Wavelet Video with Unequal Error Protection Codes in W-CDMA System and Fading Channels

Size: px
Start display at page:

Download "Wavelet Video with Unequal Error Protection Codes in W-CDMA System and Fading Channels"

Transcription

1 Wavelet Vide with Uequal Errr Prtecti Cdes i W-CDMA System ad Fadig Chaels MINH HUNG LE ad RANJITH LIYANA-PATHIRANA Schl f Egieerig ad Idustrial Desig Cllege f Sciece, Techlgy ad Evirmet Uiversity f Wester Sydey Secd Aveue, Kigswd, 747, N.S.W. AUSTRALIA Abstract: - Wavelet-based algrithm fr vide cmpressi with uequal errr prtecti (UEP) cdes i widebad cde divisi multiple access (W-CDMA) system ver additive white Gaussia ise (AWGN) ad Rayleigh fadig chaels are aalysed. The utilizati f Wavelets has cme ut t be a pwerful methd fr cmpress vide sequece. The wavelet trasfrm cmpressi techique has shw t be mre apprpriate t high quality vide applicatis, prducig better quality utput fr the cmpressed frames f vide. A spatially scalable vide cdig framewrk f MPEG i which mti crrespdeces betwee successive vide frames are explited i the wavelet trasfrm dmai. The basic mtivati fr ur cder is that mti fields are typically smth that ca be efficietly captured thrugh a multireslutial framewrk. Wavelet decmpsiti is applied t vide frames ad the cefficiets at each level are predicted frm the carser level thrugh backward mti cmpesati. The prpsed algrithms f the embedded zer-tree wavelet (EZW) cder ad the -D wavelet packet trasfrm (-D WPT) are evaluated. Key-Wrds: - Vide sequece, Uequal errr prtecti cdes, Embedded zer-tree wavelet trasfrm, -D wavelet packet trasfrm, W-CDMA, AWGN, Rayleigh fadig chaels. 1 Itrducti The wavelet fuctis are develped fr harmic aalysis, sigal represetati, speech ad vide badwidth cmpressi, multiresluti sigal prcessig, ad sigal desig i varius cdig ad cmmuicati applicatis. The wavelets i cmmercial applicatis were maily with efficiet cmpressi techiques sigals such as vice ad vide. This was due t the lgarithmic-scale decmpsiti i frequecy, which fits aturally i may f the sud ad vide sequece recstructi studies. Wavelet thery cvers quite a large area. It treats bth the ctiuus ad discrete time cases. The itrducti f the embedded zer-tree ccept fr wavelet-based vide cmpressi has geerated a sigificat imprvemet i perfrmace cmpared t previus vide cdig methds. A refiemet f the EZW apprach, called set partitiig it hierarchical trees (SPIHT) by Said ad Pearlma, is the mst well kw EZW derivative. While SPIHT eys a gd rate-distrti perfrmace fr vide sequeces with cmparatively lw cmplexity, it is quite fragile agaist bit errrs i isy cmmuicati chaels. Direct sequece sigal acquisiti i W-CDMA evirmet is estimated. A digital matched filter is preseted ad ivestigated fr direct sequece spread-spectrum systems [1]. The cdig scheme presets fur levels f errr prtecti fr differet sets f bits i a trasmitted symbl usig W-CDMA system ver AWGN ad Rayleigh fadig chaels. The prpsed scheme accmplishes uequal errr prtecti by ecdig the data accrdig t the sigificace f the ifrmati ad switchig betwee fur cdes. The scheme uses the differet pseud-ise cdes f digital matched filter sychrizer t make up fur levels f uequal errr prtecti cdes. It was shw that fur levels f differet errr prtectis were easily accmplished with the digital matched filter pseud-ise cde sychrizer systems ver AWGN ad Rayleigh fadig chaels by prvidig the cded detecti at the receiver. The scheme prvides the capability f multi-level errr prtecti withut cmplexity as cmpared t regular digital matched filter pseud-ise cde schemes. Wavelet vide with UEP cdes i W-CDMA system btais smaller PSNR tha wavelet vide with UEP cdes fr widebad MC-CDMA ad Rake receiver. Hwever, it requires less cmplex desig ad less cst f acquisiti [].

2 Wavelet Vide Trasmissi with UEP Cdes i W-CDMA System ver AWGN ad Rayleigh Fadig Chaels The fur levels f uequal errr prtecti cdes with wavelet vide trasmissi i W-CDMA system ver AWGN ad Rayleigh fadig chaels are aalyzed. Figure 1 illustrates the blck diagram f wavelet vide trasmissi with UEP cdes i W-CDMA system ver AWGN ad Rayleigh fadig chaels Ecder. Figure shws the blck diagram f wavelet vide trasmissi with UEP cdes i W- CDMA system ver AWGN ad Rayleigh fadig chaels Decder. Fig. Blck Diagram f Wavelet Vide Trasmissi with UEP Cdes i W-CDMA system ver AWGN ad Rayleigh fadig chaels Decder Fig. 1 Blck Diagram f Wavelet Vide Trasmissi with UEP Cdes i W-CDMA system ver AWGN ad Rayleigh fadig chaels Ecder The discrete wavelet trasfrm is described with the geeric sigal g(t) that ca be represeted i terms f traslates ad dilates typically badpass f a sigle prttype wavelet t). + g(t) = α (i, (1) i, = r similarly fr sme W>0 where g(t) + α (i, = W i= η ( α(i, -W i θ( i + i = g ( t ) dt () are detail cefficiets f wavelet. + = g ( t) ( dt η ( θ are apprximati cefficiets r scalig cefficiets, ad θ(t) is a lw-pass scalig fucti. The sigificace is the iterpretati f equati () as a multiresluti aalysis f g(t): i idexes the scale r resluti, the smaller i the higher the resluti, while idexes the spatial lcati f aalysis. If the mther wavelet is cetred at time 0 ad frequecy f c, α(i, measures the ctet f arud time i ad frequecy -i f c, while η( represets the lcal mea arud time W. I this framewrk, we ca thik f g(t) as the fiest scale (W=0) represetati f g(t) itself. The fucti t) has t satisfy sme critical cditis t esure that equati () hlds fr ay square itegrable fucti g(t). I particular, t) has t satisfy the tw scale equatis: θ ( t) = c ( ) θ (t ) (3) β ( t ) = c1( ) θ (t ) (4) where the cefficiets c i () ca be zer ly ver a fiite umber f csecutive values f. Hece, β i, ( t) = β ( ; θ i, ( t) = θ ( The three rthgalities cstraits require * θ i, ( t) θ ( t) dt = δ ( ) i, * β ( t) β ( t) dt = δ ( ) = δ ( i i ) i, i,

