Transistor/Gate Sizing Optimization

Size: px
Start display at page:

Download "Transistor/Gate Sizing Optimization"

Transcription

1 Trasstor/Gate Szg Optmzato Gve: Logc etwork wth or wthout cell lbrary Fd: Optmal sze for each trasstor/gate to mmze area or power, both uder delay costrat Statc szg: based o tmg aalyss ad cosder all paths at oce [Fshbur-Dulop, ICCAD 85][Sapatekar et al., TCAD 93] [Berkelaar-Jess, EDAC 90][Che-Oodera-Tamaru, ICCAD 95] Dyamc szg: based o tmg smulato ad cosder paths actvated by gve patters [Co et al., ICCAD 96] Trasstor szg versus gate szg The Trasstor Szg Problem Problem statemet mmze Areax Comb. Logc subject to Delayx T spec or mmze Powerx subject to Delayx T spec Prepared by CK 1

2 Mathematcal Backgroud - dmesoal space Ay ordered -tuple x = x 1, x 2,..., x ca be thought of as a pot a -dmesoal space fx 1,x 2,..., x s a fucto o the -dmesoal space Covex fuctos fx s a covex fucto f gve fx ay two pots x a ad x b, the le jog the two pots les o or above the fucto fx x x a x b Nocovex f: x a x b x Math Backgroud Cotd. Covex fuctos two dmesos fx 1,x 2 = x x 2 2 Formally, fx s covex f fα x a + [1 - α] x b α fx a + [1 - α] fx b 0 α 1 Prepared by CK 2

3 Math Backgroud Cotd. Covex sets A set S s a covex set f gve ay two pots x a ad x b the set, the le jog the two pots les etrely wth the set Examples Shape of yomg Shape of a pzza No-covex Sets Shape of CA Slhouette of the Taj Mahal Math Backgroud Cotd. Mathematcal characterzato of a covex set S If x 1, x 2 S, the α x α x 2 S, for 0 α 1 x 1 x 2 If fx s a covex fucto, fx c s a covex set A tersecto of covex sets s a covex set Prepared by CK 3

4 Math Backgroud Cotd. Covex programmg problem mmze covex fucto fx such that [f x c ] Global mmum value s uque! No-rgorous explaato from The Hadwaver s Gude to the Galaxy fx x a x b x Math Backgroud Cotd. Eglsh A posyomal s lke a polyomal except all coeffcets are postve expoets could be real umbers postve or egatve Are these posyomals? x x x x x x x x x x 3 + 5/x 1 + x x 4 + 3/x 3 YES NO YES Prepared by CK 4

5 Math Backgroud Cotd. I ay posyomal fucto fx 1, x 2,..., x, substtute x = expz to get Fz 1, z 2,..., z The Fz 1, z 2,..., z = covex fucto z 1,..., z! mmze posyomal objectve x s s.t. posyomal fucto x s K for 1 m [x = expz ] mmze covex objectve over a covex set Therefore, ay local mmum s a global mmum! Trasstor Szg uder the Elmore Model x s the set vector of trasstor szes mmze Areax subject to Delayx T spec Areax = Σ = 1 to x posyomal! Each path delay = Σ R C R x -1, C x posyomal path delay fucto Delayx T spec Pathdelayx T spec for all paths Therefore, problem has a uque global m. value Prepared by CK 5

6 TILOS TImed LOgc Sythess Phlosophy Sce m. value s uque, a smple method should fd t! Problem mmze Areax subject to Delayx T spec Strategy Set all trasstors the crcut to mmum sze Fd the crtcal path largest delay path Reduce delay of crtcal path, but wth a mmal crease the objectve fucto value TILOS s a regstered trademark of Lucet Techologes TILOS Cotd. mmze Areax subject to Delayx T spec Fd D/ A for all trasstors o crtcal path Bump up the sze of trasstor wth the largest D/ A x M x + a default: M = 1; a = 1 cotact head wdth IN Crtcal Path OUT Crcut Prepared by CK 6

7 Sestvty Computato Dw = K + R prev C u. w + R u. C / w R prev w C D/ w = R prev. C u - R u. C / w 2 1 Could mmze path delay by settg dervatve to zero Problem: may cause aother path delay to become very hgh! hy Is t Ths THE Perfect Soluto? Problems wth teractg paths A B C D 1 Better to sze A tha to sze all of B, C ad D 2 If X-E s ear-crtcal ad A-D s crtcal, sze A ot D X E False paths, layout cosderatos ot corporated AND YET.. TILOS the commercal tool gves good solutos It has hadled crcuts wth 250K trasstors It has lear tme performace wth creasg crcut sze Prepared by CK 7

8 CONTRAST Solves the covex optmzato problem exactly Uses a teror pot method that s guarateed to fd the optmal soluto Delay spec. satsfed Optmal soluto Ca hadle crcuts wth about a thousad trasstors Covex Polytopes Polytope = -dmesoal covex polygo Half-space: a T x b a T x = b s a hyperplae e.g. a 1 x 1 + a 2 x 2 b two dmesos Polytope = tersecto of half-spaces,.e., a 1 T x b 1 AND a 2 T x b 2 AND a m T x b m Represeted as A x b Prepared by CK 8

9 Covex Optmzato Algorthm Vadya 1 Eclose soluto wth a polytope varat Typcally, take a box represeted by w w MAX ad w w MIN as the startg polytope. 2 Fd ceter of polytope, w c 3 Does w c satsfy costrats tmg specs? Take trasstor wdths correspodg to w c ad perform a statc tmg aalyss 4 Add a hyperplae through the ceter so that the soluto les etrely oe half-space Hyperplae equato depeds o feasblty of w c Equato of the New Half-Space Half-space: f w c. w f w c. w c If w c s feasble the f = objectve fucto Fd gradet of area fucto w c If w c s feasble the f = volated costrat Fd gradet of crtcal path delay Prepared by CK 9

10 w 2 w 1 Illustratve Example S S soluto f w = c, f decreasg S S Calculatg the Polytope Ceter Fdg exact cetrod s computatoally expesve Estmate ceter by mmzg log-barrer fucto Fx = - Σ =1 to m log a T x - b Happy cocdece : Fx s a covex fucto! Physcal meag: maxmze product of perpedcular dstaces to each hyperplae that defes the polytope Prepared by CK 10

11 Lear Programmg Methods LP-based approaches Model gate delay as a pecewse lear fucto Delay Parameters: trasstor wdths w, w p faout trasstor wdths put trasto tme Formulate problem as a lear program LP Use a effcet smplex package to solve LP w Power-Delay Szg mmze Powerw subject to Delayw T spec Area A spec Each gate sze Msze Power = dyamc power + short-crcut power Prepared by CK 11

