Research Article Health Monitoring for a Structure Using Its Nonstationary Vibration

Size: px
Start display at page:

Download "Research Article Health Monitoring for a Structure Using Its Nonstationary Vibration"

Transcription

1 Hidawi Publishig Corporatio Advaces i Acoustics ad Vibratio Volume 2, Article ID 69652, 5 pages doi:.55/2/69652 Research Article Health Moitorig for a Structure Usig Its Nostatioary Vibratio Yoshimutsu Hirata, Mikio Tohyama, Mitsuo Matsumoto, ad Satoru Gotoh 2 SV Research Associates, , Yuigahama 2-chome, Kamakura-shi, Kaagawa 248-4, Japa 2 Waseda Uiversity, -4 Totsukama, Shijuku-ku, Tokyo 69-85, Japa Correspodece should be addressed to Mitsuo Matsumoto, matsu desk@jcom.home.e.jp Received 26 May 2; Accepted 4 August 2 Academic Editor: K. M. Liew Copyright 2 Yoshimutsu Hirata et al. This is a ope access article distributed uder the Creative Commos Attributio Licese, which permits urestricted use, distributio, ad reproductio i ay medium, provided the origial work is properly cited. The frequecy distributio of a short iterval period, the SIP distributio, obtaied from the vibratio of a structure that is excited by the force of o-statioary vibratio is available for the robust estimatio of the dyamic property of the structure. This paper shows experimets of the health moitorig of a model structure usig the SIP distributio. Comparisos of SIP distributios with average DFT spectra are also show.. Itroductio Oe of the major problems after a earthquake, which causes certai chages i the dyamic property of a structure, is the ivestigatio of structural damage. I priciple, we ca check the chage usig a shaker to obtai the frequecy respose ofastructure.however,itisdifficult ad ot practical to shake a big structure before ad after a earthquake to detect the chage. Regardless of size or weight, all structures such as buildigs, towers, ad bridges are vibratig due to the atural force of wids, groud motios, or both. Iformatio of the dyamic property of a buildig, for example, is comprised of the forced vibratio of a structure. Chages of dyamic property reflect structural chages. The, the problem is how to extract iformatio from the vibratio of structures. It was show by oe of the authors that the frequecy distributio of a short-iterval period, the SIP distributio, of the forced ostatioary vibratio correspods to the frequecy respose of a structure []. I this paper, experimets of health moitorig of a model structure usig its ostatioary vibratios are show, where SIP distributios are used for detectig the chages of the dyamic property of a structure. 2. SIP Distributios The discrete Fourier trasform (DFT is used i may disciplies to obtai the spectrum or frequecy of a sigal. The DFT produces reasoable results for a large class of sigal processes. However, we do ot use the DFT for detectig a short iterval period because of its iheret limitatio of frequecy resolutio [2]. The domiat frequecy or period of a short-iterval sequece W(m(m =,,..., M ca be give by the oharmoic Fourier aalysis [3]. I the process of the aalysis, we put W(x = W(m, where x = m M/2, ad obtai Fourier coefficiets a( f adb( f for a arbitrary frequecy such that a ( f = b ( f = x= M/2 W(x si ( 2πfx x= M/2 si 2( 2πfx, x= M/2 W(x cos ( 2πfx x= M/2 cos 2( 2πfx. (

2 2 Advaces i Acoustics ad Vibratio SA ( f SB ( f 5 Frequecy (Hz 5 Frequecy (Hz Figure : Power frequecy resposes of model structures A ad B. S( f S( f 5 Frequecy (Hz 5 Frequecy (Hz Figure 2: Examples of the clutter average spectrum of ostatioary vibratio. Relative magitude Relative magitude Relative magitude 5 5 (c 5 (e Relative magitude Relative magitude Relative magitude 5 5 (d 5 (f Figure 3: Power frequecy respose of the model structure A estimated by the average DFT spectrum,, ad (c ad the SIP distributio, (d, ad (f. ad Statioary radom vibratio. (c (f Nostatioary vibratio. Relative frequecy is give by = f /.

3 Advaces i Acoustics ad Vibratio 3 Relative magitude Relative magitude Relative magitude 5 5 (c 5 (e Relative magitude Relative magitude Relative magitude 5 5 (d 5 (f Figure 4: Power frequecy respose of the model structure B estimated by the average DFT spectrum, (c, ad (e ad the SIP disctributio, (d, ad (e. ad Statioary radom vibratio. (c (f Nostatioary vibratio. Relative frequecy is give by = f /. Hece, if we put y ( x, f = a ( f si ( 2πfx + b ( f cos ( 2πfx, Y ( f = M/2 x= M/2 y 2( x, f, we have the domiat frequecy f p which satisfies (2 Y ( f p = the maximum of Y ( f. (3 It should be oted that we attai a least squares fit of W(x to a siusoid by y(x, f p. The SIP distributio is give by a umber of domiat frequecies (or periods of short sequeces which are fractios of measured data. Thus, the ormalized SIP distributio D( f p gives the probability of the domiat frequecy f p foudimeasureddata. If we assume that a structure is excited by the force of radom oise ad assig the frequecy f i ( such that f = f = Δ f, =, 2,..., N, (4 where Δ f</m, wehave,from[], D ( f j D ( f i = Qij (r S( f j S ( f i S ( (, (5 f j + S fi where < Q ij (r < ads( f j is the power frequecy respose of a structure at a frequecy f j ad so o. Hece, we get a approximatio S ( f kd ( f, (6 where k is a appropriate costat. It should be metioed that the spectral resolutio give by D( f depeds little o the legth of the short sequece whe Mf >. 3. Experimet To cofirm the theoretical result show by (6 ad apply the SIP distributio to the health moitorig of a structure, experimets were made usig a model structure. A model structure is a woode framework (8(W 22(D 27(Hcm which simulates a three-storied buildig with four struts. The stregth of this model structure (the model structure A is chaged by alterig the struts, that is, the cross-sectio

