CD PHOE VOICE AV PREIU I EADS REQ D + D + D + I C + C + C + C + I G G + I G + I G + H

More information

Exercise: Show that. Remarks: (i) Fc(l) is not continuous at l=c. (ii) In general, we have. yn ¾¾. Solution:

Exercise: Show that. Remarks: (i) Fc(l) is not continuous at l=c. (ii) In general, we have. yn ¾¾. Solution: Exercie: Show ha Soluio: y ¾ y ¾¾ L c Þ y ¾¾ p c. ¾ L c Þ F y (l Fc (l I[c,(l "l¹c Þ P( y c

More information

Adaptive Multiplexing Order Selection For Single-carrier MIMO Transmission

Adaptive Multiplexing Order Selection For Single-carrier MIMO Transmission Adaive Mulilexig Ode Seleio Fo Sigle-aie MIMO Tamiio Ryo AGAOKA Shiya KUMAGAI Teuya YAMAMOTO ad Fumiyui AACI e. of Commuiaio Egieeig Gaduae Shool of Egieeig Tohou Uiveiy 6-6-5 Aza-Aoba Aamai Aoba-u Sedai

More information

Mathematical Statistics. 1 Introduction to the materials to be covered in this course

Mathematical Statistics. 1 Introduction to the materials to be covered in this course Mahemaical Saisics Iroducio o he maerials o be covered i his course. Uivariae & Mulivariae r.v s 2. Borl-Caelli Lemma Large Deviaios. e.g. X,, X are iid r.v s, P ( X + + X where I(A) is a umber depedig

More information

Dangote Flour Mills Plc

Dangote Flour Mills Plc SUMMARY OF OFFER Opening Date 6 th September 27 Closing Date 27 th September 27 Shares on Offer 1.25bn Ord. Shares of 5k each Offer Price Offer Size Market Cap (Post Offer) Minimum Offer N15. per share

More information

COMPILATION OF AUTOMATA FROM MORPHOLOGICAL TWO-LEVEL RULES

COMPILATION OF AUTOMATA FROM MORPHOLOGICAL TWO-LEVEL RULES Kimmo Koskenniemi Re se ar ch Unit for Co mp ut at io na l Li ng ui st ic s University of Helsinki, Hallituskatu 11 SF-00100 Helsinki, Finland COMPILATION OF AUTOMATA FROM MORPHOLOGICAL TWO-LEVEL RULES

More information

Lesson 5. Chapter 7. Wiener Filters. Bengt Mandersson. r x k We assume uncorrelated noise v(n). LTH. September 2010

Lesson 5. Chapter 7. Wiener Filters. Bengt Mandersson. r x k We assume uncorrelated noise v(n). LTH. September 2010 Optimal Sigal Poceig Leo 5 Chapte 7 Wiee Filte I thi chapte we will ue the model how below. The igal ito the eceive i ( ( iga. Nomally, thi igal i ditubed by additive white oie v(. The ifomatio i i (.

More information

In order to ensure that an overall development in service by those. of total. rel:rtins lo the wapris are

In order to ensure that an overall development in service by those. of total. rel:rtins lo the wapris are AhAY ggkhu e evue he eve us wch my be eese s esu eucs ese mbes buges hve bee ke cvu vs. Css e vse e' he w m ceges cec ec css. Dec Dgqs_1q W qge5ee.pe_s_ v V cuss ke ecy 1 hc huse ees. bse cu wc esb shmes.

More information

HRW 7e Chapter 13 Page 1 of 5

HRW 7e Chapter 13 Page 1 of 5 HW 7e Chapte Pae o 5 Halliday/enick/Walke 7e Chapte Gaitation The manitude o the oce o one paticle on the othe i ien by F = Gm m /, whee m and m ae the mae, i thei epaation, and G i the unieal aitational

More information

Hadamard matrices from the Multiplication Table of the Finite Fields

Hadamard matrices from the Multiplication Table of the Finite Fields adamard marice from he Muliplicaio Table of he Fiie Field 신민호 송홍엽 노종선 * Iroducio adamard mari biary m-equece New Corucio Coe Theorem. Corucio wih caoical bai Theorem. Corucio wih ay bai Remark adamard

More information

Downloaded from pdmag.info at 18: on Friday March 22nd 2019

Downloaded from pdmag.info at 18: on Friday March 22nd 2019 2 (- ( ( )*+, )%.!"# $% &" :( ( 2 * -% 345 678-397.) /0 &" &2. ) ( B(

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

LECTURE 13 SIMULTANEOUS EQUATIONS

LECTURE 13 SIMULTANEOUS EQUATIONS NOVEMBER 5, 26 Demad-upply ytem LETURE 3 SIMULTNEOUS EQUTIONS I thi lecture, we dicu edogeeity problem that arie due to imultaeity, i.e. the left-had ide variable ad ome of the right-had ide variable are