3 β * ( t ) θ ( t ) dt = δ ( ) = 0 i, i, The three rthgalities are satisfied by cefficiets c i () thse have the fllwig prperties: c ( ) c ( + k) = δ ( k) c1 ( ) = ( 1) c ( ) where c i () are the cefficiets f a perfect recstructi tw-bad r dyadic filter bak with the quadrature mirrr recstructi prperty. Therefre, the desig f wavelets is equivalet t the desig f filter baks. Observe that the cditis impsed up util w are t sufficiet t cstruct i practice useful wavelets. Certaily, they ca lead t decmpsitis with t eugh regularity. Regularity is impsed requirig a large umber f vaishig mmets. I practice, η( ad α(i, ca be cmputed recursively frm α(i+1, usig the efficiet pyramid algrithm prpsed by Mallat [3]. It is t ecessary t explicitly cmpute the shape f θ(t) ad t). The basic applicatis f wavelets i this paper stems frm a multiresluti decmpsiti f a time-varyig multipath respse ~ ( f the frm h t, τ) at ay τ with respect t t are: ~ h (t, τ ) = + W i= η (, τ ) α(i,, τ ) θ( (5) where α(i,,τ) are wavelet cefficiets ad η(,τ) are scalig cefficiets. If the chael is mdelled as determiistic, wavelet ad scalig cefficiets are csidered determiistic, ad if the chael is mdelled as radm, wavelet ad scalig cefficiets are csidered radm parameters. The waveletbased represetati will exhibit glbal characteristics f the chael dyamics i the lwresluti cefficiets, while retaiig lcal rapid trasitis i ust a few cefficiets at higher reslutis. A practical advatage is that the decmpsiti decuples the variatis i time ad relegates them i t) ad θ(t), s that the wavelets cefficiets are ideed time ivariat fr ay τ. Subsequetly, we will assume discretized respses with reslvable multipath cmpets f the frm ~ Q i 1 i t h( t, τ ) = = g ( ) δ ( τ τ ) [3]..1 Embedded Zer-Tree Wavelet Cdig Embedded zer-tree wavelet algrithm explits the imprtat hypthesis. After the embedded zer-tree wavelet trasfrm f a vide sequece, the imprtat data is ccetrated i the upper left crer that crrespds t the lw frequecy rage f the wavelet cefficiets. The remaiig data i the high frequecy dmai is t as sigificat. A wavelet i cefficiet tree is defied as the set f cefficiets frm differet bads that represet the same spatial regi i the vide sequece. A wavelet vide sequece represetati ca be thught as a tree structured spatial set f cefficiets [1]. Figure 3 illustrates three levels wavelet decmpsiti f the vide sequece. The lwest frequecy bad f the decmpsiti is represeted by the rt des (tp left) f the tree (LL 3 ), the highest frequecy bads by the leaf des (bttm right) f the tree, ad each paret de represets a lwer frequecy cmpet tha its childre. Except fr a rt de, which has ly three childre des, each paret de has fur childre des, the x regi f the same spatial lcati i the immediately higher frequecy bad [4]. Fig. 3 Three Levels Wavelet Decmpsiti. Tw-Dimesial Wavelet Packet Trasfrm Tw-dimesial wavelet packet trasfrm f vide sequece is cmpsed f lw frequecy cmpets ad high frequecy cmpets. Lw frequecy cmpets give a vide sequece its fudati, r character, while high frequecy cmpets give a vide sequece it is fie details r uaces. Figure 4 illustrates the wavelet decmpsiti f the twdimesial wavelet packet trasfrm fr the vide sequece. The utput frm the lw pass filter prduces ad apprximati f the sigal based the lw frequecy detail cefficiets. The utput frm the high pass filter prduces the fie details f the vide sequece, that whe put tgether will frm the rigial vide sequece. Hwever, these values are dw-sampled. This meas that the utput f either filter has every secd cefficiet drpped. This effectively halves the umber f cefficiets frm each filter. Nevertheless, at the recstructi side, this ca prduce sme distrti, but if the filters are chse carefully the perfect recstructi ca ccur. Oe f the aspects that make wavelets s suited t vide cdig is that the filterig prcess ca be iterated repeatedly, allwig us t break up a

4 vide sequece it varius lwer resluti versis r multilevel decmpsiti. Typically, the way i which this is cducted is by filterig the utput f the Lw Frequecy Decmpsig Filter with the same wavelet fucti. The lw frequecy cefficiets f this utput may agai be filtered, extractig mre ifrmati ad s. Nw, because there is a dw samplig rutie de after each filterig prcess, the theretical limit that stps us frm iteratig is util we reach e discrete wavelet trasfrm cefficiet. I geeral, the mre levels f decmpsiti we have, the better the cmpressi, althugh lss f quality []. Fig. 4 Wavelet Decmpsiti f the -D Wavelet Packet Trasfrm fr the Vide Sequece 3 Experimetal Results The QCIF vide sequeces with cmpressi rate f 0.31 bits/pixel are examied. The W-CDMA system btais a badwidth f 5MHz ad will als be i may idr achievemets. The varius sectis f a cmpressed vide sequece btai differet imprtace ad errr sesitivity. The W-CDMA system ver AWGN ad Rayleigh fadig chaels with uequal errr prtecti cdes are csidered with fur levels f sigificace fr peratig with data stream f ifrmati. The prpsed scheme accmplishes uequal errr prtecti by ecdig the data accrdig t the sigificace f the ifrmati ad dividig it fur cdes. The cdig scheme itrduces fur levels f errr prtecti fr differet sets f bits i a trasmitted symbl fuctiig W-CDMA system ver AWGN ad Rayleigh fadig chaels. The prpsed scheme applies the differet pseud-ise cdes f digital matched filter sychrizer t cstruct fur levels f uequal errr prtecti cdes. The fuctiig estimati f fur uequal errr prtecti cdes with W-CDMA system ver AWGN ad Rayleigh fadig chaels are evaluated. Fr the Embedded Zer-Tree Wavelet Cdig, the fur levels f uequal errr prtecti cdes with fur sigificat levels f uequal errr prtecti cdes are prpsed fr this digital matched filter pseud-ise cde sychrizer scheme. Frm figure 3, the first level r the LL 3 is the lwest errr prtecti level with ecdig. The secd level r the HL 3, LH 3, HH 3 is the lwer errr prtecti level with easiest level f digital matched filter pseud-ise cde sychrizer. The third level r the HL, LH, HH is the higher errr prtecti level with easier level f digital matched filter pseudise cde sychrizer. The furth level r the HL 1, LH 1, HH 1 is the highest errr prtecti level with harder level f digital matched filter pseud-ise cde sychrizer. Fr the -D Wavelet Packet Trasfrm, the fur levels f uequal errr prtecti cdes with fur differet levels f uequal errr prtecti cdes are desiged fr this digital matched filter pseud-ise cde sychrizer scheme. Figure 4 illustrates the Wavelet Decmpsiti f the -D Wavelet Packet Trasfrm fr the vide sequece. The first level r the average sigal is the lwest errr prtecti level with easiest level f digital matched filter pseudise cde sychrizer. The secd level r the hriztal vide sequece features is the lwer errr prtecti level with easier level f digital matched filter pseud-ise cde sychrizer. The third level r the vertical vide sequece features is the higher errr prtecti level with harder level f digital matched filter pseud-ise cde sychrizer. The furth level r the diagal vide sequece features is the highest errr prtecti level with hardest level f digital matched filter pseud-ise cde sychrizer. Matlab prgrams are writte t simulate the utcmes f the fur levels f UEP cdes with wavelet vide cmpressi i W-CDMA system ver AWGN ad Rayleigh fadig chaels. The peak sigal t ise rati is calculated. The bective vide sequece quality has bee evaluated usig peak sigal t ise rati, which is defied as fllws: ( PeakSigal Value ) PSNR = 10 lg 10 (6) MeaSquare Errr where, Peak Sigal Value=55 fr a 8 bits/pixel vide sequece. MeaSquare Errr = 1 ( x ) i y i (7) N N ( ) x i -y i =value f pixel (i, i the rigial ad recstructed vide sequeces respectively. NxN=umber f pixels i the vide sequece. i

5 The table f utcmes f tested Miss America sequeces is tabulated i the table 1. Miss America Sequeces i QCIF with Cmpressi rate f 0.31 (bits/pixel) W-CDMA System ver AWGN chaels W-CDMA System ver Rayleigh fadig chaels PSNR (db) f Fur levels UEP fr EZWT PSNR (db) f Fur levels UEP fr -D WPT Fig. 6 (a) Fig. 6 (b) Table 1: Outcmes f tested Miss America sequeces The rigial tested vide sequeces f Miss America i QCIF (176x144) are illustrated i figure 5. Fig. 6 (c) Fig. 6 (d) Fig. 6 The recstructed Miss America sequece with Fur levels f Embedded Zertree Wavelet trasfrm i W-CDMA system ver AWGN chaels; PSNR=11 db (a) Frame umber 0 (b) Frame umber 0 (c) Frame umber 45 (d) Frame umber 80 Fig. 5 (a) Fig. 5 (b) Fig. 7 (a) Fig. 7 (b) Fig. 5 (c) Fig. 5 (d) Fig. 5 The rigial Miss America sequece i QCIF (a) Frame umber 0 (b) Frame umber 0 (c) Frame umber 45 (d) Frame umber 80 Fig. 7 (c) Fig. 7 (d) The results f Miss America sequeces i QCIF (176x144) are illustrated i figure 6, figure 7, figure 8 ad figure 9. Fig. 7 The recstructed Miss America sequece with Fur levels f Embedded Zertree Wavelet trasfrm i W-CDMA system ver Rayleigh fadig chaels; PSNR=3 db (a) Frame umber 0 (b) Frame umber 0 (c) Frame umber 45 (d) Frame umber 80