12 POST-IT Dyamc Power Dyamc Power Power requred to charge/dscharge capactaces P dyamc = C L V dd 2 f p T C L = load capactace, f = clock frequecy, p T = trasto probablty Posyomal fucto w s f p T costat Costtutes domat part of power a well-desged crcut Mmze dyamc power mmze C L mmze all trasstor szes! RIGHT? Ufortuately ot! Short-Crcut Power POST-IT Short-crcut Power Power dsspated whe a drect V dd -groud path exsts Approxmate formula by Veedrck may assumptos P short-ckt = β/12. V dd -2V T 2 τ f p T β = trascoductace, τ = trasto tme Posyomal fucto w s f p T cost Other more accurate models: table lookup, curve-fttg Less tha 10-20% of total power a well-desged crcut So what s the catch? Prepared by CK 12

13 The Catch X A B C D E F G H Delay of gate A s large Therefore, the value of τ for B, C,..., H s large Therefore short-crcut power for B, C,..., H s large Ca be reduced by reducg the delay of A I other words, sze A! Tradeoff dyamc ad short-crcut power! Mpower msze Soluto Techque beg Calculate p T 's for mszed gates error < ε? ed No Yes Solve gate szg problem for curret p T Calculate p T 's for ew szes error = old p T - ew p T Problem: accuraces short-ckt. power model Prepared by CK 13

14 Prepared by CK 14 Trasstor/Gate Szg [Borah-Owes-Irw, ISLPD 95, TCAD 96] γ σ α τ µ τ µ + + = = = = f f k f CL f c V P dd Optmal trasstor sze τ µ µ τ µ µ + = + = = = = = p I p p p I p C O C p O 1 1 * 1 1 * C I = t. cap Power Optmal Szes ad Correspodg Power Savgs

15 Power-Delay Optmzato Power, Delay ad Power-Delay Curves Prepared by CK 15

16 Power-Delay Optmal Trasstor Szg Algorthm Power-Optmal tal szg Tmg aalyss hle exsts path-delay > target-delay Power-delay optmal szg crtcal path f path-delay > target-delay upsze trasstor wth mmum power-delay slope f path-delay < target-delay dowsze trasstor wth mmum power-delay slope Icremetal tmg aalyss Effect of Trasstor Szg Prepared by CK 16

For all questions, answer choice E) NOTA" means none of the above answers is correct. A) 50,500 B) 500,000 C) 500,500 D) 1,001,000 E) NOTA

For all questions, answer choice E) NOTA means none of the above answers is correct. A) 50,500 B) 500,000 C) 500,500 D) 1,001,000 E) NOTA For all questos, aswer choce " meas oe of the above aswers s correct.. What s the sum of the frst 000 postve tegers? A) 50,500 B) 500,000 C) 500,500 D),00,000. What s the sum of the tegers betwee 00 ad

More information

LP: example of formulations

LP: example of formulations LP: eample of formulatos Three classcal decso problems OR: Trasportato problem Product-m problem Producto plag problem Operatos Research Massmo Paolucc DIBRIS Uversty of Geova Trasportato problem The decso

More information

Bezier curves. 1. Defining a Bezier curve. A closed Bezier curve can simply be generated by closing its characteristic polygon

Bezier curves. 1. Defining a Bezier curve. A closed Bezier curve can simply be generated by closing its characteristic polygon Curve represetato Copyrght@, YZU Optmal Desg Laboratory. All rghts reserved. Last updated: Yeh-Lag Hsu (--). Note: Ths s the course materal for ME55 Geometrc modelg ad computer graphcs, Yua Ze Uversty.

More information

Machine Learning: Algorithms and Applications

Machine Learning: Algorithms and Applications /03/ Mache Learg: Algorthms ad Applcatos Florao Z Free Uversty of Boze-Bolzao Faculty of Computer Scece Academc Year 0-0 Lecture 3: th March 0 Naïve Bayes classfer ( Problem defto A trag set X, where each

More information

Fitting. We ve learned how to detect edges, corners, blobs. Now what? We would like to form a. compact representation of

Fitting. We ve learned how to detect edges, corners, blobs. Now what? We would like to form a. compact representation of Fttg Fttg We ve leared how to detect edges, corers, blobs. Now what? We would lke to form a hgher-level, h l more compact represetato of the features the mage b groupg multple features accordg to a smple

More information

1-D matrix method. U 4 transmitted. incident U 2. reflected U 1 U 5 U 3 L 2 L 3 L 4. EE 439 matrix method 1

1-D matrix method. U 4 transmitted. incident U 2. reflected U 1 U 5 U 3 L 2 L 3 L 4. EE 439 matrix method 1 -D matrx method We ca expad the smple plae-wave scatterg for -D examples that we ve see to a more versatle matrx approach that ca be used to hadle may terestg -D problems. The basc dea s that we ca break

More information

Point Estimation-III: General Methods for Obtaining Estimators

Point Estimation-III: General Methods for Obtaining Estimators Pot Estmato-III: Geeral Methods for Obtag Estmators RECAP 0.-0.6 Data: Radom Sample from a Populato of terest o Real valued measuremets: o Assumpto (Hopefully Reasoable) o Model: Specfed Probablty Dstrbuto

More information

Eight Solved and Eight Open Problems in Elementary Geometry

Eight Solved and Eight Open Problems in Elementary Geometry Eght Solved ad Eght Ope Problems Elemetary Geometry Floret Smaradache Math & Scece Departmet Uversty of New Mexco, Gallup, US I ths paper we revew eght prevous proposed ad solved problems of elemetary

More information

CS 2710 Foundations of AI Lecture 22. Machine learning. Machine Learning

CS 2710 Foundations of AI Lecture 22. Machine learning. Machine Learning CS 7 Foudatos of AI Lecture Mache learg Mlos Hauskrecht mlos@cs.ptt.edu 539 Seott Square Mache Learg The feld of mache learg studes the desg of computer programs (agets) capable of learg from past eperece

More information

Office Hours. COS 341 Discrete Math. Office Hours. Homework 8. Currently, my office hours are on Friday, from 2:30 to 3:30.