4 4 Advaces i Acoustics ad Vibratio DFT spectrum SIP distributio 2 5 DFT spectrum 2 5 SIP distributio 2 5 (c 2 5 (d Figure 5: Illustratio of the health-moitorig of a structure by the DFT spectrum ad the SIP distributio for radom oise excitatio, ad ostatioary oise excitatio (c, (d. area of struts has a 25-percet decrease. This chaged model structure (a model structure B is assumed to be the damaged structure of the model A. The frequecy resposes of the model structures A ad B, which are difficult to measure i real cases, are show i Figure, where the power frequecy respose S A ( f ad S B ( f are show withi the observatio bad. The force of statioary radom vibratio as well as ostatioary oe was applied to excite a model structure, ad the acceleratio of the structure was measured at the fixed poit of the frame. The measured data were provided for the DFT aalysis ad SIP distributio. We assume that the average spectrum of ostatioary vibratio is a clutter oe which varies slowly with time, so that we represet a ostatioary vibratio as a set of radom oise sequeces each havig a differet clutter average spectrum; see Figure 2. The measured data sequece was divided ito 2,4 short-iterval sequeces for the oharmoic Fourier aalysis to get a SIP distributio, that is, the domiat frequecy of each sequece is give by the aalysis of 6 sampled data. To compare the SIP distributio with the average of DFT spectra, the measured data sequece was also divided ito 24 sequeces, so that the DFT frequecy, f,isgiveby F/6, where F is a samplig frequecy. Correspodig to the DFT frequecy, we put the frequecy of the oharmoic Fourier aalysis (see ( such that f = f. Figure 3 shows the power frequecy respose of the model structure A estimated by the average of 24 DFT spectra ad the SIP distributio give by 2,4 domiat frequecy samples. Both estimatios are much the same whe excited by the statioary radom vibratio, see Figures 3 ad 3. Differeces arise i the case of ostatioary vibratios, see Figures 3(c 3(f. Similarly, Figure 4 shows estimatios of the power frequecy respose of the model structure B. We see that the SIP distributio is stable comparig with the DFT spectrum. Figure 5 shows the illustratio of the health-moitorig of a structure usig its ostatioary vibratio, where the model structure A chages gradually from time ad comes to the structure B at time 2. The DFT spectrum Figure 5 ad the SIP distributio Figure 5 show the same chage for radom oise excitatio. The differece of the both method arises whe the structure is excited by ostatioary oises Figures 5(c ad 5(d. It seems that the SIP distributio is stable comparig with the DFT spectrum. 4. Coclusios A umber of buildigs, bridges, ad towers have bee costructed i past decades. Cosequetly, there are may decrepit structures which eed to be recostructed. Oe may remember the accidet i Mieapolis, USA where thirtee persos were killed by the sudde collapse of a old bridge over the Mississippi. The health moitorig of structures is a importat mea for security agaist such a accidet. The method described i this paper might be available. Further

5 Advaces i Acoustics ad Vibratio 5 experimets usig a real bridge, for example, will cofirm the proposed method, though it will take decades. Refereces [] Y. Hirata, Estimatio of the frequecy respose of a structure usig its o-statioary vibratio, Joural of Soud ad Vibratio, vol. 33, o. 3 5, pp , 28. [2] S. M. Kay ad S. L. Marple Jr., Spectrum aalysis a moder perspective, Proceedigs of the IEEE, vol. 69, o., pp , 98. [3] Y. Hirata, No-harmoic Fourier aalysis available for detectig very low-frequecy compoets, Joural of Soud ad Vibratio, vol. 287, o. 3, pp. 6 63, 25.

Research Article Health Monitoring for a Structure Using Its Nonstationary Vibration

Research Article Health Monitoring for a Structure Using Its Nonstationary Vibration Advaces i Acoustics ad Vibratio Volume 2, Article ID 69652, 5 pages doi:.55/2/69652 Research Article Health Moitorig for a Structure Usig Its Nostatioary Vibratio Yoshimutsu Hirata, Mikio Tohyama, Mitsuo

More information

CUMULATIVE DAMAGE ESTIMATION USING WAVELET TRANSFORM OF STRUCTURAL RESPONSE

CUMULATIVE DAMAGE ESTIMATION USING WAVELET TRANSFORM OF STRUCTURAL RESPONSE CUMULATIVE DAMAGE ESTIMATION USING WAVELET TRANSFORM OF STRUCTURAL RESPONSE Ryutaro SEGAWA 1, Shizuo YAMAMOTO, Akira SONE 3 Ad Arata MASUDA 4 SUMMARY Durig a strog earthquake, the respose of a structure

More information

Spectral Analysis. This week in lab. Next classes: 3/26 and 3/28. Your next experiment Homework is to prepare

Spectral Analysis. This week in lab. Next classes: 3/26 and 3/28. Your next experiment Homework is to prepare Spectral Aalysis This week i lab Your ext experimet Homework is to prepare Next classes: 3/26 ad 3/28 Aero Testig, Fracture Toughess Testig Read the Experimets 5 ad 7 sectios of the course maual Spectral

More information

Data Analysis and Statistical Methods Statistics 651

Data Analysis and Statistical Methods Statistics 651 Data Aalysis ad Statistical Methods Statistics 651 http://www.stat.tamu.edu/~suhasii/teachig.html Suhasii Subba Rao Review of testig: Example The admistrator of a ursig home wats to do a time ad motio

More information

Double Stage Shrinkage Estimator of Two Parameters. Generalized Exponential Distribution

Double Stage Shrinkage Estimator of Two Parameters. Generalized Exponential Distribution Iteratioal Mathematical Forum, Vol., 3, o. 3, 3-53 HIKARI Ltd, www.m-hikari.com http://dx.doi.org/.9/imf.3.335 Double Stage Shrikage Estimator of Two Parameters Geeralized Expoetial Distributio Alaa M.