6 Fig. 8 (a) Fig. 8 (c) Fig. 8 (b) Fig. 8 (d) Fig. 8 The recstructed Miss America sequece with Fur levels f -D Wavelet Packet Trasfrm i W-CDMA system ver AWGN chaels; PSNR=10 db (a) Frame umber 0 (b) Frame umber 0 (c) Frame umber 45 (d) Frame umber 80 4 Cclusi Wavelet vide cmpressi with fur levels f UEP cdes i W-CDMA system ver AWGN ad Rayleigh fadig chaels are perfrmed ad evaluated. The prpsed scheme achieves uequal errr prtecti by ecdig the data accrdig t the imprtace f the ifrmati ad dividig it fur cdes. The cdig scheme establishes fur levels f errr prtecti fr varius sets f bits i a trasmitted symbl with W-CDMA system ver AWGN ad Rayleigh fadig chaels. The scheme perates the differet pseud-ise cdes f digital matched filter sychrizer t create fur levels f uequal errr prtecti cdes. Wavelet vide cmpressi with fur levels f UEP cdes i W- CDMA system ver AWGN ad Rayleigh fadig chaels are fuctied t icrease the vide sequeces pre-emiece. EZW trasfrm cdig i fur levels f UEP cdes with W-CDMA system ver AWGN ad Rayleigh fadig chaels has advatages cmpared t -D WPT cdig i fur levels f UEP cdes with W-CDMA system ver AWGN ad Rayleigh fadig chaels. The Rayleigh fadig chaels achieve higher PSNR tha the AWGN chaels. The qualities f QCIF vide sequeces imprve with the prgressive icrease f the PSNR. The scheme demstrates desig flexibility s that it is easily mdified t accmmdate differet eeds fr errr prtecti i varius data trasmissi systems. Fig. 9 (a) Fig. 9 (c) Fig. 9 (b) Fig. 9 (d) Fig. 9 The recstructed Miss America sequece with Fur levels f -D Wavelet Packet Trasfrm i W-CDMA system ver Rayleigh fadig chaels; PSNR=31 db (a) Frame umber 0 (b) Frame umber 0 (c) Frame umber 45 (d) Frame umber 80 Refereces: [1] Mih Hug Le ad Raith Liyaa-Pathiraa, Perfrmace Evaluati f Rake Receiver fr Wavelet Vide with UEP Cdes i W-CDMA System ad Fadig Chaels, The 3 rd WSEAS Iteratial Cferece Sigal, Speech ad Image Prcessig, Octber 003. [] Mih Hug Le ad Raith Liyaa-Pathiraa, Wavelet Vide with Uequal Errr Prtecti Cdes fr Widebad Multicarrier CDMA ver Fadig Chaels, The 3 rd WSEAS Iteratial Cferece Sigal, Speech ad Image Prcessig, Octber 003. [3] S. Mallat, A Thery f Multiresluti Sigal Decmpsiti: The Wavelet Represetati, IEEE Tras., PAMI-11: , [4] J. Shapir, Embedded Image Cdig Usig Zer Trees f Wavelet Cefficiets, IEEE Tras. Sigal Prcess. 41, , 1993.

D.S.G. POLLOCK: TOPICS IN TIME-SERIES ANALYSIS STATISTICAL FOURIER ANALYSIS

D.S.G. POLLOCK: TOPICS IN TIME-SERIES ANALYSIS STATISTICAL FOURIER ANALYSIS STATISTICAL FOURIER ANALYSIS The Furier Represetati f a Sequece Accrdig t the basic result f Furier aalysis, it is always pssible t apprximate a arbitrary aalytic fucti defied ver a fiite iterval f the

More information

Author. Introduction. Author. o Asmir Tobudic. ISE 599 Computational Modeling of Expressive Performance

Author. Introduction. Author. o Asmir Tobudic. ISE 599 Computational Modeling of Expressive Performance ISE 599 Cmputatial Mdelig f Expressive Perfrmace Playig Mzart by Aalgy: Learig Multi-level Timig ad Dyamics Strategies by Gerhard Widmer ad Asmir Tbudic Preseted by Tsug-Ha (Rbert) Chiag April 5, 2006

More information

The Excel FFT Function v1.1 P. T. Debevec February 12, The discrete Fourier transform may be used to identify periodic structures in time ht.

The Excel FFT Function v1.1 P. T. Debevec February 12, The discrete Fourier transform may be used to identify periodic structures in time ht. The Excel FFT Fucti v P T Debevec February 2, 26 The discrete Furier trasfrm may be used t idetify peridic structures i time ht series data Suppse that a physical prcess is represeted by the fucti f time,

More information

Chapter 3.1: Polynomial Functions

Chapter 3.1: Polynomial Functions Ntes 3.1: Ply Fucs Chapter 3.1: Plymial Fuctis I Algebra I ad Algebra II, yu ecutered sme very famus plymial fuctis. I this secti, yu will meet may ther members f the plymial family, what sets them apart

More information

Multi-objective Programming Approach for. Fuzzy Linear Programming Problems

Multi-objective Programming Approach for. Fuzzy Linear Programming Problems Applied Mathematical Scieces Vl. 7 03. 37 8-87 HIKARI Ltd www.m-hikari.cm Multi-bective Prgrammig Apprach fr Fuzzy Liear Prgrammig Prblems P. Padia Departmet f Mathematics Schl f Advaced Scieces VIT Uiversity

More information

Fourier Series & Fourier Transforms

Fourier Series & Fourier Transforms Experimet 1 Furier Series & Furier Trasfrms MATLAB Simulati Objectives Furier aalysis plays a imprtat rle i cmmuicati thery. The mai bjectives f this experimet are: 1) T gai a gd uderstadig ad practice

More information

ENGI 4421 Central Limit Theorem Page Central Limit Theorem [Navidi, section 4.11; Devore sections ]

ENGI 4421 Central Limit Theorem Page Central Limit Theorem [Navidi, section 4.11; Devore sections ] ENGI 441 Cetral Limit Therem Page 11-01 Cetral Limit Therem [Navidi, secti 4.11; Devre sectis 5.3-5.4] If X i is t rmally distributed, but E X i, V X i ad is large (apprximately 30 r mre), the, t a gd

More information

Axial Temperature Distribution in W-Tailored Optical Fibers

Axial Temperature Distribution in W-Tailored Optical Fibers Axial Temperature Distributi i W-Tailred Optical ibers Mhamed I. Shehata (m.ismail34@yah.cm), Mustafa H. Aly(drmsaly@gmail.cm) OSA Member, ad M. B. Saleh (Basheer@aast.edu) Arab Academy fr Sciece, Techlgy

More information

Ch. 1 Introduction to Estimation 1/15

Ch. 1 Introduction to Estimation 1/15 Ch. Itrducti t stimati /5 ample stimati Prblem: DSB R S f M f s f f f ; f, φ m tcsπf t + φ t f lectrics dds ise wt usually white BPF & mp t s t + w t st. lg. f & φ X udi mp cs π f + φ t Oscillatr w/ f

More information

5.1 Two-Step Conditional Density Estimator

5.1 Two-Step Conditional Density Estimator 5.1 Tw-Step Cditial Desity Estimatr We ca write y = g(x) + e where g(x) is the cditial mea fucti ad e is the regressi errr. Let f e (e j x) be the cditial desity f e give X = x: The the cditial desity

More information

A New Method for Finding an Optimal Solution. of Fully Interval Integer Transportation Problems