Office Hours. COS 341 Discrete Math. Office Hours. Homework 8. Currently, my office hours are on Friday, from 2:30 to 3:30. Oce Hours Curretly, my oce hours are o Frday, rom :30 to 3:30. COS 31 Dscrete Math 1 Oce Hours Curretly, my oce hours are o Frday, rom :30 to 3:30. Nobody seems to care. Chage oce hours? Tuesday, 8 PM

More information

Eight Solved and Eight Open Problems in Elementary Geometry

Eight Solved and Eight Open Problems in Elementary Geometry Eght Solved ad Eght Ope Problems Elemetary Geometry Floret Smaradache Math & Scece Departmet Uversty of New Mexco, Gallup, US I ths paper we revew eght prevous proposed ad solved problems of elemetary

More information

Nine Solved and Nine Open Problems in Elementary Geometry

Nine Solved and Nine Open Problems in Elementary Geometry Ne Solved ad Ne Ope Problems Elemetary Geometry Floret Smaradache Math & Scece Departmet Uversty of New Mexco, Gallup, US I ths paper we revew e prevous proposed ad solved problems of elemetary D geometry

More information

International Mathematical Forum, 1, 2006, no. 31, ON JONES POLYNOMIALS OF GRAPHS OF TORUS KNOTS K (2, q ) Tamer UGUR, Abdullah KOPUZLU

International Mathematical Forum, 1, 2006, no. 31, ON JONES POLYNOMIALS OF GRAPHS OF TORUS KNOTS K (2, q ) Tamer UGUR, Abdullah KOPUZLU Iteratoal Mathematcal Forum,, 6, o., 57-54 ON JONES POLYNOMIALS OF RAPHS OF TORUS KNOTS K (, q ) Tamer UUR, Abdullah KOPUZLU Atatürk Uverst Scece Facult Dept. of. Math. 54 Erzurum, Turkey tugur@atau.edu.tr

More information

A Framework for Block-Based Timing Sensitivity Analysis

A Framework for Block-Based Timing Sensitivity Analysis 39.3 Framework for Block-Based Tmg Sestvty alyss Sajay V. Kumar Chadramoul V. Kashyap Sach S. Sapatekar Uversty of Mesota Itel Corporato Uversty of Mesota Meapols MN 55455 Hllsboro OR 973 Meapols MN 55455

More information

ChEn 475 Statistical Analysis of Regression Lesson 1. The Need for Statistical Analysis of Regression

ChEn 475 Statistical Analysis of Regression Lesson 1. The Need for Statistical Analysis of Regression Statstcal-Regresso_hadout.xmcd Statstcal Aalss of Regresso ChE 475 Statstcal Aalss of Regresso Lesso. The Need for Statstcal Aalss of Regresso What do ou do wth dvdual expermetal data pots? How are the

More information

Optimal Allocation of Complex Equipment System Maintainability

Optimal Allocation of Complex Equipment System Maintainability Optmal Allocato of Complex Equpmet System ataablty X Re Graduate School, Natoal Defese Uversty, Bejg, 100091, Cha edcal Protecto Laboratory, Naval edcal Research Isttute, Shagha, 200433, Cha Emal:rexs841013@163.com

More information

From Math to Efficient Hardware. James C. Hoe Department of ECE Carnegie Mellon University

From Math to Efficient Hardware. James C. Hoe Department of ECE Carnegie Mellon University FFT Compler: From Math to Effcet Hardware James C. Hoe Departmet of ECE Carege Mello Uversty jot wor wth Peter A. Mlder, Fraz Frachett, ad Marus Pueschel the SPIRAL project wth support from NSF ACR-3493,

More information

FLOORPLAN DESIGN FOR WIRING LENGTH MINIMIZATION IN ULSI CHIP USING SIMULATED ANNEALING. Apichat Terapasirdsin and Naruemon Wattanapongsakorn

FLOORPLAN DESIGN FOR WIRING LENGTH MINIMIZATION IN ULSI CHIP USING SIMULATED ANNEALING. Apichat Terapasirdsin and Naruemon Wattanapongsakorn Proceedgs of the 25 Iteratoal Coferece o Smulato ad Modelg V. Kachtvchyaukul, U. Purtrapba, P. Utayopas, eds. FLOORPLN DESIGN FOR WIRING LENGTH MINIMIZTION IN ULSI CHIP USING SIMULTED NNELING pchat Terapasrds

More information

A PROCEDURE FOR SOLVING INTEGER BILEVEL LINEAR PROGRAMMING PROBLEMS

A PROCEDURE FOR SOLVING INTEGER BILEVEL LINEAR PROGRAMMING PROBLEMS ISSN: 39-8753 Iteratoal Joural of Iovatve Research Scece, Egeerg ad Techology A ISO 397: 7 Certfed Orgazato) Vol. 3, Issue, Jauary 4 A PROCEDURE FOR SOLVING INTEGER BILEVEL LINEAR PROGRAMMING PROBLEMS

More information

A Novel Optimization Algorithm for Adaptive Simplex Method with Application to High Dimensional Functions

A Novel Optimization Algorithm for Adaptive Simplex Method with Application to High Dimensional Functions A Novel Optmzato Algorthm for Adaptve Smplex Method th Applcato to Hgh Dmesoal Fuctos ZuoYg LIU, XaWe LUO 2 Southest Uversty Chogqg 402460, Cha, zuyglu@alyu.com 2 Southest Uversty Chogqg 402460, Cha, xael@su.edu.c.

More information

COMSC 2613 Summer 2000

COMSC 2613 Summer 2000 Programmg II Fal Exam COMSC 63 Summer Istructos: Name:. Prt your ame the space provded Studet Id:. Prt your studet detfer the space Secto: provded. Date: 3. Prt the secto umber of the secto whch you are

More information

Prof. Feng Liu. Winter /24/2019

Prof. Feng Liu. Winter /24/2019 Prof. Feg Lu Wter 209 http://www.cs.pd.edu/~flu/courses/cs40/ 0/24/209 Last Tme Feature detecto 2 Toda Feature matchg Fttg The followg sldes are largel from Prof. S. Lazebk 3 Wh etract features? Motvato:

More information

ECE Digital Image Processing and Introduction to Computer Vision

ECE Digital Image Processing and Introduction to Computer Vision ECE59064 Dgtal Image Processg ad Itroducto to Computer Vso Depart. of ECE NC State Uverst Istructor: Tafu Matt Wu Sprg 07 Outle Recap Le Segmet Detecto Fttg Least square Total square Robust estmator Hough

More information

ITEM ToolKit Technical Support Notes

ITEM ToolKit Technical Support Notes ITEM ToolKt Notes Fault Tree Mathematcs Revew, Ic. 2875 Mchelle Drve Sute 300 Irve, CA 92606 Phoe: +1.240.297.4442 Fax: +1.240.297.4429 http://www.itemsoft.com Page 1 of 15 6/1/2016 Copyrght, Ic., All

More information

APR 1965 Aggregation Methodology

APR 1965 Aggregation Methodology Sa Joaqu Valley Ar Polluto Cotrol Dstrct APR 1965 Aggregato Methodology Approved By: Sged Date: March 3, 2016 Araud Marjollet, Drector of Permt Servces Backgroud Health rsk modelg ad the collecto of emssos

More information

A Comparison of Univariate Smoothing Models: Application to Heart Rate Data Marcus Beal, Member, IEEE