More information

Research Article Moment Inequality for ϕ-mixing Sequences and Its Applications

Research Article Moment Inequality for ϕ-mixing Sequences and Its Applications Hidawi Publishig Corporatio Joural of Iequalities ad Applicatios Volume 2009, Article ID 379743, 2 pages doi:0.55/2009/379743 Research Article Momet Iequality for ϕ-mixig Sequeces ad Its Applicatios Wag

More information

Research Article A Unified Weight Formula for Calculating the Sample Variance from Weighted Successive Differences

Research Article A Unified Weight Formula for Calculating the Sample Variance from Weighted Successive Differences Discrete Dyamics i Nature ad Society Article ID 210761 4 pages http://dxdoiorg/101155/2014/210761 Research Article A Uified Weight Formula for Calculatig the Sample Variace from Weighted Successive Differeces

More information

A. Basics of Discrete Fourier Transform

A. Basics of Discrete Fourier Transform A. Basics of Discrete Fourier Trasform A.1. Defiitio of Discrete Fourier Trasform (8.5) A.2. Properties of Discrete Fourier Trasform (8.6) A.3. Spectral Aalysis of Cotiuous-Time Sigals Usig Discrete Fourier

More information

Comparison Study of Series Approximation. and Convergence between Chebyshev. and Legendre Series

Comparison Study of Series Approximation. and Convergence between Chebyshev. and Legendre Series Applied Mathematical Scieces, Vol. 7, 03, o. 6, 3-337 HIKARI Ltd, www.m-hikari.com http://d.doi.org/0.988/ams.03.3430 Compariso Study of Series Approimatio ad Covergece betwee Chebyshev ad Legedre Series

More information

Research Article Approximate Riesz Algebra-Valued Derivations

Research Article Approximate Riesz Algebra-Valued Derivations Abstract ad Applied Aalysis Volume 2012, Article ID 240258, 5 pages doi:10.1155/2012/240258 Research Article Approximate Riesz Algebra-Valued Derivatios Faruk Polat Departmet of Mathematics, Faculty of

More information

Research Article A New Second-Order Iteration Method for Solving Nonlinear Equations

Research Article A New Second-Order Iteration Method for Solving Nonlinear Equations Abstract ad Applied Aalysis Volume 2013, Article ID 487062, 4 pages http://dx.doi.org/10.1155/2013/487062 Research Article A New Secod-Order Iteratio Method for Solvig Noliear Equatios Shi Mi Kag, 1 Arif

More information

Frequency Response of FIR Filters

Frequency Response of FIR Filters EEL335: Discrete-Time Sigals ad Systems. Itroductio I this set of otes, we itroduce the idea of the frequecy respose of LTI systems, ad focus specifically o the frequecy respose of FIR filters.. Steady-state

More information

Two Topics in Number Theory: Sum of Divisors of the Factorial and a Formula for Primes

Two Topics in Number Theory: Sum of Divisors of the Factorial and a Formula for Primes Iteratioal Mathematical Forum, Vol. 2, 207, o. 9, 929-935 HIKARI Ltd, www.m-hiari.com https://doi.org/0.2988/imf.207.7088 Two Topics i Number Theory: Sum of Divisors of the Factorial ad a Formula for Primes

More information

A statistical method to determine sample size to estimate characteristic value of soil parameters

A statistical method to determine sample size to estimate characteristic value of soil parameters A statistical method to determie sample size to estimate characteristic value of soil parameters Y. Hojo, B. Setiawa 2 ad M. Suzuki 3 Abstract Sample size is a importat factor to be cosidered i determiig

More information

The Sampling Distribution of the Maximum. Likelihood Estimators for the Parameters of. Beta-Binomial Distribution

The Sampling Distribution of the Maximum. Likelihood Estimators for the Parameters of. Beta-Binomial Distribution Iteratioal Mathematical Forum, Vol. 8, 2013, o. 26, 1263-1277 HIKARI Ltd, www.m-hikari.com http://d.doi.org/10.12988/imf.2013.3475 The Samplig Distributio of the Maimum Likelihood Estimators for the Parameters

More information

The Random Walk For Dummies

The Random Walk For Dummies The Radom Walk For Dummies Richard A Mote Abstract We look at the priciples goverig the oe-dimesioal discrete radom walk First we review five basic cocepts of probability theory The we cosider the Beroulli

More information

PROPOSING INPUT-DEPENDENT MODE CONTRIBUTION FACTORS FOR SIMPLIFIED SEISMIC RESPONSE ANALYSIS OF BUILDING SYSTEMS

PROPOSING INPUT-DEPENDENT MODE CONTRIBUTION FACTORS FOR SIMPLIFIED SEISMIC RESPONSE ANALYSIS OF BUILDING SYSTEMS he 4 th World Coferece o Earthquake Egieerig October -7, 008, Beiig, Chia PROPOSING INPU-DEPENDEN ODE CONRIBUION FACORS FOR SIPLIFIED SEISIC RESPONSE ANALYSIS OF BUILDING SYSES ahmood Hosseii ad Laya Abbasi

More information

Chapter 13, Part A Analysis of Variance and Experimental Design

Chapter 13, Part A Analysis of Variance and Experimental Design Slides Prepared by JOHN S. LOUCKS St. Edward s Uiversity Slide 1 Chapter 13, Part A Aalysis of Variace ad Eperimetal Desig Itroductio to Aalysis of Variace Aalysis of Variace: Testig for the Equality of

More information

COMPLEX FACTORIZATIONS OF THE GENERALIZED FIBONACCI SEQUENCES {q n } Sang Pyo Jun

COMPLEX FACTORIZATIONS OF THE GENERALIZED FIBONACCI SEQUENCES {q n } Sang Pyo Jun Korea J. Math. 23 2015) No. 3 pp. 371 377 http://dx.doi.org/10.11568/kjm.2015.23.3.371 COMPLEX FACTORIZATIONS OF THE GENERALIZED FIBONACCI SEQUENCES {q } Sag Pyo Ju Abstract. I this ote we cosider a geeralized

More information

Chapter 6 Sampling Distributions

Chapter 6 Sampling Distributions Chapter 6 Samplig Distributios 1 I most experimets, we have more tha oe measuremet for ay give variable, each measuremet beig associated with oe radomly selected a member of a populatio. Hece we eed to

More information

Warped, Chirp Z-Transform: Radar Signal Processing

Warped, Chirp Z-Transform: Radar Signal Processing arped, Chirp Z-Trasform: Radar Sigal Processig by Garimella Ramamurthy Report o: IIIT/TR// Cetre for Commuicatios Iteratioal Istitute of Iformatio Techology Hyderabad - 5 3, IDIA Jauary ARPED, CHIRP Z

More information

Vibratory Motion. Prof. Zheng-yi Feng NCHU SWC. National CHung Hsing University, Department of Soil and Water Conservation

Vibratory Motion. Prof. Zheng-yi Feng NCHU SWC. National CHung Hsing University, Department of Soil and Water Conservation Vibratory Motio Prof. Zheg-yi Feg NCHU SWC 1 Types of vibratory motio Periodic motio Noperiodic motio See Fig. A1, p.58 Harmoic motio Periodic motio Trasiet motio impact Trasiet motio earthquake A powerful