A New Method for Finding an Optimal Solution. of Fully Interval Integer Transportation Problems Applied Matheatical Scieces, Vl. 4, 200,. 37, 89-830 A New Methd fr Fidig a Optial Sluti f Fully Iterval Iteger Trasprtati Prbles P. Padia ad G. Nataraja Departet f Matheatics, Schl f Advaced Scieces,

More information

Intermediate Division Solutions

Intermediate Division Solutions Itermediate Divisi Slutis 1. Cmpute the largest 4-digit umber f the frm ABBA which is exactly divisible by 7. Sluti ABBA 1000A + 100B +10B+A 1001A + 110B 1001 is divisible by 7 (1001 7 143), s 1001A is

More information

Markov processes and the Kolmogorov equations

Markov processes and the Kolmogorov equations Chapter 6 Markv prcesses ad the Klmgrv equatis 6. Stchastic Differetial Equatis Csider the stchastic differetial equati: dx(t) =a(t X(t)) dt + (t X(t)) db(t): (SDE) Here a(t x) ad (t x) are give fuctis,

More information

ENGI 4421 Central Limit Theorem Page Central Limit Theorem [Navidi, section 4.11; Devore sections ]

ENGI 4421 Central Limit Theorem Page Central Limit Theorem [Navidi, section 4.11; Devore sections ] ENGI 441 Cetral Limit Therem Page 11-01 Cetral Limit Therem [Navidi, secti 4.11; Devre sectis 5.3-5.4] If X i is t rmally distributed, but E X i, V X i ad is large (apprximately 30 r mre), the, t a gd

More information

BIO752: Advanced Methods in Biostatistics, II TERM 2, 2010 T. A. Louis. BIO 752: MIDTERM EXAMINATION: ANSWERS 30 November 2010

BIO752: Advanced Methods in Biostatistics, II TERM 2, 2010 T. A. Louis. BIO 752: MIDTERM EXAMINATION: ANSWERS 30 November 2010 BIO752: Advaced Methds i Bistatistics, II TERM 2, 2010 T. A. Luis BIO 752: MIDTERM EXAMINATION: ANSWERS 30 Nvember 2010 Questi #1 (15 pits): Let X ad Y be radm variables with a jit distributi ad assume

More information

Quantum Mechanics for Scientists and Engineers. David Miller

Quantum Mechanics for Scientists and Engineers. David Miller Quatum Mechaics fr Scietists ad Egieers David Miller Time-depedet perturbati thery Time-depedet perturbati thery Time-depedet perturbati basics Time-depedet perturbati thery Fr time-depedet prblems csider

More information

5.80 Small-Molecule Spectroscopy and Dynamics

5.80 Small-Molecule Spectroscopy and Dynamics MIT OpeCurseWare http://cw.mit.edu 5.8 Small-Mlecule Spectrscpy ad Dyamics Fall 8 Fr ifrmati abut citig these materials r ur Terms f Use, visit: http://cw.mit.edu/terms. 5.8 Lecture #33 Fall, 8 Page f

More information

A Study on Estimation of Lifetime Distribution with Covariates Under Misspecification

A Study on Estimation of Lifetime Distribution with Covariates Under Misspecification Prceedigs f the Wrld Cgress Egieerig ad Cmputer Sciece 2015 Vl II, Octber 21-23, 2015, Sa Fracisc, USA A Study Estimati f Lifetime Distributi with Cvariates Uder Misspecificati Masahir Ykyama, Member,

More information

Fourier Method for Solving Transportation. Problems with Mixed Constraints

Fourier Method for Solving Transportation. Problems with Mixed Constraints It. J. Ctemp. Math. Scieces, Vl. 5, 200,. 28, 385-395 Furier Methd fr Slvig Trasprtati Prblems with Mixed Cstraits P. Padia ad G. Nataraja Departmet f Mathematics, Schl f Advaced Scieces V I T Uiversity,

More information

Study of Energy Eigenvalues of Three Dimensional. Quantum Wires with Variable Cross Section

Study of Energy Eigenvalues of Three Dimensional. Quantum Wires with Variable Cross Section Adv. Studies Ther. Phys. Vl. 3 009. 5 3-0 Study f Eergy Eigevalues f Three Dimesial Quatum Wires with Variale Crss Secti M.. Sltai Erde Msa Departmet f physics Islamic Aad Uiversity Share-ey rach Ira alrevahidi@yah.cm

More information

K [f(t)] 2 [ (st) /2 K A GENERALIZED MEIJER TRANSFORMATION. Ku(z) ()x) t -)-I e. K(z) r( + ) () (t 2 I) -1/2 e -zt dt, G. L. N. RAO L.

K [f(t)] 2 [ (st) /2 K A GENERALIZED MEIJER TRANSFORMATION. Ku(z) ()x) t -)-I e. K(z) r( + ) () (t 2 I) -1/2 e -zt dt, G. L. N. RAO L. Iterat. J. Math. & Math. Scl. Vl. 8 N. 2 (1985) 359-365 359 A GENERALIZED MEIJER TRANSFORMATION G. L. N. RAO Departmet f Mathematics Jamshedpur C-perative Cllege f the Rachi Uiversity Jamshedpur, Idia

More information

Design and Implementation of Cosine Transforms Employing a CORDIC Processor

Design and Implementation of Cosine Transforms Employing a CORDIC Processor C16 1 Desig ad Implemetati f Csie Trasfrms Emplyig a CORDIC Prcessr Sharaf El-Di El-Nahas, Ammar Mttie Al Hsaiy, Magdy M. Saeb Arab Academy fr Sciece ad Techlgy, Schl f Egieerig, Alexadria, EGYPT ABSTRACT

More information

Lecture 21: Signal Subspaces and Sparsity

Lecture 21: Signal Subspaces and Sparsity ECE 830 Fall 00 Statistical Sigal Prcessig istructr: R. Nwak Lecture : Sigal Subspaces ad Sparsity Sigal Subspaces ad Sparsity Recall the classical liear sigal mdel: X = H + w, w N(0, where S = H, is a

More information

Frequency-Domain Study of Lock Range of Injection-Locked Non- Harmonic Oscillators

Frequency-Domain Study of Lock Range of Injection-Locked Non- Harmonic Oscillators 0 teratial Cferece mage Visi ad Cmputig CVC 0 PCST vl. 50 0 0 ACST Press Sigapre DO: 0.776/PCST.0.V50.6 Frequecy-Dmai Study f Lck Rage f jecti-lcked N- armic Oscillatrs Yushi Zhu ad Fei Yua Departmet f

More information

MODIFIED LEAKY DELAYED LMS ALGORITHM FOR IMPERFECT ESTIMATE SYSTEM DELAY

MODIFIED LEAKY DELAYED LMS ALGORITHM FOR IMPERFECT ESTIMATE SYSTEM DELAY 5th Eurpea Sigal Prcessig Cferece (EUSIPCO 7), Pza, Plad, September 3-7, 7, cpyright by EURASIP MOIFIE LEAKY ELAYE LMS ALGORIHM FOR IMPERFEC ESIMAE SYSEM ELAY Jua R. V. López, Orlad J. bias, ad Rui Seara

More information

Solutions. Definitions pertaining to solutions

Solutions. Definitions pertaining to solutions Slutis Defiitis pertaiig t slutis Slute is the substace that is disslved. It is usually preset i the smaller amut. Slvet is the substace that des the disslvig. It is usually preset i the larger amut. Slubility

More information

ACTIVE FILTERS EXPERIMENT 2 (EXPERIMENTAL)

ACTIVE FILTERS EXPERIMENT 2 (EXPERIMENTAL) EXPERIMENT ATIVE FILTERS (EXPERIMENTAL) OBJETIVE T desig secd-rder lw pass ilters usig the Salle & Key (iite psitive- gai) ad iiite-gai apliier dels. Oe circuit will exhibit a Butterwrth respse ad the

More information

Mean residual life of coherent systems consisting of multiple types of dependent components