A Comparison of Univariate Smoothing Models: Application to Heart Rate Data Marcus Beal, Member, IEEE A Comparso of Uvarate Smoothg Models: Applcato to Heart Rate Data Marcus Beal, Member, IEEE E-mal: bealm@pdx.edu Abstract There are a umber of uvarate smoothg models that ca be appled to a varety of olear

More information

MATHEMATICAL PROGRAMMING MODEL OF THE CRITICAL CHAIN METHOD

MATHEMATICAL PROGRAMMING MODEL OF THE CRITICAL CHAIN METHOD MATHEMATICAL PROGRAMMING MODEL OF THE CRITICAL CHAIN METHOD TOMÁŠ ŠUBRT, PAVLÍNA LANGROVÁ CUA, SLOVAKIA Abstract Curretly there s creasgly dcated that most of classcal project maagemet methods s ot sutable

More information

Face Recognition using Supervised & Unsupervised Techniques

Face Recognition using Supervised & Unsupervised Techniques Natoal Uversty of Sgapore EE5907-Patter recogto-2 NAIONAL UNIVERSIY OF SINGAPORE EE5907 Patter Recogto Project Part-2 Face Recogto usg Supervsed & Usupervsed echques SUBMIED BY: SUDEN NAME: harapa Reddy

More information

Fuzzy Multi-objective Linear Programming Approach for Traveling Salesman Problem

Fuzzy Multi-objective Linear Programming Approach for Traveling Salesman Problem Fuzzy Mult-objectve Lear Programmg Approach for Travelg Salesma Problem Ama Rehmat Pujab Uversty College of Iformato Techology Uversty of the Pujab, Lahore, Pasta ama_mmal@yahoo.com Ha Saeed Pujab Uversty

More information

MINIMIZATION OF THE VALUE OF DAVIES-BOULDIN INDEX

MINIMIZATION OF THE VALUE OF DAVIES-BOULDIN INDEX MIIMIZATIO OF THE VALUE OF DAVIES-BOULDI IDEX ISMO ÄRÄIE ad PASI FRÄTI Departmet of Computer Scece, Uversty of Joesuu Box, FI-800 Joesuu, FILAD ABSTRACT We study the clusterg problem whe usg Daves-Bould

More information

Image Analysis. Segmentation by Fitting a Model. Christophoros Nikou We ve learned how to detect edges, corners, blobs. Now what?

Image Analysis. Segmentation by Fitting a Model. Christophoros Nikou We ve learned how to detect edges, corners, blobs. Now what? Image Aalyss Fttg Segmetato y Fttg a Model Chrstophoros Nkou ckou@cs.uo.gr Images take from: D. Forsyth ad J. Poce. Computer Vso: A Moder Approach, Pretce Hall, 003. Computer Vso course y Svetlaa Lazek,

More information

Region Matching by Optimal Fuzzy Dissimilarity

Region Matching by Optimal Fuzzy Dissimilarity Rego Matchg by Optmal Fuzzy Dssmlarty Zhaggu Zeg, Ala Fu ad Hog Ya School of Electrcal ad formato Egeerg The Uversty of Sydey Phoe: +6--935-6659 Fax: +6--935-3847 Emal: zzeg@ee.usyd.edu.au Abstract: Ths

More information

Signal-Path Driven Partition and Placement for Analog Circuit

Signal-Path Driven Partition and Placement for Analog Circuit Sgal-Path Drve Partto ad Placemet for Aalog Crcut D Log Xalog Hog Sheq Dog EDA Lab Departmet of Computer Scece ad Techology Tsghua Uversty Beg 100084 Cha logd02@malstsghuaeduc; hxl-dcs@maltsghuaeduc; dogsq@maltsghuaeduc

More information

Parallel Ant Colony for Nonlinear Function Optimization with Graphics Hardware Acceleration

Parallel Ant Colony for Nonlinear Function Optimization with Graphics Hardware Acceleration Proceedgs of the 009 IEEE Iteratoal Coferece o Systems Ma ad Cyberetcs Sa Atoo TX USA - October 009 Parallel At Coloy for Nolear Fucto Optmzato wth Graphcs Hardware Accelerato Wehag Zhu Departmet of Idustral

More information

Reconstruction of Orthogonal Polygonal Lines

Reconstruction of Orthogonal Polygonal Lines Recostructo of Orthogoal Polygoal Les Alexader Grbov ad Eugee Bodasky Evrometal System Research Isttute (ESRI) 380 New ork St. Redlads CA 9373-800 USA {agrbov ebodasky}@esr.com Abstract. A orthogoal polygoal

More information

Clustering documents with vector space model using n-grams

Clustering documents with vector space model using n-grams Clusterg documets wth vector space model usg -grams Klas Skogmar, d97ksk@efd.lth.se Joha Olsso, d97jo@efd.lth.se Lud Isttute of Techology Supervsed by: Perre Nugues, Perre.Nugues@cs.lth.se Abstract Ths

More information

DEEP (Displacement Estimation Error Back-Propagation) Method for Cascaded ViSPs (Visually Servoed Paired Structured Light Systems)

DEEP (Displacement Estimation Error Back-Propagation) Method for Cascaded ViSPs (Visually Servoed Paired Structured Light Systems) DEEP (Dsplacemet Estmato Error Back-Propagato) Method for Cascaded VSPs (Vsually Servoed Pared Structured Lght Systems) Haem Jeo 1), Jae-Uk Sh 2), Wachoel Myeog 3), Yougja Km 4), ad *Hyu Myug 5) 1), 3),

More information

Towards Green Cloud Computing: Demand Allocation and Pricing Policies for. Cloud service brokerage.

Towards Green Cloud Computing: Demand Allocation and Pricing Policies for. Cloud service brokerage. 15 IEEE Iteratoal Coferece o Bg Data (Bg Data) Towards Gree Cloud Computg: Demad Allocato ad Prcg Polces for Cloud Servce Broerage Chex Qu, Hayg She ad Luhua Che Departmet of Electrcal ad Computer Egeerg

More information

Descriptive Statistics: Measures of Center

Descriptive Statistics: Measures of Center Secto 2.3 Descrptve Statstcs: Measures of Ceter Frequec dstrbutos are helpful provdg formato about categorcal data, but wth umercal data we ma wat more formato. Statstc: s a umercal measure calculated

More information

A New Newton s Method with Diagonal Jacobian Approximation for Systems of Nonlinear Equations

A New Newton s Method with Diagonal Jacobian Approximation for Systems of Nonlinear Equations Joural of Mathematcs ad Statstcs 6 (3): 46-5, ISSN 549-3644 Scece Publcatos A New Newto s Method wth Dagoal Jacoba Appromato for Systems of Nolear Equatos M.Y. Wazr, W.J. Leog, M.A. Hassa ad M. Mos Departmet

More information

Vertex Odd Divisor Cordial Labeling of Graphs

Vertex Odd Divisor Cordial Labeling of Graphs IJISET - Iteratoal Joural of Iovatve Scece, Egeerg & Techology, Vol. Issue 0, October 0. www.jset.com Vertex Odd Dvsor Cordal Labelg of Graphs ISSN 48 68 A. Muthaya ad P. Pugaleth Assstat Professor, P.G.