More information

Research Article On the Strong Laws for Weighted Sums of ρ -Mixing Random Variables

Research Article On the Strong Laws for Weighted Sums of ρ -Mixing Random Variables Hidawi Publishig Corporatio Joural of Iequalities ad Applicatios Volume 2011, Article ID 157816, 8 pages doi:10.1155/2011/157816 Research Article O the Strog Laws for Weighted Sums of ρ -Mixig Radom Variables

More information

EE / EEE SAMPLE STUDY MATERIAL. GATE, IES & PSUs Signal System. Electrical Engineering. Postal Correspondence Course

EE / EEE SAMPLE STUDY MATERIAL. GATE, IES & PSUs Signal System. Electrical Engineering. Postal Correspondence Course Sigal-EE Postal Correspodece Course 1 SAMPLE STUDY MATERIAL Electrical Egieerig EE / EEE Postal Correspodece Course GATE, IES & PSUs Sigal System Sigal-EE Postal Correspodece Course CONTENTS 1. SIGNAL

More information

Evapotranspiration Estimation Using Support Vector Machines and Hargreaves-Samani Equation for St. Johns, FL, USA

Evapotranspiration Estimation Using Support Vector Machines and Hargreaves-Samani Equation for St. Johns, FL, USA Evirometal Egieerig 0th Iteratioal Coferece eissn 2029-7092 / eisbn 978-609-476-044-0 Vilius Gedimias Techical Uiversity Lithuaia, 27 28 April 207 Article ID: eviro.207.094 http://eviro.vgtu.lt DOI: https://doi.org/0.3846/eviro.207.094

More information

Complex Algorithms for Lattice Adaptive IIR Notch Filter

Complex Algorithms for Lattice Adaptive IIR Notch Filter 4th Iteratioal Coferece o Sigal Processig Systems (ICSPS ) IPCSIT vol. 58 () () IACSIT Press, Sigapore DOI:.7763/IPCSIT..V58. Complex Algorithms for Lattice Adaptive IIR Notch Filter Hog Liag +, Nig Jia

More information

Measurement uncertainty of the sound absorption

Measurement uncertainty of the sound absorption Measuremet ucertaity of the soud absorptio coefficiet Aa Izewska Buildig Research Istitute, Filtrowa Str., 00-6 Warsaw, Polad a.izewska@itb.pl 6887 The stadard ISO/IEC 705:005 o the competece of testig

More information

Chapter 11 Output Analysis for a Single Model. Banks, Carson, Nelson & Nicol Discrete-Event System Simulation

Chapter 11 Output Analysis for a Single Model. Banks, Carson, Nelson & Nicol Discrete-Event System Simulation Chapter Output Aalysis for a Sigle Model Baks, Carso, Nelso & Nicol Discrete-Evet System Simulatio Error Estimatio If {,, } are ot statistically idepedet, the S / is a biased estimator of the true variace.

More information

Correspondence should be addressed to Wing-Sum Cheung,

Correspondence should be addressed to Wing-Sum Cheung, Hidawi Publishig Corporatio Joural of Iequalities ad Applicatios Volume 2009, Article ID 137301, 7 pages doi:10.1155/2009/137301 Research Article O Pečarić-Raić-Dragomir-Type Iequalities i Normed Liear

More information

567. Research of Dynamics of a Vibration Isolation Platform

567. Research of Dynamics of a Vibration Isolation Platform 567. Research of Dyamics of a Vibratio Isolatio Platform A. Kilikevičius, M. Jurevičius 2, M. Berba 3 Vilius Gedimias Techical Uiversity, Departmet of Machie buildig, J. Basaavičiaus str. 28, LT-03224

More information

62. Power series Definition 16. (Power series) Given a sequence {c n }, the series. c n x n = c 0 + c 1 x + c 2 x 2 + c 3 x 3 +

62. Power series Definition 16. (Power series) Given a sequence {c n }, the series. c n x n = c 0 + c 1 x + c 2 x 2 + c 3 x 3 + 62. Power series Defiitio 16. (Power series) Give a sequece {c }, the series c x = c 0 + c 1 x + c 2 x 2 + c 3 x 3 + is called a power series i the variable x. The umbers c are called the coefficiets of

More information

Fourier and Periodogram Transform Temperature Analysis in Soil

Fourier and Periodogram Transform Temperature Analysis in Soil ISSN (e): 2250 3005 Volume, 05 Issue, 09 September 2015 Iteratioal Joural of Computatioal Egieerig Research (IJCER) Fourier ad Periodogram Trasform Aalysis i Soil Afolabi O.M. Adekule Ajasi Uiversity,

More information

Kolmogorov-Smirnov type Tests for Local Gaussianity in High-Frequency Data

Kolmogorov-Smirnov type Tests for Local Gaussianity in High-Frequency Data Proceedigs 59th ISI World Statistics Cogress, 5-30 August 013, Hog Kog (Sessio STS046) p.09 Kolmogorov-Smirov type Tests for Local Gaussiaity i High-Frequecy Data George Tauche, Duke Uiversity Viktor Todorov,

More information

Diffusivity and Mobility Quantization. in Quantum Electrical Semi-Ballistic. Quasi-One-Dimensional Conductors

Diffusivity and Mobility Quantization. in Quantum Electrical Semi-Ballistic. Quasi-One-Dimensional Conductors Advaces i Applied Physics, Vol., 014, o. 1, 9-13 HIKARI Ltd, www.m-hikari.com http://dx.doi.org/10.1988/aap.014.3110 Diffusivity ad Mobility Quatizatio i Quatum Electrical Semi-Ballistic Quasi-Oe-Dimesioal

More information

MASSACHUSETTS INSTITUTE OF TECHNOLOGY Department of Electrical Engineering and Computer Science. BACKGROUND EXAM September 30, 2004.