Mean residual life of coherent systems consisting of multiple types of dependent components Mea residual life f cheret systems csistig f multiple types f depedet cmpets Serka Eryilmaz, Frak P.A. Cle y ad Tahai Cle-Maturi z February 20, 208 Abstract Mea residual life is a useful dyamic characteristic

More information

Preliminary Test Single Stage Shrinkage Estimator for the Scale Parameter of Gamma Distribution

Preliminary Test Single Stage Shrinkage Estimator for the Scale Parameter of Gamma Distribution America Jural f Mathematics ad Statistics, (3): 3-3 DOI:.593/j.ajms.3. Prelimiary Test Sigle Stage Shrikage Estimatr fr the Scale Parameter f Gamma Distributi Abbas Najim Salma,*, Aseel Hussei Ali, Mua

More information

Sound Absorption Characteristics of Membrane- Based Sound Absorbers

Sound Absorption Characteristics of Membrane- Based Sound Absorbers Purdue e-pubs Publicatis f the Ray W. Schl f Mechaical Egieerig 8-28-2003 Sud Absrpti Characteristics f Membrae- Based Sud Absrbers J Stuart Blt, blt@purdue.edu Jih Sg Fllw this ad additial wrks at: http://dcs.lib.purdue.edu/herrick

More information

Software Designs Of Image Processing Tasks With Incremental Refinement Of Computation

Software Designs Of Image Processing Tasks With Incremental Refinement Of Computation IEEE Trasactis Image Prcessig, t appear i 21 1 Sftware Desigs Of Image Prcessig Tasks With Icremetal Refiemet Of Cmputati Davide Aastasia ad Yiais Adrepuls * ABSTRACT Sftware realizatis f cmputatially-demadig

More information

Christensen, Mads Græsbøll; Vera-Candeas, Pedro; Somasundaram, Samuel D.; Jakobsson, Andreas

Christensen, Mads Græsbøll; Vera-Candeas, Pedro; Somasundaram, Samuel D.; Jakobsson, Andreas Dwladed frm vb.aau.dk : April 12, 2019 Aalbrg Uiversitet Rbust Subspace-based Fudametal Frequecy Estimati Christese, Mads Græsbøll; Vera-Cadeas, Pedr; Smasudaram, Samuel D.; Jakbss, Adreas Published i:

More information

Super-efficiency Models, Part II

Super-efficiency Models, Part II Super-efficiec Mdels, Part II Emilia Niskae The 4th f Nvember S steemiaalsi Ctets. Etesis t Variable Returs-t-Scale (0.4) S steemiaalsi Radial Super-efficiec Case Prblems with Radial Super-efficiec Case

More information

University of Bristol - Explore Bristol Research. Peer reviewed version. Link to publication record in Explore Bristol Research PDF-document

University of Bristol - Explore Bristol Research. Peer reviewed version. Link to publication record in Explore Bristol Research PDF-document Pieccki, RJ, Adrieu, C, Nix, AR, & McGeea, JP (3) Jit blid ad semi-blid detecti ad cael estimati fr space-time trellis cded systems IEEE Iteratial Cferece Acustics, Speec, ad Sigal Prcessig, 3 (ICASSP

More information

Grade 3 Mathematics Course Syllabus Prince George s County Public Schools

Grade 3 Mathematics Course Syllabus Prince George s County Public Schools Ctet Grade 3 Mathematics Curse Syllabus Price Gerge s Cuty Public Schls Prerequisites: Ne Curse Descripti: I Grade 3, istructial time shuld fcus fur critical areas: (1) develpig uderstadig f multiplicati

More information

Comparative analysis of bayesian control chart estimation and conventional multivariate control chart

Comparative analysis of bayesian control chart estimation and conventional multivariate control chart America Jural f Theretical ad Applied Statistics 3; ( : 7- ublished lie Jauary, 3 (http://www.sciecepublishiggrup.cm//atas di:.648/.atas.3. Cmparative aalysis f bayesia ctrl chart estimati ad cvetial multivariate

More information

Cold mirror based on High-Low-High refractive index dielectric materials

Cold mirror based on High-Low-High refractive index dielectric materials Cld mirrr based High-Lw-High refractive idex dielectric materials V.V. Elyuti.A. Butt S.N. Khia Samara Natial Research Uiversity 34 skvske Shsse 443086 Samara Russia Image Prcessig Systems Istitute Brach

More information

MATH Midterm Examination Victor Matveev October 26, 2016

MATH Midterm Examination Victor Matveev October 26, 2016 MATH 33- Midterm Examiati Victr Matveev Octber 6, 6. (5pts, mi) Suppse f(x) equals si x the iterval < x < (=), ad is a eve peridic extesi f this fucti t the rest f the real lie. Fid the csie series fr

More information

Claude Elysée Lobry Université de Nice, Faculté des Sciences, parc Valrose, NICE, France.

Claude Elysée Lobry Université de Nice, Faculté des Sciences, parc Valrose, NICE, France. CHAOS AND CELLULAR AUTOMATA Claude Elysée Lbry Uiversité de Nice, Faculté des Scieces, parc Valrse, 06000 NICE, Frace. Keywrds: Chas, bifurcati, cellularautmata, cmputersimulatis, dyamical system, ifectius

More information

A Hartree-Fock Calculation of the Water Molecule

A Hartree-Fock Calculation of the Water Molecule Chemistry 460 Fall 2017 Dr. Jea M. Stadard Nvember 29, 2017 A Hartree-Fck Calculati f the Water Mlecule Itrducti A example Hartree-Fck calculati f the water mlecule will be preseted. I this case, the water

More information

Physical Chemistry Laboratory I CHEM 445 Experiment 2 Partial Molar Volume (Revised, 01/13/03)

Physical Chemistry Laboratory I CHEM 445 Experiment 2 Partial Molar Volume (Revised, 01/13/03) Physical Chemistry Labratry I CHEM 445 Experimet Partial Mlar lume (Revised, 0/3/03) lume is, t a gd apprximati, a additive prperty. Certaily this apprximati is used i preparig slutis whse ccetratis are

More information

ELEG 635 Digital Communication Theory. Lecture 11

ELEG 635 Digital Communication Theory. Lecture 11 EEG 635 Digital Cmmuiati Thery eture 11 110801 Ageda Carrier Syhrizati Phase k p (P) Deisi Direted ps N-Deisi Direted ps Timig Syhrizati Deisi Direted ps N-Deisi Direted ps frmati Thery Sha's aw iear Blk

More information

, the random variable. and a sample size over the y-values 0:1:10.

, the random variable. and a sample size over the y-values 0:1:10. Lecture 3 (4//9) 000 HW PROBLEM 3(5pts) The estimatr i (c) f PROBLEM, p 000, where { } ~ iid bimial(,, is 000 e f the mst ppular statistics It is the estimatr f the ppulati prprti I PROBLEM we used simulatis

More information

UNIVERSITY OF TECHNOLOGY. Department of Mathematics PROBABILITY THEORY, STATISTICS AND OPERATIONS RESEARCH GROUP. Memorandum COSOR 76-10

UNIVERSITY OF TECHNOLOGY. Department of Mathematics PROBABILITY THEORY, STATISTICS AND OPERATIONS RESEARCH GROUP. Memorandum COSOR 76-10 EI~~HOVEN UNIVERSITY OF TECHNOLOGY Departmet f Mathematics PROBABILITY THEORY, STATISTICS AND OPERATIONS RESEARCH GROUP Memradum COSOR 76-10 O a class f embedded Markv prcesses ad recurrece by F.H. Sims

More information

Matching a Distribution by Matching Quantiles Estimation

Matching a Distribution by Matching Quantiles Estimation Jural f the America Statistical Assciati ISSN: 0162-1459 (Prit) 1537-274X (Olie) Jural hmepage: http://www.tadflie.cm/li/uasa20 Matchig a Distributi by Matchig Quatiles Estimati Niklas Sgurpuls, Qiwei

More information

Copyright 1978, by the author(s). All rights reserved.