More information

NEURO FUZZY MODELING OF CONTROL SYSTEMS

NEURO FUZZY MODELING OF CONTROL SYSTEMS NEURO FUZZY MODELING OF CONTROL SYSTEMS Efré Gorrosteta, Carlos Pedraza Cetro de Igeería y Desarrollo Idustral CIDESI, Av Pe de La Cuesta 70. Des. Sa Pablo. Querétaro, Qro, Méxco gorrosteta@teso.mx pedraza@cdes.mx

More information

A Genetic K-means Clustering Algorithm Applied to Gene Expression Data

A Genetic K-means Clustering Algorithm Applied to Gene Expression Data A Geetc K-meas Clusterg Algorthm Appled to Gee Expresso Data Fag-Xag Wu, W. J. Zhag, ad Athoy J. Kusal Dvso of Bomedcal Egeerg, Uversty of Sasatchewa, Sasatoo, S S7N 5A9, CANADA faw34@mal.usas.ca, zhagc@egr.usas.ca

More information

Biconnected Components

Biconnected Components Presetato for use wth the textbook, Algorthm Desg ad Applcatos, by M. T. Goodrch ad R. Tamassa, Wley, 2015 Bcoected Compoets SEA PVD ORD FCO SNA MIA 2015 Goodrch ad Tamassa Bcoectvty 1 Applcato: Networkg

More information

Topology Design for Directional Range Extension Networks with Antenna Blockage

Topology Design for Directional Range Extension Networks with Antenna Blockage Topology Desg for Drectoal Rage Exteso etworks wth Atea Blockage Thomas Shake MIT Lcol Laboratory shake@ll.mt.edu Abstract Extedg the rage of local area surface etworks by usg small arcraft to relay traffc

More information

Curve Modeling NURBS. Dr. S.M. Malaek. Assistant: M. Younesi

Curve Modeling NURBS. Dr. S.M. Malaek. Assistant: M. Younesi Crve Modelg NURBS Dr. S.M. Malaek Assstat: M. Yoes Motvato Motvato We eed more cotrol over the crve Desg Sketch Motvato Redered Motvato Motvato Fal Physcal Prodct Motvato Dfferet eghts of cotrol ots Motvato

More information

Weighting Cache Replace Algorithm for Storage System

Weighting Cache Replace Algorithm for Storage System Weghtg Cache Replace Algorthm for Storage System Yhu Luo 2 Chagsheg Xe 2 Chegfeg Zhag 2 School of mathematcs ad Computer Scece, Hube Uversty, Wuha 430062, P.R. Cha 2 Natoal Storage System Laboratory, School

More information

ANALYSIS OF VARIANCE WITH PARETO DATA

ANALYSIS OF VARIANCE WITH PARETO DATA Proceedgs of the th Aual Coferece of Asa Pacfc Decso Sceces Isttute Hog Kog, Jue -8, 006, pp. 599-609. ANALYSIS OF VARIANCE WITH PARETO DATA Lakhaa Watthaacheewakul Departmet of Mathematcs ad Statstcs,

More information

SVM Classification Method Based Marginal Points of Representative Sample Sets

SVM Classification Method Based Marginal Points of Representative Sample Sets P P College P P College P Iteratoal Joural of Iformato Techology Vol. No. 9 005 SVM Classfcato Method Based Margal Pots of Represetatve Sample Sets Wecag ZhaoP P, Guagrog JP P, Ru NaP P, ad Che FegP of

More information

Constructive Semi-Supervised Classification Algorithm and Its Implement in Data Mining

Constructive Semi-Supervised Classification Algorithm and Its Implement in Data Mining Costructve Sem-Supervsed Classfcato Algorthm ad Its Implemet Data Mg Arvd Sgh Chadel, Arua Twar, ad Naredra S. Chaudhar Departmet of Computer Egg. Shr GS Ist of Tech.& Sc. SGSITS, 3, Par Road, Idore (M.P.)

More information

Estimating Feasibility Using Multiple Surrogates and ROC Curves

Estimating Feasibility Using Multiple Surrogates and ROC Curves Estmatg Feasblty Usg Multple Surrogates ad ROC Curves Arba Chaudhur * Uversty of Florda, Gaesvlle, Florda, 3601 Rodolphe Le Rche École Natoale Supéreure des Mes de Sat-Étee, Sat-Étee, Frace ad CNRS LIMOS

More information

Self-intersection Avoidance for 3-D Triangular Mesh Model

Self-intersection Avoidance for 3-D Triangular Mesh Model Self-tersecto Avodace for 3-D Tragular Mesh Model Habtamu Masse Aycheh 1) ad M Ho Kyug ) 1) Departmet of Computer Egeerg, Ajou Uversty, Korea, ) Departmet of Dgtal Meda, Ajou Uversty, Korea, 1) hab01@ajou.ac.kr

More information

An Efficient Approach to Mining Frequent Itemsets on Data Streams

An Efficient Approach to Mining Frequent Itemsets on Data Streams A Effcet Approach to Mg Frequet Itemsets o Data Streams Sara Asar, ad Mohammad Had Sadredd Abstract The creasg mportace of data stream arsg a wde rage of advaced applcatos has led to the extesve study

More information

Using The ACO Algorithm in Image Segmentation for Optimal Thresholding 陳香伶財務金融系

Using The ACO Algorithm in Image Segmentation for Optimal Thresholding 陳香伶財務金融系 教專研 95P- Usg The ACO Algorthm Image Segmetato for Optmal Thresholdg Abstract Usg The ACO Algorthm Image Segmetato for Optmal Thresholdg 陳香伶財務金融系 Despte the fact that the problem of thresholdg has bee qute

More information

An Enhanced Local Covering Approach for Minimization of Multiple-Valued Input Binary-Valued Output Functions

An Enhanced Local Covering Approach for Minimization of Multiple-Valued Input Binary-Valued Output Functions Proceedgs of the 10th WSEAS Iteratoal Coferece o COMPUTERS, Voulagme, Athes, Greece, July 13-15, 2006 (pp63-68) A Ehaced Local Coverg Approach for Mmzato of Multple-Valued Iput Bary-Valued Output Fuctos

More information

Airline Fleet Routing and Flight Scheduling under Market Competitions. Tang and Ming-Chei