MASSACHUSETTS INSTITUTE OF TECHNOLOGY Department of Electrical Engineering and Computer Science. BACKGROUND EXAM September 30, 2004. MASSACHUSETTS INSTITUTE OF TECHNOLOGY Departmet of Electrical Egieerig ad Computer Sciece 6.34 Discrete Time Sigal Processig Fall 24 BACKGROUND EXAM September 3, 24. Full Name: Note: This exam is closed

More information

Random Variables, Sampling and Estimation

Random Variables, Sampling and Estimation Chapter 1 Radom Variables, Samplig ad Estimatio 1.1 Itroductio This chapter will cover the most importat basic statistical theory you eed i order to uderstad the ecoometric material that will be comig

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

Stopping oscillations of a simple harmonic oscillator using an impulse force

Stopping oscillations of a simple harmonic oscillator using an impulse force It. J. Adv. Appl. Math. ad Mech. 5() (207) 6 (ISSN: 2347-2529) IJAAMM Joural homepage: www.ijaamm.com Iteratioal Joural of Advaces i Applied Mathematics ad Mechaics Stoppig oscillatios of a simple harmoic

More information

Direction of Arrival Estimation Method in Underdetermined Condition Zhang Youzhi a, Li Weibo b, Wang Hanli c

Direction of Arrival Estimation Method in Underdetermined Condition Zhang Youzhi a, Li Weibo b, Wang Hanli c 4th Iteratioal Coferece o Advaced Materials ad Iformatio Techology Processig (AMITP 06) Directio of Arrival Estimatio Method i Uderdetermied Coditio Zhag Youzhi a, Li eibo b, ag Hali c Naval Aeroautical

More information

Statistical Analysis on Uncertainty for Autocorrelated Measurements and its Applications to Key Comparisons

Statistical Analysis on Uncertainty for Autocorrelated Measurements and its Applications to Key Comparisons Statistical Aalysis o Ucertaity for Autocorrelated Measuremets ad its Applicatios to Key Comparisos Nie Fa Zhag Natioal Istitute of Stadards ad Techology Gaithersburg, MD 0899, USA Outlies. Itroductio.

More information

577. Estimation of surface roughness using high frequency vibrations

577. Estimation of surface roughness using high frequency vibrations 577. Estimatio of surface roughess usig high frequecy vibratios V. Augutis, M. Sauoris, Kauas Uiversity of Techology Electroics ad Measuremets Systems Departmet Studetu str. 5-443, LT-5368 Kauas, Lithuaia

More information

Research Article Some E-J Generalized Hausdorff Matrices Not of Type M

Research Article Some E-J Generalized Hausdorff Matrices Not of Type M Abstract ad Applied Aalysis Volume 2011, Article ID 527360, 5 pages doi:10.1155/2011/527360 Research Article Some E-J Geeralized Hausdorff Matrices Not of Type M T. Selmaogullari, 1 E. Savaş, 2 ad B. E.

More information

The Discrete-Time Fourier Transform (DTFT)

The Discrete-Time Fourier Transform (DTFT) EEL: Discrete-Time Sigals ad Systems The Discrete-Time Fourier Trasorm (DTFT) The Discrete-Time Fourier Trasorm (DTFT). Itroductio I these otes, we itroduce the discrete-time Fourier trasorm (DTFT) ad

More information

Sensitivity Analysis of Daubechies 4 Wavelet Coefficients for Reduction of Reconstructed Image Error

Sensitivity Analysis of Daubechies 4 Wavelet Coefficients for Reduction of Reconstructed Image Error Proceedigs of the 6th WSEAS Iteratioal Coferece o SIGNAL PROCESSING, Dallas, Texas, USA, March -4, 7 67 Sesitivity Aalysis of Daubechies 4 Wavelet Coefficiets for Reductio of Recostructed Image Error DEVINDER

More information

FACULTY OF MATHEMATICAL STUDIES MATHEMATICS FOR PART I ENGINEERING. Lectures

FACULTY OF MATHEMATICAL STUDIES MATHEMATICS FOR PART I ENGINEERING. Lectures FACULTY OF MATHEMATICAL STUDIES MATHEMATICS FOR PART I ENGINEERING Lectures MODULE 5 STATISTICS II. Mea ad stadard error of sample data. Biomial distributio. Normal distributio 4. Samplig 5. Cofidece itervals

More information

11 Correlation and Regression

11 Correlation and Regression 11 Correlatio Regressio 11.1 Multivariate Data Ofte we look at data where several variables are recorded for the same idividuals or samplig uits. For example, at a coastal weather statio, we might record

More information

Entropy Rates and Asymptotic Equipartition

Entropy Rates and Asymptotic Equipartition Chapter 29 Etropy Rates ad Asymptotic Equipartitio Sectio 29. itroduces the etropy rate the asymptotic etropy per time-step of a stochastic process ad shows that it is well-defied; ad similarly for iformatio,

More information

Introduction to Signals and Systems, Part V: Lecture Summary

Introduction to Signals and Systems, Part V: Lecture Summary EEL33: Discrete-Time Sigals ad Systems Itroductio to Sigals ad Systems, Part V: Lecture Summary Itroductio to Sigals ad Systems, Part V: Lecture Summary So far we have oly looked at examples of o-recursive

More information

There is no straightforward approach for choosing the warmup period l.

There is no straightforward approach for choosing the warmup period l. B. Maddah INDE 504 Discrete-Evet Simulatio Output Aalysis () Statistical Aalysis for Steady-State Parameters I a otermiatig simulatio, the iterest is i estimatig the log ru steady state measures of performace.

More information

The target reliability and design working life

The target reliability and design working life Safety ad Security Egieerig IV 161 The target reliability ad desig workig life M. Holický Kloker Istitute, CTU i Prague, Czech Republic Abstract Desig workig life ad target reliability levels recommeded

More information

The Poisson Process *

The Poisson Process * OpeStax-CNX module: m11255 1 The Poisso Process * Do Johso This work is produced by OpeStax-CNX ad licesed uder the Creative Commos Attributio Licese 1.0 Some sigals have o waveform. Cosider the measuremet

More information

Practical Spectral Anaysis (continue) (from Boaz Porat s book) Frequency Measurement

Practical Spectral Anaysis (continue) (from Boaz Porat s book) Frequency Measurement Practical Spectral Aaysis (cotiue) (from Boaz Porat s book) Frequecy Measuremet Oe of the most importat applicatios of the DFT is the measuremet of frequecies of periodic sigals (eg., siusoidal sigals),

More information

Machine Learning Assignment-1

Machine Learning Assignment-1 Uiversity of Utah, School Of Computig Machie Learig Assigmet-1 Chadramouli, Shridhara sdhara@cs.utah.edu 00873255) Sigla, Sumedha sumedha.sigla@utah.edu 00877456) September 10, 2013 1 Liear Regressio a)