Copyright 1978, by the author(s). All rights reserved. Cpyright 1978, by the authr(s). All rights reserved. Permissi t make digital r hard cpies f all r part f this wrk fr persal r classrm use is grated withut fee prvided that cpies are t made r distributed

More information

ANALOG FILTERS. C. Sauriol. Algonquin College Ottawa, Ontario

ANALOG FILTERS. C. Sauriol. Algonquin College Ottawa, Ontario LOG ILT By. auril lgqui llege Ottawa, Otari ev. March 4, 003 TBL O OTT alg ilters TIO PI ILT. irst-rder lw-pass filter- -4. irst-rder high-pass filter- 4-6 3. ecd-rder lw-pass filter- 6-4. ecd-rder bad-pass

More information

[1 & α(t & T 1. ' ρ 1

[1 & α(t & T 1. ' ρ 1 NAME 89.304 - IGNEOUS & METAMORPHIC PETROLOGY DENSITY & VISCOSITY OF MAGMAS I. Desity The desity (mass/vlume) f a magma is a imprtat parameter which plays a rle i a umber f aspects f magma behavir ad evluti.

More information

Study in Cylindrical Coordinates of the Heat Transfer Through a Tow Material-Thermal Impedance

Study in Cylindrical Coordinates of the Heat Transfer Through a Tow Material-Thermal Impedance Research ural f Applied Scieces, Egieerig ad echlgy (): 9-63, 3 ISSN: 4-749; e-issn: 4-7467 Maxwell Scietific Orgaiati, 3 Submitted: uly 4, Accepted: September 8, Published: May, 3 Study i Cylidrical Crdiates

More information

AP Statistics Notes Unit Eight: Introduction to Inference

AP Statistics Notes Unit Eight: Introduction to Inference AP Statistics Ntes Uit Eight: Itrducti t Iferece Syllabus Objectives: 4.1 The studet will estimate ppulati parameters ad margis f errrs fr meas. 4.2 The studet will discuss the prperties f pit estimatrs,

More information

ALE 26. Equilibria for Cell Reactions. What happens to the cell potential as the reaction proceeds over time?

ALE 26. Equilibria for Cell Reactions. What happens to the cell potential as the reaction proceeds over time? Name Chem 163 Secti: Team Number: AL 26. quilibria fr Cell Reactis (Referece: 21.4 Silberberg 5 th editi) What happes t the ptetial as the reacti prceeds ver time? The Mdel: Basis fr the Nerst quati Previusly,

More information

Strathprints Institutional Repository

Strathprints Institutional Repository Strathprits Istitutial Repsitry Hussi, Mhammed Nuri ad Weiss, Stepha (2011) Chael estimati ad trackig fr clsed lp EO-STBC with differetially ecdig feedback. I: 11th IEEE Iteratial Sympsium Sigal Prcessig

More information

Unifying the Derivations for. the Akaike and Corrected Akaike. Information Criteria. from Statistics & Probability Letters,

Unifying the Derivations for. the Akaike and Corrected Akaike. Information Criteria. from Statistics & Probability Letters, Uifyig the Derivatis fr the Akaike ad Crrected Akaike Ifrmati Criteria frm Statistics & Prbability Letters, Vlume 33, 1997, pages 201{208. by Jseph E. Cavaaugh Departmet f Statistics, Uiversity f Missuri,

More information

On the affine nonlinearity in circuit theory

On the affine nonlinearity in circuit theory O the affie liearity i circuit thery Emauel Gluski The Kieret Cllege the Sea f Galilee; ad Ort Braude Cllege (Carmiel), Israel. gluski@ee.bgu.ac.il; http://www.ee.bgu.ac.il/~gluski/ E. Gluski, O the affie

More information

Filter banks. Separately, the lowpass and highpass filters are not invertible. removes the highest frequency 1/ 2and

Filter banks. Separately, the lowpass and highpass filters are not invertible. removes the highest frequency 1/ 2and Filter bas Separately, the lowpass ad highpass filters are ot ivertible T removes the highest frequecy / ad removes the lowest frequecy Together these filters separate the sigal ito low-frequecy ad high-frequecy

More information

Partial-Sum Queries in OLAP Data Cubes Using Covering Codes

Partial-Sum Queries in OLAP Data Cubes Using Covering Codes 326 IEEE TRANSACTIONS ON COMPUTERS, VOL. 47, NO. 2, DECEMBER 998 Partial-Sum Queries i OLAP Data Cubes Usig Cverig Cdes Chig-Tie H, Member, IEEE, Jehshua Bruck, Seir Member, IEEE, ad Rakesh Agrawal, Seir

More information

Bayesian Estimation for Continuous-Time Sparse Stochastic Processes

Bayesian Estimation for Continuous-Time Sparse Stochastic Processes Bayesia Estimati fr Ctiuus-Time Sparse Stchastic Prcesses Arash Amii, Ulugbek S Kamilv, Studet, IEEE, Emrah Bsta, Studet, IEEE, Michael User, Fellw, IEEE Abstract We csider ctiuus-time sparse stchastic

More information

A NEW METHOD OF THRUSTER CONTROL IN POSITIONING OF SHIPS BASED ON POWER CONTROL

A NEW METHOD OF THRUSTER CONTROL IN POSITIONING OF SHIPS BASED ON POWER CONTROL A NEW METHOD O THRUSTER CONTROL IN POSITIONING O SHIPS BASED ON POWER CONTROL Asgeir J. Sørese*, Alf Kåre Ådaes*, Thr I. sse** ad Ja-Peter Strad** *ABB Idustri AS, Hasleveie 50, P. O. Bx 6540 Rdeløkka,

More information

FREQUENCY DOMAIN BLIND DECONVOLUTION IN MULTIFRAME IMAGING USING ANISOTROPIC SPATIALLY-ADAPTIVE DENOISING

FREQUENCY DOMAIN BLIND DECONVOLUTION IN MULTIFRAME IMAGING USING ANISOTROPIC SPATIALLY-ADAPTIVE DENOISING FREQUENCY DOMAIN BLIND DECONVOLUTION IN MULTIFRAME IMAGING USING ANISOTROIC SATIALLY-ADATIVE DENOISING Vladimir Katkvik, Dmitriy aliy, Kare Egiazaria, ad Jaakk Astla Istitute Sigal rcessig, Tampere Uiversity

More information

n i y W TEQ x i delay TIR

n i y W TEQ x i delay TIR Kathlieke Uiversiteit Leuve Departemet Elektrtechiek ESA-SISA/R - A imprved ptimizati algrithm fr time dmai equalizer desig i ADSL mdems Katlee Va Acker, Geert Leus, Marc Me, Sta Claes, livier va de Wiel

More information

Recovery of Third Order Tensors via Convex Optimization

Recovery of Third Order Tensors via Convex Optimization Recvery f Third Order Tesrs via Cvex Optimizati Hlger Rauhut RWTH Aache Uiversity Lehrstuhl C für Mathematik (Aalysis) Ptdriesch 10 5056 Aache Germay Email: rauhut@mathcrwth-aachede Željka Stjaac RWTH

More information

Rates and Mechanisms of Chemical Reactions

Rates and Mechanisms of Chemical Reactions Rates ad Mechaisms f Chemical Reactis Why sme rxs prceed very fast ad thers require days, mths r eve years t prduce a detectable amt f prduct? H (g) + F (g) HF (g) (very fast) 3 H (g) + N (g) NH 3 (g)

More information

Module 5 EMBEDDED WAVELET CODING. Version 2 ECE IIT, Kharagpur

Module 5 EMBEDDED WAVELET CODING. Version 2 ECE IIT, Kharagpur Module 5 EMBEDDED WAVELET CODING Versio ECE IIT, Kharagpur Lesso 4 SPIHT algorithm Versio ECE IIT, Kharagpur Istructioal Objectives At the ed of this lesso, the studets should be able to:. State the limitatios