Airline Fleet Routing and Flight Scheduling under Market Competitions. Tang and Ming-Chei Arle Fleet Routg ad Flght Schedulg uder Market Compettos Shagyao Ya, Ch-Hu Tag ad Mg-Che Lee Departmet of Cvl Egeerg, Natoal Cetral Uversty 3/12/2009 Itroducto Lterature revew The model Soluto method Numercal

More information

Computer Aided Drafting, Design and Manufacturing Volume 26, Number 2, June 2016, Page 1

Computer Aided Drafting, Design and Manufacturing Volume 26, Number 2, June 2016, Page 1 Computer Aded Draftg, Desg ad Maufacturg Volume 26, Number 2, Jue 2016, Page 1 CADDM Road etwork extracto from hgh resoluto satellte mages L Gag 1,3, La Shua 2, L Sheg 2,3 1. Pekg Uversty Shezhe Graduate

More information

Area and Power Efficient Modulo 2^n+1 Multiplier

Area and Power Efficient Modulo 2^n+1 Multiplier Iteratoal Joural of Moder Egeerg Research (IJMER) www.jmer.com Vol.3, Issue.3, May-Jue. 013 pp-137-1376 ISSN: 49-6645 Area ad Power Effcet Modulo ^+1 Multpler K. Ptambar Patra, 1 Saket Shrvastava, Sehlata

More information

SALAM A. ISMAEEL Computer Man College for Computer Studies, Khartoum / Sudan

SALAM A. ISMAEEL Computer Man College for Computer Studies, Khartoum / Sudan AAPTIVE HYBRI-WAVELET ETHO FOR GPS/ SYSTE INTEGRATION SALA A. ISAEEL Computer a College for Computer Studes, Khartoum / Suda salam.smaeel@gmal.com ABSTRACT I ths paper, a techque for estmato a global postog

More information

Workflow- Based Shape Optimization of Airfoils and Blades using Chained Bezier Curves

Workflow- Based Shape Optimization of Airfoils and Blades using Chained Bezier Curves Workflow- Based Shape Optmzato of Arfols ad Blades usg Chaed Bezer Curves Igor Pehec, Damr Vuča, Želja Loza Faculty of Electrcal Egeerg, Mechacal Egeerg ad Naval Archtecture FESB, Uversty of Splt, Croata

More information

Optimization of Light Switching Pattern on Large Scale using Genetic Algorithm

Optimization of Light Switching Pattern on Large Scale using Genetic Algorithm Optmzato of Lght Swtchg Patter o Large Scale usg Geetc Algorthm Pryaka Sambyal, Pawaesh Abrol 2, Parvee Lehaa 3,2 Departmet of Computer Scece & IT 3 Departmet of Electrocs Uversty of Jammu, Jammu, J&K,

More information

Reflection models. Rendering equation. Taxonomy 2. Taxonomy 1. Digital Image Synthesis Yung-Yu Chuang 11/01/2005

Reflection models. Rendering equation. Taxonomy 2. Taxonomy 1. Digital Image Synthesis Yung-Yu Chuang 11/01/2005 Rederg equato Reflecto models Dgtal Image Sythess Yug-Yu Chuag 11/01/005 wth sldes by Pat Haraha ad Matt Pharr Taxoomy 1 ( xyt,,, θ, φλ, ) ( xyt,,, θφλ,, ) Geeral fucto = 1D Scatterg fucto = 9D out Assume

More information

Impact of Mobility Prediction on the Temporal Stability of MANET Clustering Algorithms *

Impact of Mobility Prediction on the Temporal Stability of MANET Clustering Algorithms * Impact of Moblty Predcto o the Temporal Stablty of MANET Clusterg Algorthms * Aravdha Vekateswara, Vekatesh Saraga, Nataraa Gautam 1, Ra Acharya Departmet of Comp. Sc. & Egr. Pesylvaa State Uversty Uversty

More information

Microelectronics Journal

Microelectronics Journal Mcroelectrocs Joural () otets lsts avalable at ScVerse SceceDrect Mcroelectrocs Joural joural homepage: www.elsever.com/locate/mejo Mult-aggressor capactve ad ductve couplg ose modelg ad mtgato Vctora

More information

Reliable Surface Extraction from Point-Clouds using Scanner-Dependent Parameters

Reliable Surface Extraction from Point-Clouds using Scanner-Dependent Parameters 1 Relable Surface Extracto from Pot-Clouds usg Scaer-Depedet Parameters Hrosh Masuda 1, Ichro Taaka 2, ad Masakazu Eomoto 3 1 The Uversty of Tokyo, masuda@sys.t.u-tokyo.ac.jp 2 Tokyo Dek Uversty, taaka@cck.deda.ac.jp

More information

Probabilistic properties of topologies of finite metric spaces minimal fillings.

Probabilistic properties of topologies of finite metric spaces minimal fillings. arxv:308.656v [math.mg] Aug 03 Probablstc propertes of topologes of fte metrc spaces mmal fllgs. Vsevolod Salkov Abstract I ths work we provde a way to troduce a probablty measure o the space of mmal fllgs

More information

Designing a learning system

Designing a learning system CS 75 Mache Leafrg Lecture 3 Desgg a learg system Mlos Hauskrecht mlos@cs.ptt.edu 539 Seott Square, x4-8845 people.cs.ptt.edu/~mlos/courses/cs75/ Homeork assgmet Homeork assgmet ll be out today To parts:

More information

Cubic fuzzy H-ideals in BF-Algebras

Cubic fuzzy H-ideals in BF-Algebras OSR Joural of Mathematcs (OSR-JM) e-ssn: 78-578 p-ssn: 39-765X Volume ssue 5 Ver (Sep - Oct06) PP 9-96 wwwosrjouralsorg Cubc fuzzy H-deals F-lgebras Satyaarayaa Esraa Mohammed Waas ad U du Madhav 3 Departmet

More information

Signal Classification Method Based on Support Vector Machine and High-Order Cumulants

Signal Classification Method Based on Support Vector Machine and High-Order Cumulants Wreless Sesor Network,,, 48-5 do:.46/ws..7 Publshed Ole Jauary (http://www.scrp.org/joural/ws/). Sgal Classfcato Method Based o Support Vector Mache ad Hgh-Order Cumulats Abstract X ZHOU, Yg WU, B YANG

More information

Spatial Error Concealment Based on Bezier Curves Ocultamiento de Errores Espacial Mediante Curvas de Bezier

Spatial Error Concealment Based on Bezier Curves Ocultamiento de Errores Espacial Mediante Curvas de Bezier Computacó y Sstemas Vol. 9 Núm. 3, pp. 256-269 2006, CIC-IPN, ISSN 1405-5546, Impreso e Méxco Ocultameto de Errores Espacal Medate Curvas de Bezer Rogelo Hasmoto-Beltrá 1 ad Ashfaq A. Khokhar 2 1 Cetro