More information

ECEN474/704: (Analog) VLSI Circuit Design Spring 2018

ECEN474/704: (Analog) VLSI Circuit Design Spring 2018 EEN474/704: (Anal) LSI cut De S 08 Lectue 8: Fequency ene Sa Pale Anal & Mxed-Sal ente Texa A&M Unety Annunceent & Aenda HW Due Ma 6 ead aza hate 3 & 6 Annunceent & Aenda n-suce A Fequency ene Oen-cut

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

I M P O R T A N T S A F E T Y I N S T R U C T I O N S W h e n u s i n g t h i s e l e c t r o n i c d e v i c e, b a s i c p r e c a u t i o n s s h o

I M P O R T A N T S A F E T Y I N S T R U C T I O N S W h e n u s i n g t h i s e l e c t r o n i c d e v i c e, b a s i c p r e c a u t i o n s s h o I M P O R T A N T S A F E T Y I N S T R U C T I O N S W h e n u s i n g t h i s e l e c t r o n i c d e v i c e, b a s i c p r e c a u t i o n s s h o u l d a l w a y s b e t a k e n, i n c l u d f o l

More information

SMT 2018 Geometry Test Solutions February 17, 2018

SMT 2018 Geometry Test Solutions February 17, 2018 SMT 018 Geometry Test Solutions February 17, 018 1. Consider a semi-circle with diameter AB. Let points C and D be on diameter AB such that CD forms the base of a square inscribed in the semicircle. Given

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

Comparing Different Estimators for Parameters of Kumaraswamy Distribution

Comparing Different Estimators for Parameters of Kumaraswamy Distribution Compaig Diffee Esimaos fo Paamees of Kumaaswamy Disibuio ا.م.د نذير عباس ابراهيم الشمري جامعة النهرين/بغداد-العراق أ.م.د نشات جاسم محمد الجامعة التقنية الوسطى/بغداد- العراق Absac: This pape deals wih compaig

More information

FARADAY'S LAW dt

FARADAY'S LAW dt FAADAY'S LAW 31.1 Faaday's Law of Induction In the peious chapte we leaned that electic cuent poduces agnetic field. Afte this ipotant discoey, scientists wondeed: if electic cuent poduces agnetic field,

More information

Meromorphic Functions Sharing Three Values *

Meromorphic Functions Sharing Three Values * Alied Maheaic 11 718-74 doi:1436/a11695 Pulihed Olie Jue 11 (h://wwwscirporg/joural/a) Meroorhic Fucio Sharig Three Value * Arac Chagju Li Liei Wag School o Maheaical Sciece Ocea Uiveriy o Chia Qigdao

More information

K3 p K2 p Kp 0 p 2 p 3 p

K3 p K2 p Kp 0 p 2 p 3 p Mah 80-00 Mo Ar 0 Chaer 9 Fourier Series ad alicaios o differeial equaios (ad arial differeial equaios) 9.-9. Fourier series defiiio ad covergece. The idea of Fourier series is relaed o he liear algebra

More information

THIS PAGE DECLASSIFIED IAW EO IRIS u blic Record. Key I fo mation. Ma n: AIR MATERIEL COMM ND. Adm ni trative Mar ings.

THIS PAGE DECLASSIFIED IAW EO IRIS u blic Record. Key I fo mation. Ma n: AIR MATERIEL COMM ND. Adm ni trative Mar ings. T H S PA G E D E CLA SSFED AW E O 2958 RS u blc Recod Key fo maon Ma n AR MATEREL COMM ND D cumen Type Call N u b e 03 V 7 Rcvd Rel 98 / 0 ndexe D 38 Eneed Dae RS l umbe 0 0 4 2 3 5 6 C D QC d Dac A cesson

More information

Big O Notation for Time Complexity of Algorithms

Big O Notation for Time Complexity of Algorithms BRONX COMMUNITY COLLEGE of he Ciy Uiversiy of New York DEPARTMENT OF MATHEMATICS AND COMPUTER SCIENCE CSI 33 Secio E01 Hadou 1 Fall 2014 Sepember 3, 2014 Big O Noaio for Time Complexiy of Algorihms Time

More information

Numerical Solution of Transient Thermal Stresses in a Functionally Graded Cylinder

Numerical Solution of Transient Thermal Stresses in a Functionally Graded Cylinder La d gg Mha gg Glgy al l f a hal a Fally Gadd yld IQ H KHOLO I-LMH aal gg a Jda y f ad hlgy P.O x Ibd JO al: daabh@.d. ba: - h a d h a hal a la yld ad f a fally gadd aal FGM. h yld aal dd b gadd alg h

More information

Maxwell Equations. Dr. Ray Kwok sjsu

Maxwell Equations. Dr. Ray Kwok sjsu Maxwell quains. Ray Kwk sjsu eeence: lecmagneic Fields and Waves, Lain & Csn (Feeman) Inducin lecdynamics,.. Giihs (Penice Hall) Fundamenals ngineeing lecmagneics,.k. Cheng (Addisn Wesley) Maxwell quains.