More information

WEST VIRGINIA UNIVERSITY

WEST VIRGINIA UNIVERSITY WEST VIRGINIA UNIVERSITY PLASMA PHYSICS GROUP INTERNAL REPORT PL - 045 Mea Optical epth ad Optical Escape Factr fr Helium Trasitis i Helic Plasmas R.F. Bivi Nvember 000 Revised March 00 TABLE OF CONTENT.0

More information

, which yields. where z1. and z2

, which yields. where z1. and z2 The Gaussian r Nrmal PDF, Page 1 The Gaussian r Nrmal Prbability Density Functin Authr: Jhn M Cimbala, Penn State University Latest revisin: 11 September 13 The Gaussian r Nrmal Prbability Density Functin

More information

MATHEMATICS 9740/01 Paper 1 14 Sep hours

MATHEMATICS 9740/01 Paper 1 14 Sep hours Cadidate Name: Class: JC PRELIMINARY EXAM Higher MATHEMATICS 9740/0 Paper 4 Sep 06 3 hurs Additial Materials: Cver page Aswer papers List f Frmulae (MF5) READ THESE INSTRUCTIONS FIRST Write yur full ame

More information

Aligning Anatomy Ontologies in the Ontology Alignment Evaluation Initiative

Aligning Anatomy Ontologies in the Ontology Alignment Evaluation Initiative Aligig Aatmy Otlgies i the Otlgy Aligmet Evaluati Iitiative Patrick Lambrix, Qiag Liu, He Ta Departmet f Cmputer ad Ifrmati Sciece Liköpigs uiversitet 581 83 Liköpig, Swede Abstract I recet years may tlgies

More information

The Acoustical Physics of a Standing Wave Tube

The Acoustical Physics of a Standing Wave Tube UIUC Physics 93POM/Physics 406POM The Physics f Music/Physics f Musical Istrumets The Acustical Physics f a Stadig Wave Tube A typical cylidrical-shaped stadig wave tube (SWT) {aa impedace tube} f legth

More information

Physical Layer: Outline

Physical Layer: Outline 18-: Intrductin t Telecmmunicatin Netwrks Lectures : Physical Layer Peter Steenkiste Spring 01 www.cs.cmu.edu/~prs/nets-ece Physical Layer: Outline Digital Representatin f Infrmatin Characterizatin f Cmmunicatin

More information

are specified , are linearly independent Otherwise, they are linearly dependent, and one is expressed by a linear combination of the others

are specified , are linearly independent Otherwise, they are linearly dependent, and one is expressed by a linear combination of the others Chater 3. Higher Order Liear ODEs Kreyszig by YHLee;4; 3-3. Hmgeeus Liear ODEs The stadard frm f the th rder liear ODE ( ) ( ) = : hmgeeus if r( ) = y y y y r Hmgeeus Liear ODE: Suersiti Pricile, Geeral

More information

Dynamic Response of Second Order Mechanical Systems with Viscous Dissipation forces

Dynamic Response of Second Order Mechanical Systems with Viscous Dissipation forces Hadut #a (pp. 1-39) Dyamic Respse f Secd Order Mechaical Systems with Viscus Dissipati frces d X d X + + = ext() t M D K X F dt dt Free Respse t iitial cditis ad F (t) = 0, Uderdamped, Critically Damped

More information

Abstract: The asympttically ptimal hypthesis testig prblem with the geeral surces as the ull ad alterative hyptheses is studied uder expetial-type err

Abstract: The asympttically ptimal hypthesis testig prblem with the geeral surces as the ull ad alterative hyptheses is studied uder expetial-type err Hypthesis Testig with the Geeral Surce y Te Su HAN z April 26, 2000 y This paper is a exteded ad revised versi f Sectis 4.4 4.7 i Chapter 4 f the Japaese bk f Ha [8]. z Te Su Ha is with the Graduate Schl

More information

A unified brittle fracture criterion for structures with sharp V-notches under mixed mode loading

A unified brittle fracture criterion for structures with sharp V-notches under mixed mode loading Jural f Mechaical Sciece ad Techlgy Jural f Mechaical Sciece ad Techlgy 22 (2008) 269~278 www.sprigerlik.cm/ctet/738-494x A uified brittle fracture criteri fr structures with sharp V-tches uder mixed mde

More information

Seismic Performance of Symmetrical and Asymmetrical Buildings with Heavy Loads

Seismic Performance of Symmetrical and Asymmetrical Buildings with Heavy Loads Seismic Perfrmace f Symmetrical ad al Buildigs with Heavy Lads Md. Jaweed Jilai Kha, Seshadri Sekhar ad Bellam Sivarama Krisha Prasad esearch Schlar, Departmet f Civil gieerig esearch, Gitam Uiversity,

More information

ADVANCED DIGITAL SIGNAL PROCESSING

ADVANCED DIGITAL SIGNAL PROCESSING ADVANCED DIGITAL SIGNAL PROCESSING PROF. S. C. CHAN (email : sccha@eee.hku.hk, Rm. CYC-702) DISCRETE-TIME SIGNALS AND SYSTEMS MULTI-DIMENSIONAL SIGNALS AND SYSTEMS RANDOM PROCESSES AND APPLICATIONS ADAPTIVE

More information

THE MATRIX VERSION FOR THE MULTIVARIABLE HUMBERT POLYNOMIALS

THE MATRIX VERSION FOR THE MULTIVARIABLE HUMBERT POLYNOMIALS Misklc Mathematical Ntes HU ISSN 1787-2405 Vl. 13 (2012), N. 2, pp. 197 208 THE MATRI VERSION FOR THE MULTIVARIABLE HUMBERT POLYNOMIALS RABİA AKTAŞ, BAYRAM ÇEKIM, AN RECEP ŞAHI Received 4 May, 2011 Abstract.

More information

ESWW-2. Israeli semi-underground great plastic scintillation multidirectional muon telescope (ISRAMUTE) for space weather monitoring and forecasting

ESWW-2. Israeli semi-underground great plastic scintillation multidirectional muon telescope (ISRAMUTE) for space weather monitoring and forecasting ESWW-2 Israeli semi-udergrud great plastic scitillati multidirectial mu telescpe (ISRAMUTE) fr space weather mitrig ad frecastig L.I. Drma a,b, L.A. Pustil'ik a, A. Sterlieb a, I.G. Zukerma a (a) Israel

More information

COWLES FOUNDATION FOR RESEARCH IN ECONOMICS YALE UNIVERSITY

COWLES FOUNDATION FOR RESEARCH IN ECONOMICS YALE UNIVERSITY HAC ESTIMATION BY AUTOMATED REGRESSION By Peter C.B. Phillips July 004 COWLES FOUNDATION DISCUSSION PAPER NO. 470 COWLES FOUNDATION FOR RESEARCH IN ECONOMICS YALE UNIVERSITY Bx 088 New Have, Cecticut 0650-88

More information

Spatio-temporal Modeling of Environmental Data for Epidemiologic Health Effects Analyses

Spatio-temporal Modeling of Environmental Data for Epidemiologic Health Effects Analyses Spati-tempral Mdelig f Evirmetal Data fr Epidemilgic Health Effects Aalyses Paul D. Samps Uiversity f Washigt Air Quality ad Health: a glbal issue with lcal challeges 8 Aug 2017 -- Mexic City 1 The MESA

More information

Multiresolution coding and wavelets. Interpolation error coding, I

Multiresolution coding and wavelets. Interpolation error coding, I Multiresolutio codig ad wavelets Predictive (closed-loop) pyramids Ope-loop ( Laplacia ) pyramids Discrete Wavelet Trasform (DWT) Quadrature mirror filters ad cojugate quadrature filters Liftig ad reversible

More information

This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and

This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and This article appeared i a jural published by Elsevier The attached cpy is furished t the authr fr iteral -cmmercial research ad educati use, icludig fr istructi at the authrs istituti ad sharig with clleagues

More information

x 2 x 3 x b 0, then a, b, c log x 1 log z log x log y 1 logb log a dy 4. dx As tangent is perpendicular to the x axis, slope

x 2 x 3 x b 0, then a, b, c log x 1 log z log x log y 1 logb log a dy 4. dx As tangent is perpendicular to the x axis, slope The agle betwee the tagets draw t the parabla y = frm the pit (-,) 5 9 6 Here give pit lies the directri, hece the agle betwee the tagets frm that pit right agle Ratig :EASY The umber f values f c such