More information

Improved MOPSO Algorithm Based on Map-Reduce Model in Cloud Resource Scheduling

Improved MOPSO Algorithm Based on Map-Reduce Model in Cloud Resource Scheduling Improved MOPSO Algorthm Based o Map-Reduce Model Cloud Resource Schedulg Heg-We ZHANG, Ka NIU *, J-Dog WANG, Na WANG Zhegzhou Isttute of Iformato Scece ad Techology, Zhegzhou 45000, Cha State Key Laboratory

More information

NUMERICAL INTEGRATION BY GENETIC ALGORITHMS. Vladimir Morozenko, Irina Pleshkova

NUMERICAL INTEGRATION BY GENETIC ALGORITHMS. Vladimir Morozenko, Irina Pleshkova 5 Iteratoal Joural Iformato Theores ad Applcatos, Vol., Number 3, 3 NUMERICAL INTEGRATION BY GENETIC ALGORITHMS Vladmr Morozeko, Ira Pleshkova Abstract: It s show that geetc algorthms ca be used successfully

More information

Adaptive Clustering Algorithm for Mining Subspace Clusters in High-Dimensional Data Stream *

Adaptive Clustering Algorithm for Mining Subspace Clusters in High-Dimensional Data Stream * ISSN 673-948 CODEN JKYTA8 E-mal: fcst@vp.63.com Joural of Froters of Computer Scece ad Techology http://www.ceaj.org 673-948/200/04(09)-0859-06 Tel: +86-0-566056 DOI: 0.3778/j.ss.673-948.200.09.009 *,2,

More information

A MapReduce-Based Multiple Flow Direction Runoff Simulation

A MapReduce-Based Multiple Flow Direction Runoff Simulation A MapReduce-Based Multple Flow Drecto Ruoff Smulato Ahmed Sdahmed ad Gyozo Gdofalv GeoIformatcs, Urba lag ad Evromet, KTH Drottg Krstas väg 30 100 44 Stockholm Telephoe: +46-8-790 8709 Emal:{sdahmed, gyozo}@

More information

Integrated fault diagnosis method for down-hole working conditions of the beam pumping unit

Integrated fault diagnosis method for down-hole working conditions of the beam pumping unit Itegrated fault dagoss method for dow-hole workg codtos of the beam pumpg ut Ha Yg, L Ku College of Egeerg, Boha Uversty, Jzhou 203, Cha. E-mal: fegya326@alyu.com Abstract: The Dyamometer card s commoly

More information

Electrocardiogram Classification Method Based on SVM

Electrocardiogram Classification Method Based on SVM Electrocardogram Classfcato Method Based o SVM Xao Tag Zhwe Mo College of mathematcs ad software scece, Schua ormal uversty, Chegdu 60066, P. R. Cha Abstract Heart dsease s oe of the ma dseases threateg

More information

An Improved Fuzzy C-Means Clustering Algorithm Based on Potential Field

An Improved Fuzzy C-Means Clustering Algorithm Based on Potential Field 07 d Iteratoal Coferece o Advaces Maagemet Egeerg ad Iformato Techology (AMEIT 07) ISBN: 978--60595-457-8 A Improved Fuzzy C-Meas Clusterg Algorthm Based o Potetal Feld Yua-hag HAO, Zhu-chao YU *, X GAO

More information

Multiobjective Space Search Optimization and Information Granulation in the Design of Fuzzy Radial Basis Function Neural Networks

Multiobjective Space Search Optimization and Information Granulation in the Design of Fuzzy Radial Basis Function Neural Networks 636 Joural of Electrcal Egeerg & Techology Vol. 7, No. 4, pp. 636~645, http://dx.do.org/.537/jeet..7.4.636 ultobjectve Space Search Optmzato ad Iformato Graulato the Desg of Fuzzy Radal Bass Fucto Neural

More information

Linear Interval Estimations - A New Kind of Bounding Volumes for Implicit and Parametric Objects

Linear Interval Estimations - A New Kind of Bounding Volumes for Implicit and Parametric Objects Lear Iterval Estatos - A New Kd of Boudg Volues for Iplct ad Paraetrc Objects VRVs Research Ceter for Vrtual Realty ad Vsualzato Vea Austra Sear o Nuercal Software wth Result Verfcato Dagstuhl 9.-24..2003

More information

Performance Impact of Load Balancers on Server Farms

Performance Impact of Load Balancers on Server Farms erformace Impact of Load Balacers o Server Farms Ypg Dg BMC Software Server Farms have gaed popularty for provdg scalable ad relable computg / Web servces. A load balacer plays a key role ths archtecture,

More information

Parallel Iterative Poisson Solver for a Distributed Memory Architecture

Parallel Iterative Poisson Solver for a Distributed Memory Architecture Parallel Iteratve Posso Solver for a Dstrbted Memory Archtectre Erc Dow Aerospace Comptatoal Desg Lab Departmet of Aeroatcs ad Astroatcs 2 Motvato Solvg Posso s Eqato s a commo sbproblem may mercal schemes

More information

ADAPTIVE WEB CACHING WITH INTERPOLATION AND WEB USAGE PATTERNS

ADAPTIVE WEB CACHING WITH INTERPOLATION AND WEB USAGE PATTERNS VOL. 0, NO., FEBRUARY 05 ISSN 89-08 ARPN Joural of Egeerg ad Appled Sceces 00-05 Asa Research Publshg Network (ARPN). All rghts reserved. www.arpjourals.com ADAPTIVE WEB CACHING WITH INTERPOLATION AND

More information

Mode Changes in Priority Pre-emptively Scheduled Systems. K. W. Tindell, A. Burns, A. J. Wellings

Mode Changes in Priority Pre-emptively Scheduled Systems. K. W. Tindell, A. Burns, A. J. Wellings ode hages rorty re-emptvely Scheduled Systems. W. dell, A. Burs, A.. Wellgs Departmet of omputer Scece, Uversty of York, Eglad Abstract may hard real tme systems the set of fuctos that a system s requred

More information

Approximation of Curves Contained on the Surface by Freed-Forward Neural Networks

Approximation of Curves Contained on the Surface by Freed-Forward Neural Networks Appromato of Curves Cotaed o the Surface by Freed-Forward Neural Networks Zheghua Zhou ad Jawe Zhao Departmet of formato ad mathematcs Sceces Cha Jlag Uversty, Hagzhou, 3008, Cha zzhzjw003@63.com Abstract.

More information

Estimation of Co-efficient of Variation in PPS sampling.