More information

Relations on the Apostol Type (p, q)-frobenius-euler Polynomials and Generalizations of the Srivastava-Pintér Addition Theorems

Relations on the Apostol Type (p, q)-frobenius-euler Polynomials and Generalizations of the Srivastava-Pintér Addition Theorems Tish Joal of Aalysis ad Nmbe Theoy 27 Vol 5 No 4 26-3 Available olie a hp://pbssciepbcom/ja/5/4/2 Sciece ad Edcaio Pblishig DOI:269/ja-5-4-2 Relaios o he Aposol Type (p -Fobeis-Ele Polyomials ad Geealizaios

More information

Structure and Some Geometric Properties of Nakano Difference Sequence Space

Structure and Some Geometric Properties of Nakano Difference Sequence Space Stuctue ad Soe Geoetic Poeties of Naao Diffeece Sequece Sace N Faied ad AA Baey Deatet of Matheatics, Faculty of Sciece, Ai Shas Uivesity, Caio, Egyt awad_baey@yahooco Abstact: I this ae, we exted the

More information

EQUATION SHEET Principles of Finance Exam 1

EQUATION SHEET Principles of Finance Exam 1 EQUATION SHEET Piciple of iace Exa INANCIAL STATEMENT ANALYSIS Ne cah flow Ne icoe + Depeciaio ad aoizaio DuPo equaio: ROANe pofi agi Toal ae uove Ne icoe Sale Sale Toal ae DuPo equaio: ROE ROA Equiy uliplie

More information

Basic Results in Functional Analysis

Basic Results in Functional Analysis Preared by: F.. ewis Udaed: Suday, Augus 7, 4 Basic Resuls i Fucioal Aalysis f ( ): X Y is coiuous o X if X, (, ) z f( z) f( ) f ( ): X Y is uiformly coiuous o X if i is coiuous ad ( ) does o deed o. f

More information

Representing Knowledge. CS 188: Artificial Intelligence Fall Properties of BNs. Independence? Reachability (the Bayes Ball) Example

Representing Knowledge. CS 188: Artificial Intelligence Fall Properties of BNs. Independence? Reachability (the Bayes Ball) Example C 188: Aificial Inelligence Fall 2007 epesening Knowledge ecue 17: ayes Nes III 10/25/2007 an Klein UC ekeley Popeies of Ns Independence? ayes nes: pecify complex join disibuions using simple local condiional

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

Inference of the Second Order Autoregressive. Model with Unit Roots

Inference of the Second Order Autoregressive. Model with Unit Roots Ieraioal Mahemaical Forum Vol. 6 0 o. 5 595-604 Iferece of he Secod Order Auoregressive Model wih Ui Roos Ahmed H. Youssef Professor of Applied Saisics ad Ecoomerics Isiue of Saisical Sudies ad Research

More information

Executive Committee and Officers ( )

Executive Committee and Officers ( ) Gifted and Talented International V o l u m e 2 4, N u m b e r 2, D e c e m b e r, 2 0 0 9. G i f t e d a n d T a l e n t e d I n t e r n a t i o n a2 l 4 ( 2), D e c e m b e r, 2 0 0 9. 1 T h e W o r

More information

Modeling the Evolution of Demand Forecasts with Application to Safety Stock Analysis in Production/Distribution Systems

Modeling the Evolution of Demand Forecasts with Application to Safety Stock Analysis in Production/Distribution Systems Modeling he Evoluion of Demand oreca wih Applicaion o Safey Sock Analyi in Producion/Diribuion Syem David Heah and Peer Jackon Preened by Kai Jiang Thi ummary preenaion baed on: Heah, D.C., and P.L. Jackon.

More information

Regular Semigroups with Inverse Transversals

Regular Semigroups with Inverse Transversals International Mathematical Forum, Vol. 7, 2012, no. 31, 1547-1552 Regular Semigroups with Inverse Transversals Junwei Shi Zhenji Tian School of Sciences Lanzhou University of Technology Lanzhou, Gansu,

More information

Notes on Inductance and Circuit Transients Joe Wolfe, Physics UNSW. Circuits with R and C. τ = RC = time constant

Notes on Inductance and Circuit Transients Joe Wolfe, Physics UNSW. Circuits with R and C. τ = RC = time constant Nes n Inducance and cu Tansens Je Wlfe, Physcs UNSW cus wh and - Wha happens when yu clse he swch? (clse swch a 0) - uen flws ff capac, s d Acss capac: Acss ess: c d s d d ln + cns. 0, ln cns. ln ln ln

More information