More information

Estimation for Complete Data

Estimation for Complete Data Estimatio for Complete Data complete data: there is o loss of iformatio durig study. complete idividual complete data= grouped data A complete idividual data is the oe i which the complete iformatio of

More information

Agreement of CI and HT. Lecture 13 - Tests of Proportions. Example - Waiting Times

Agreement of CI and HT. Lecture 13 - Tests of Proportions. Example - Waiting Times Sigificace level vs. cofidece level Agreemet of CI ad HT Lecture 13 - Tests of Proportios Sta102 / BME102 Coli Rudel October 15, 2014 Cofidece itervals ad hypothesis tests (almost) always agree, as log

More information

Estimation of Population Mean Using Co-Efficient of Variation and Median of an Auxiliary Variable

Estimation of Population Mean Using Co-Efficient of Variation and Median of an Auxiliary Variable Iteratioal Joural of Probability ad Statistics 01, 1(4: 111-118 DOI: 10.593/j.ijps.010104.04 Estimatio of Populatio Mea Usig Co-Efficiet of Variatio ad Media of a Auxiliary Variable J. Subramai *, G. Kumarapadiya

More information

ANALYSIS OF EXPERIMENTAL ERRORS

ANALYSIS OF EXPERIMENTAL ERRORS ANALYSIS OF EXPERIMENTAL ERRORS All physical measuremets ecoutered i the verificatio of physics theories ad cocepts are subject to ucertaities that deped o the measurig istrumets used ad the coditios uder

More information

3 Resampling Methods: The Jackknife

3 Resampling Methods: The Jackknife 3 Resamplig Methods: The Jackkife 3.1 Itroductio I this sectio, much of the cotet is a summary of material from Efro ad Tibshirai (1993) ad Maly (2007). Here are several useful referece texts o resamplig

More information

A PROCEDURE TO MODIFY THE FREQUENCY AND ENVELOPE CHARACTERISTICS OF EMPIRICAL GREEN'S FUNCTION. Lin LU 1 SUMMARY

A PROCEDURE TO MODIFY THE FREQUENCY AND ENVELOPE CHARACTERISTICS OF EMPIRICAL GREEN'S FUNCTION. Lin LU 1 SUMMARY A POCEDUE TO MODIFY THE FEQUENCY AND ENVELOPE CHAACTEISTICS OF EMPIICAL GEEN'S FUNCTION Li LU SUMMAY Semi-empirical method, which divides the fault plae of large earthquake ito mets ad uses small groud

More information

A Relationship Between the One-Way MANOVA Test Statistic and the Hotelling Lawley Trace Test Statistic

A Relationship Between the One-Way MANOVA Test Statistic and the Hotelling Lawley Trace Test Statistic http://ijspccseetorg Iteratioal Joural of Statistics ad Probability Vol 7, No 6; 2018 A Relatioship Betwee the Oe-Way MANOVA Test Statistic ad the Hotellig Lawley Trace Test Statistic Hasthika S Rupasighe

More information

ECON 3150/4150, Spring term Lecture 3

ECON 3150/4150, Spring term Lecture 3 Itroductio Fidig the best fit by regressio Residuals ad R-sq Regressio ad causality Summary ad ext step ECON 3150/4150, Sprig term 2014. Lecture 3 Ragar Nymoe Uiversity of Oslo 21 Jauary 2014 1 / 30 Itroductio

More information

Review Article Incomplete Bivariate Fibonacci and Lucas p-polynomials

Review Article Incomplete Bivariate Fibonacci and Lucas p-polynomials Discrete Dyamics i Nature ad Society Volume 2012, Article ID 840345, 11 pages doi:10.1155/2012/840345 Review Article Icomplete Bivariate Fiboacci ad Lucas p-polyomials Dursu Tasci, 1 Mirac Ceti Firegiz,

More information

Free Space Optical Wireless Communications under Turbulence Channel Effect

Free Space Optical Wireless Communications under Turbulence Channel Effect IOSR Joural of Electroics ad Commuicatio Egieerig (IOSR-JECE) e-issn: 78-834,p- ISSN: 78-8735.Volume 9, Issue 3, Ver. III (May - Ju. 014), PP 01-08 Free Space Optical Wireless Commuicatios uder Turbulece

More information

Improved Class of Ratio -Cum- Product Estimators of Finite Population Mean in two Phase Sampling

Improved Class of Ratio -Cum- Product Estimators of Finite Population Mean in two Phase Sampling Global Joural of Sciece Frotier Research: F Mathematics ad Decisio Scieces Volume 4 Issue 2 Versio.0 Year 204 Type : Double Blid Peer Reviewed Iteratioal Research Joural Publisher: Global Jourals Ic. (USA

More information

Chapter 22. Comparing Two Proportions. Copyright 2010, 2007, 2004 Pearson Education, Inc.

Chapter 22. Comparing Two Proportions. Copyright 2010, 2007, 2004 Pearson Education, Inc. Chapter 22 Comparig Two Proportios Copyright 2010, 2007, 2004 Pearso Educatio, Ic. Comparig Two Proportios Read the first two paragraphs of pg 504. Comparisos betwee two percetages are much more commo

More information

Chapter 22. Comparing Two Proportions. Copyright 2010 Pearson Education, Inc.

Chapter 22. Comparing Two Proportions. Copyright 2010 Pearson Education, Inc. Chapter 22 Comparig Two Proportios Copyright 2010 Pearso Educatio, Ic. Comparig Two Proportios Comparisos betwee two percetages are much more commo tha questios about isolated percetages. Ad they are more

More information

The z-transform. 7.1 Introduction. 7.2 The z-transform Derivation of the z-transform: x[n] = z n LTI system, h[n] z = re j

The z-transform. 7.1 Introduction. 7.2 The z-transform Derivation of the z-transform: x[n] = z n LTI system, h[n] z = re j The -Trasform 7. Itroductio Geeralie the complex siusoidal represetatio offered by DTFT to a represetatio of complex expoetial sigals. Obtai more geeral characteristics for discrete-time LTI systems. 7.