More information

The Complexity of Translation Membership for Macro Tree Transducers

The Complexity of Translation Membership for Macro Tree Transducers The Cmplexity f Traslati Membership fr Macr Tree Trasducers Kazuhir Iaba The Uiversity f Tky kiaba@is.s.u-tky.ac.jp Sebastia Maeth NICTA ad Uiversity f New Suth Wales sebastia.maeth@icta.cm.au ABSTRACT

More information

Chapter 5. Root Locus Techniques

Chapter 5. Root Locus Techniques Chapter 5 Rt Lcu Techique Itrducti Sytem perfrmace ad tability dt determied dby cled-lp l ple Typical cled-lp feedback ctrl ytem G Ope-lp TF KG H Zer -, - Ple 0, -, - K Lcati f ple eaily fud Variati f

More information

An Investigation of Stratified Jackknife Estimators Using Simulated Establishment Data Under an Unequal Probability Sample Design

An Investigation of Stratified Jackknife Estimators Using Simulated Establishment Data Under an Unequal Probability Sample Design Secti Survey Research Methds SM 9 A Ivestigati f Stratified ackkife Estimatrs Usig Simulated Establishmet Data Uder a Uequal Prbability Sample Desig Abstract Plip Steel, Victria McNerey, h Slata Csiderig

More information

Portfolio Performance Evaluation in a Modified Mean-Variance-Skewness Framework with Negative Data

Portfolio Performance Evaluation in a Modified Mean-Variance-Skewness Framework with Negative Data Available lie at http://idea.srbiau.ac.ir It. J. Data Evelpmet Aalysis (ISSN 345-458X) Vl., N.3, Year 04 Article ID IJDEA-003,3 pages Research Article Iteratial Jural f Data Evelpmet Aalysis Sciece ad

More information

Analysis of a Positive Output Super-Lift Luo Boost Converter

Analysis of a Positive Output Super-Lift Luo Boost Converter Ausha eade et al. t. Jural f Egeerg esearch ad Applicats SSN: 8-96, l. 6, ssue, (Part - 5) February 06, pp.7-78 ESEACH ACE www.ijera.cm OPEN ACCESS Aalys f a Psitive Output Super-ift u Bst Cverter Ausha

More information

Thermodynamic study of CdCl 2 in 2-propanol (5 mass %) + water mixture using potentiometry

Thermodynamic study of CdCl 2 in 2-propanol (5 mass %) + water mixture using potentiometry Thermdyamic study f CdCl 2 i 2-prpal (5 mass %) + water mixture usig ptetimetry Reat Tmaš, Ađelka Vrdljak UDC: 544.632.4 Uiversity f Split, Faculty f Chemistry ad Techlgy, Teslia 10/V, HR-21000 Split,

More information

EE260: Digital Design, Spring n Binary Addition. n Complement forms. n Subtraction. n Multiplication. n Inputs: A 0, B 0. n Boolean equations:

EE260: Digital Design, Spring n Binary Addition. n Complement forms. n Subtraction. n Multiplication. n Inputs: A 0, B 0. n Boolean equations: EE260: Digital Desig, Sprig 2018 EE 260: Itroductio to Digital Desig Arithmetic Biary Additio Complemet forms Subtractio Multiplicatio Overview Yao Zheg Departmet of Electrical Egieerig Uiversity of Hawaiʻi

More information

E o and the equilibrium constant, K

E o and the equilibrium constant, K lectrchemical measuremets (Ch -5 t 6). T state the relati betwee ad K. (D x -b, -). Frm galvaic cell vltage measuremet (a) K sp (D xercise -8, -) (b) K sp ad γ (D xercise -9) (c) K a (D xercise -G, -6)

More information

Application Of Mealy Machine And Recurrence Relations In Cryptography

Application Of Mealy Machine And Recurrence Relations In Cryptography Applicatin Of Mealy Machine And Recurrence Relatins In Cryptgraphy P. A. Jytirmie 1, A. Chandra Sekhar 2, S. Uma Devi 3 1 Department f Engineering Mathematics, Andhra University, Visakhapatnam, IDIA 2

More information

NUROP CONGRESS PAPER CHINESE PINYIN TO CHINESE CHARACTER CONVERSION

NUROP CONGRESS PAPER CHINESE PINYIN TO CHINESE CHARACTER CONVERSION NUROP Chinese Pinyin T Chinese Character Cnversin NUROP CONGRESS PAPER CHINESE PINYIN TO CHINESE CHARACTER CONVERSION CHIA LI SHI 1 AND LUA KIM TENG 2 Schl f Cmputing, Natinal University f Singapre 3 Science

More information

ELEG 635 Digital Communication Theory. Lecture 10

ELEG 635 Digital Communication Theory. Lecture 10 ELEG 635 Digital Cmmuiati hery Leture Ergdi Radm Presses CPM reeiver Sigal Parameter Estimati Carrier Syhrizati Ageda Ergdi Radm Presses - A radm press is said t be ergdi if time averagig is equivalet

More information

The generation of successive approximation methods for Markov decision processes by using stopping times

The generation of successive approximation methods for Markov decision processes by using stopping times The geerati f successive apprximati methds fr Markv decisi prcesses by usig stppig times Citati fr published versi (APA): va Nue, J. A. E. E., & Wessels, J. (1976). The geerati f successive apprximati

More information

Signals & Systems Chapter3

Signals & Systems Chapter3 Sigals & Systems Chapter3 1.2 Discrete-Time (D-T) Sigals Electroic systems do most of the processig of a sigal usig a computer. A computer ca t directly process a C-T sigal but istead eeds a stream of

More information

Distributed Trajectory Generation for Cooperative Multi-Arm Robots via Virtual Force Interactions

Distributed Trajectory Generation for Cooperative Multi-Arm Robots via Virtual Force Interactions 862 IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS PART B: CYBERNETICS, VOL. 27, NO. 5, OCTOBER 1997 Distributed Trajectry Geerati fr Cperative Multi-Arm Rbts via Virtual Frce Iteractis Tshi Tsuji,

More information

Efficient Processing of Continuous Reverse k Nearest Neighbor on Moving Objects in Road Networks

Efficient Processing of Continuous Reverse k Nearest Neighbor on Moving Objects in Road Networks Iteratial Jural f Ge-Ifrmati Article Efficiet Prcessig f Ctiuus Reverse k Nearest Neighbr Mvig Objects i Rad Netwrks Muhammad Attique, Hyug-Ju Ch, Rize Ji ad Tae-Su Chug, * Departmet f Cmputer Egieerig,

More information

k-nearest Neighbor How to choose k Average of k points more reliable when: Large k: noise in attributes +o o noise in class labels

k-nearest Neighbor How to choose k Average of k points more reliable when: Large k: noise in attributes +o o noise in class labels Mtivating Example Memry-Based Learning Instance-Based Learning K-earest eighbr Inductive Assumptin Similar inputs map t similar utputs If nt true => learning is impssible If true => learning reduces t

More information

STRUCTURES IN MIKE 21. Flow over sluice gates A-1

STRUCTURES IN MIKE 21. Flow over sluice gates A-1 A-1 STRUCTURES IN MIKE 1 Fl ver luice gate Fr a give gemetry f the luice gate ad k ater level uptream ad dtream f the tructure, the fl rate, ca be determied thrugh the equati f eergy ad mmetum - ee B Pedere,

More information

Collision and Packet Loss Analysis in a LoRaWAN Network

Collision and Packet Loss Analysis in a LoRaWAN Network 7 5th Europea Sigal Processig Cferece EUSIPCO Collisi ad Packet Loss Aalysis i a LoRaWAN Network Guillaume Ferré IMS Laboratory - Uiversity of Bordeaux - Bordeaux INP 35 cours de la libérati 334 Talece

More information