Estimation of Co-efficient of Variation in PPS sampling. It. Statstcal Ist.: Proc. 58th World Statstcal Cogress, 0, Dubl (Sesso CPS00) p.409 Estmato of Co-effcet of Varato PPS samplg. Archaa. V ( st Author) Departmet of Statstcs, Magalore Uverst Magalagagotr,

More information

APPLICATION OF CLUSTERING METHODS IN BANK S PROPENSITY MODEL

APPLICATION OF CLUSTERING METHODS IN BANK S PROPENSITY MODEL APPLICATION OF CLUSTERING METHODS IN BANK S PROPENSITY MODEL Sergej Srota Haa Řezaková Abstract Bak s propesty models are beg developed for busess support. They should help to choose clets wth a hgher

More information

2 General Regression Neural Network (GRNN)

2 General Regression Neural Network (GRNN) 4 Geeral Regresso Neural Network (GRNN) GRNN, as proposed b oald F. Specht [Specht 9] falls to the categor of probablstc eural etworks as dscussed Chapter oe. Ths eural etwork lke other probablstc eural

More information

Some Results on Vertex Equitable Labeling

Some Results on Vertex Equitable Labeling Ope Joural of Dscrete Mathematcs, 0,, 5-57 http://dxdoorg/0436/odm0009 Publshed Ole Aprl 0 (http://wwwscrporg/oural/odm) Some Results o Vertex Equtable Labelg P Jeyath, A Maheswar Research Cetre, Departmet

More information

Fuzzy Partition based Similarity Measure for Spectral Clustering. Xi an , China Abstract

Fuzzy Partition based Similarity Measure for Spectral Clustering. Xi an , China Abstract Iteratoal Joural of Sgal Processg, Image Processg ad Patter Recogto Vol.9, No., (6), pp.47-48 http://dx.do.org/.457/sp.6.9..39 Fuzzy Partto based Smlarty Measure for Spectral Clusterg Yfag Yag ad Yupg

More information

Summary of Curve Smoothing Technology Development

Summary of Curve Smoothing Technology Development RESEARCH ARTICLE Summary of Curve Smoothg Techology Developmet Wu Yze,ZhagXu,Jag Mgyag (College of Mechacal Egeerg, Shagha Uversty of Egeerg Scece, Shagha, Cha) Abstract: Wth the cotuous developmet of

More information

REVISTA INVESTIGACION OPERACIONAL Vol. 23, No. 1, 2002

REVISTA INVESTIGACION OPERACIONAL Vol. 23, No. 1, 2002 REVISTA INVESTIGACION OERACIONAL Vol. 3, No., FITTING A CONIC A-SLINE TO CONTOUR IMAGE DATA V. Herádez Mederos, D. Martíez Morera y J. Estrada Sarlabous 3 Isttuto de Cberétca, Matemátca y Físca, ICIMAF,

More information

FITTING A POINT CLOUD TO A 3D POLYHEDRAL SURFACE

FITTING A POINT CLOUD TO A 3D POLYHEDRAL SURFACE The Iteratoal Archves of the Photogrammetry, Remote Sesg ad Spatal Iformato Sceces, Volume XLII-/W4, 07 d Iteratoal ISPRS Workshop o PS, 5 7 May 07, Moscow, Russa FITTING A POINT CLOUD TO A 3D POLYHEDRAL

More information

Meshfree Analysis Using the Generalized Meshfree (GMF) Approximation

Meshfree Analysis Using the Generalized Meshfree (GMF) Approximation 11 th Iteratoal LS-DYNA Users Coferece Smulato (4) Meshfree Aalyss Usg the Geeralzed Meshfree (GMF) Approxmato Chug-Kyu Park *, Cheg-Tag Wu ** ad Cg-Dao (Steve) Ka * * Natoal Crash Aalyss Ceter (NCAC),

More information

Analysis of Energy Consumption and Lifetime of Heterogeneous Wireless Sensor Networks

Analysis of Energy Consumption and Lifetime of Heterogeneous Wireless Sensor Networks Aalyss of Eergy Cosumpto ad Lfetme of Heterogeeous Wreless Sesor Networks Erque J. Duarte-Melo, Mgya Lu EECS, Uversty of Mchga, A Arbor ejd, mgya @eecs.umch.edu Abstract The paper exames the performace

More information

Journal of Chemical and Pharmaceutical Research, 2016, 8(4): Research Article. Learning Methods of Radial Basis Function Neural Network

Journal of Chemical and Pharmaceutical Research, 2016, 8(4): Research Article. Learning Methods of Radial Basis Function Neural Network Avalable ole www.jocpr.com Joural of Chemcal ad Pharmaceutcal Research, 2016, 8(4):457-461 Research Artcle ISSN : 0975-7384 CODEN(USA) : JCPRC5 Learg Methods of Radal Bass Fucto Neural Network Wedog J

More information

Normal Distributions

Normal Distributions Normal Distributios Stacey Hacock Look at these three differet data sets Each histogram is overlaid with a curve : A B C A) Weights (g) of ewly bor lab rat pups B) Mea aual temperatures ( F ) i A Arbor,

More information

Marcus Gallagher School of Information Technology and Electrical Engineering The University of Queensland QLD 4072, Australia

Marcus Gallagher School of Information Technology and Electrical Engineering The University of Queensland QLD 4072, Australia O the Importace of Dversty Mateace Estmato of Dstrbuto Algorthms Bo Yua School of Iformato Techology ad Electrcal Egeerg The Uversty of Queeslad QLD 4072, Australa +6-7-3365636 boyua@tee.uq.edu.au Marcus

More information

Research on Circular Target Center Detection Algorithm Based on Morphological Algorithm and Subpixel Method

Research on Circular Target Center Detection Algorithm Based on Morphological Algorithm and Subpixel Method Research o Crcular Target Ceter Detecto Algorthm Based o Morphologcal Algorthm ad Subpxel Method Yu Le 1, Ma HuZhu 1, ad Yag Wezhou 1 1 College of Iformato ad Commucato Egeerg, Harb Egeerg Uversty, Harb

More information

Keywords: complete graph, coloursignlesslaplacian matrix, coloursignlesslaplacian energy of a graph.

Keywords: complete graph, coloursignlesslaplacian matrix, coloursignlesslaplacian energy of a graph. Amerca Iteratoal Joural of Research Scece, Techology, Egeerg & Mathematcs Avalable ole at http://www.asr.et ISSN (Prt): 38-3491, ISSN (Ole): 38-3580, ISSN (CD-ROM): 38-369 AIJRSTEM s a refereed, dexed,

More information

Adaptive Provisioning of Differentiated Services Networks based on Reinforcement Learning

Adaptive Provisioning of Differentiated Services Networks based on Reinforcement Learning Adaptve Provsog of Dfferetated Servces Networks based o Reforcemet Learg T C K Hu ad C K Tham Dept of Electrcal & Computer Egeerg Natoal Uversty of Sgapore to appear IEEE Trasactos o Systems, Ma & Cyberetcs

More information