More information

Information-based Feature Selection

Information-based Feature Selection Iformatio-based Feature Selectio Farza Faria, Abbas Kazeroui, Afshi Babveyh Email: {faria,abbask,afshib}@staford.edu 1 Itroductio Feature selectio is a topic of great iterest i applicatios dealig with

More information

2C09 Design for seismic and climate changes

2C09 Design for seismic and climate changes 2C09 Desig for seismic ad climate chages Lecture 02: Dyamic respose of sigle-degree-of-freedom systems I Daiel Grecea, Politehica Uiversity of Timisoara 10/03/2014 Europea Erasmus Mudus Master Course Sustaiable

More information

OBJECTIVES. Chapter 1 INTRODUCTION TO INSTRUMENTATION FUNCTION AND ADVANTAGES INTRODUCTION. At the end of this chapter, students should be able to:

OBJECTIVES. Chapter 1 INTRODUCTION TO INSTRUMENTATION FUNCTION AND ADVANTAGES INTRODUCTION. At the end of this chapter, students should be able to: OBJECTIVES Chapter 1 INTRODUCTION TO INSTRUMENTATION At the ed of this chapter, studets should be able to: 1. Explai the static ad dyamic characteristics of a istrumet. 2. Calculate ad aalyze the measuremet

More information

Lecture 2: Monte Carlo Simulation

Lecture 2: Monte Carlo Simulation STAT/Q SCI 43: Itroductio to Resamplig ethods Sprig 27 Istructor: Ye-Chi Che Lecture 2: ote Carlo Simulatio 2 ote Carlo Itegratio Assume we wat to evaluate the followig itegratio: e x3 dx What ca we do?

More information

EXPERIMENT OF SIMPLE VIBRATION

EXPERIMENT OF SIMPLE VIBRATION EXPERIMENT OF SIMPLE VIBRATION. PURPOSE The purpose of the experimet is to show free vibratio ad damped vibratio o a system havig oe degree of freedom ad to ivestigate the relatioship betwee the basic

More information

FIR Filter Design: Part II

FIR Filter Design: Part II EEL335: Discrete-Time Sigals ad Systems. Itroductio I this set of otes, we cosider how we might go about desigig FIR filters with arbitrary frequecy resposes, through compositio of multiple sigle-peak

More information

Run-length & Entropy Coding. Redundancy Removal. Sampling. Quantization. Perform inverse operations at the receiver EEE

Run-length & Entropy Coding. Redundancy Removal. Sampling. Quantization. Perform inverse operations at the receiver EEE Geeral e Image Coder Structure Motio Video (s 1,s 2,t) or (s 1,s 2 ) Natural Image Samplig A form of data compressio; usually lossless, but ca be lossy Redudacy Removal Lossless compressio: predictive

More information

4. Partial Sums and the Central Limit Theorem

4. Partial Sums and the Central Limit Theorem 1 of 10 7/16/2009 6:05 AM Virtual Laboratories > 6. Radom Samples > 1 2 3 4 5 6 7 4. Partial Sums ad the Cetral Limit Theorem The cetral limit theorem ad the law of large umbers are the two fudametal theorems

More information

Expectation and Variance of a random variable

Expectation and Variance of a random variable Chapter 11 Expectatio ad Variace of a radom variable The aim of this lecture is to defie ad itroduce mathematical Expectatio ad variace of a fuctio of discrete & cotiuous radom variables ad the distributio

More information

Shock-Turbulence Interaction

Shock-Turbulence Interaction Shock-Turbulece Iteractio A.Sakurai ad M.Tsukamoto Tokyo Deki Uiversity, Nishikicho -, Kada, Chiyoda-ku, Tokyo, Japa Abstract. For the geeral purpose of ivestigatig pheomeo of shock-turbulece iteractio,

More information

Modified Ratio Estimators Using Known Median and Co-Efficent of Kurtosis

Modified Ratio Estimators Using Known Median and Co-Efficent of Kurtosis America Joural of Mathematics ad Statistics 01, (4): 95-100 DOI: 10.593/j.ajms.01004.05 Modified Ratio s Usig Kow Media ad Co-Efficet of Kurtosis J.Subramai *, G.Kumarapadiya Departmet of Statistics, Podicherry

More information

Comparing Two Populations. Topic 15 - Two Sample Inference I. Comparing Two Means. Comparing Two Pop Means. Background Reading

Comparing Two Populations. Topic 15 - Two Sample Inference I. Comparing Two Means. Comparing Two Pop Means. Background Reading Topic 15 - Two Sample Iferece I STAT 511 Professor Bruce Craig Comparig Two Populatios Research ofte ivolves the compariso of two or more samples from differet populatios Graphical summaries provide visual

More information

Topic 18: Composite Hypotheses

Topic 18: Composite Hypotheses Toc 18: November, 211 Simple hypotheses limit us to a decisio betwee oe of two possible states of ature. This limitatio does ot allow us, uder the procedures of hypothesis testig to address the basic questio:

More information

Research Article Powers of Complex Persymmetric Antitridiagonal Matrices with Constant Antidiagonals

Research Article Powers of Complex Persymmetric Antitridiagonal Matrices with Constant Antidiagonals Hidawi Publishig orporatio ISRN omputatioal Mathematics, Article ID 4570, 5 pages http://dx.doi.org/0.55/04/4570 Research Article Powers of omplex Persymmetric Atitridiagoal Matrices with ostat Atidiagoals

More information

STA Learning Objectives. Population Proportions. Module 10 Comparing Two Proportions. Upon completing this module, you should be able to:

STA Learning Objectives. Population Proportions. Module 10 Comparing Two Proportions. Upon completing this module, you should be able to: STA 2023 Module 10 Comparig Two Proportios Learig Objectives Upo completig this module, you should be able to: 1. Perform large-sample ifereces (hypothesis test ad cofidece itervals) to compare two populatio

More information

Varanasi , India. Corresponding author

Varanasi , India. Corresponding author A Geeral Family of Estimators for Estimatig Populatio Mea i Systematic Samplig Usig Auxiliary Iformatio i the Presece of Missig Observatios Maoj K. Chaudhary, Sachi Malik, Jayat Sigh ad Rajesh Sigh Departmet

More information

Statistics 511 Additional Materials

Statistics 511 Additional Materials Cofidece Itervals o mu Statistics 511 Additioal Materials This topic officially moves us from probability to statistics. We begi to discuss makig ifereces about the populatio. Oe way to differetiate probability

More information

Signal Processing in Mechatronics. Lecture 3, Convolution, Fourier Series and Fourier Transform

Signal Processing in Mechatronics. Lecture 3, Convolution, Fourier Series and Fourier Transform Sigal Processig i Mechatroics Summer semester, 1 Lecture 3, Covolutio, Fourier Series ad Fourier rasform Dr. Zhu K.P. AIS, UM 1 1. Covolutio Covolutio Descriptio of LI Systems he mai premise is that the

More information

HAJEK-RENYI-TYPE INEQUALITY FOR SOME NONMONOTONIC FUNCTIONS OF ASSOCIATED RANDOM VARIABLES

HAJEK-RENYI-TYPE INEQUALITY FOR SOME NONMONOTONIC FUNCTIONS OF ASSOCIATED RANDOM VARIABLES HAJEK-RENYI-TYPE INEQUALITY FOR SOME NONMONOTONIC FUNCTIONS OF ASSOCIATED RANDOM VARIABLES ISHA DEWAN AND B. L. S. PRAKASA RAO Received 1 April 005; Revised 6 October 005; Accepted 11 December 005 Let

More information

Estimation of a population proportion March 23,

Estimation of a population proportion March 23, 1 Social Studies 201 Notes for March 23, 2005 Estimatio of a populatio proportio Sectio 8.5, p. 521. For the most part, we have dealt with meas ad stadard deviatios this semester. This sectio of the otes

More information

ECON 3150/4150, Spring term Lecture 1

ECON 3150/4150, Spring term Lecture 1 ECON 3150/4150, Sprig term 2013. Lecture 1 Ragar Nymoe Uiversity of Oslo 15 Jauary 2013 1 / 42 Refereces to Lecture 1 ad 2 Hill, Griffiths ad Lim, 4 ed (HGL) Ch 1-1.5; Ch 2.8-2.9,4.3-4.3.1.3 Bårdse ad

More information

Module 18 Discrete Time Signals and Z-Transforms Objective: Introduction : Description: Discrete Time Signal representation

Module 18 Discrete Time Signals and Z-Transforms Objective: Introduction : Description: Discrete Time Signal representation Module 8 Discrete Time Sigals ad Z-Trasforms Objective:To uderstad represetig discrete time sigals, apply z trasform for aalyzigdiscrete time sigals ad to uderstad the relatio to Fourier trasform Itroductio

More information

1 Review of Probability & Statistics

1 Review of Probability & Statistics 1 Review of Probability & Statistics a. I a group of 000 people, it has bee reported that there are: 61 smokers 670 over 5 960 people who imbibe (drik alcohol) 86 smokers who imbibe 90 imbibers over 5

More information

(a) (b) All real numbers. (c) All real numbers. (d) None. to show the. (a) 3. (b) [ 7, 1) (c) ( 7, 1) (d) At x = 7. (a) (b)

(a) (b) All real numbers. (c) All real numbers. (d) None. to show the. (a) 3. (b) [ 7, 1) (c) ( 7, 1) (d) At x = 7. (a) (b) Chapter 0 Review 597. E; a ( + )( + ) + + S S + S + + + + + + S lim + l. D; a diverges by the Itegral l k Test sice d lim [(l ) ], so k l ( ) does ot coverge absolutely. But it coverges by the Alteratig

More information

FIR Filter Design: Part I

FIR Filter Design: Part I EEL3: Discrete-Time Sigals ad Systems FIR Filter Desig: Part I. Itroductio FIR Filter Desig: Part I I this set o otes, we cotiue our exploratio o the requecy respose o FIR ilters. First, we cosider some

More information

Formation of A Supergain Array and Its Application in Radar

Formation of A Supergain Array and Its Application in Radar Formatio of A Supergai Array ad ts Applicatio i Radar Tra Cao Quye, Do Trug Kie ad Bach Gia Duog. Research Ceter for Electroic ad Telecommuicatios, College of Techology (Coltech, Vietam atioal Uiversity,

More information

Chapter 10: Power Series

Chapter 10: Power Series Chapter : Power Series 57 Chapter Overview: Power Series The reaso series are part of a Calculus course is that there are fuctios which caot be itegrated. All power series, though, ca be itegrated because

More information

Statistics 300: Elementary Statistics

Statistics 300: Elementary Statistics Statistics 300: Elemetary Statistics Sectios 7-, 7-3, 7-4, 7-5 Parameter Estimatio Poit Estimate Best sigle value to use Questio What is the probability this estimate is the correct value? Parameter Estimatio

More information

PH 411/511 ECE B(k) Sin k (x) dk (1)

PH 411/511 ECE B(k) Sin k (x) dk (1) Fall-27 PH 4/5 ECE 598 A. La Rosa Homework-3 Due -7-27 The Homework is iteded to gai a uderstadig o the Heiseberg priciple, based o a compariso betwee the width of a pulse ad the width of its spectral

More information

GUIDELINES ON REPRESENTATIVE SAMPLING

GUIDELINES ON REPRESENTATIVE SAMPLING DRUGS WORKING GROUP VALIDATION OF THE GUIDELINES ON REPRESENTATIVE SAMPLING DOCUMENT TYPE : REF. CODE: ISSUE NO: ISSUE DATE: VALIDATION REPORT DWG-SGL-001 002 08 DECEMBER 2012 Ref code: DWG-SGL-001 Issue

More information

Computing Confidence Intervals for Sample Data

Computing Confidence Intervals for Sample Data Computig Cofidece Itervals for Sample Data Topics Use of Statistics Sources of errors Accuracy, precisio, resolutio A mathematical model of errors Cofidece itervals For meas For variaces For proportios

More information

Statistical Noise Models and Diagnostics

Statistical Noise Models and Diagnostics L. Yaroslavsky: Advaced Image Processig Lab: A Tutorial, EUSIPCO2 LECTURE 2 Statistical oise Models ad Diagostics 2. Statistical models of radom iterfereces: (i) Additive sigal idepedet oise model: r =

More information

Module 11: Applications : Linear prediction, Speech Analysis and Speech Enhancement Prof. Eliathamby Ambikairajah Dr. Tharmarajah Thiruvaran School

Module 11: Applications : Linear prediction, Speech Analysis and Speech Enhancement Prof. Eliathamby Ambikairajah Dr. Tharmarajah Thiruvaran School Module : Applicatios : Liear predictio, Speech Aalysis ad Speech Ehacemet Prof. Eliathamby Ambiairajah Dr. Tharmarajah Thiruvara School of Electrical Egieerig & Telecommuicatios The Uiversity of New South

More information