Lecture 7: Multistage Logic Networks. Best Number of Stages

Size: px
Start display at page:

Download "Lecture 7: Multistage Logic Networks. Best Number of Stages"

Transcription

1 Lecture 7: Multstage Logc Networks Multstage Logc Networks (cont. from Lec 06) Examples Readng: Ch. Best Number of Stages How many stages should a path use? Mnmzng number of stages s not always fastest Example: drve 6-bt datapath wth unt nverter Intal Drver D = NF /N + P = N(6) /N + N F=GBH B= H=6 G= Datapath Load N: f: D: Fastest

2 Best Stage Effort Dervaton Consder addng nverters to end of path How many gve least delay? N n = ( ) D= NF + p + N n p D N N N = F ln F + F + pnv = 0 N Defne best stage effort ρ = F N p + ρ lnρ = 0 nv ( ) Logc Block: n Stages Path Effort F N - n Ex tra Inv erters Neglectng parastcs (p nv = 0), we fnd ρ = 2.78 (e) For p nv =, solve numercally for ρ = 3.59 nv No closed-form soluton Senstvty Analyss How senstve s delay to usng exactly the best number of stages?.6.5 D(N) /D(N) (ρ=6) (ρ =2.) < ρ < 6 gves delay wthn 5% of optmal We can be sloppy! I lke ρ = N / N 2

3 Example: extractng logcal effort from datasheets INVX Determne p, g and τ for INVX from datasheet Unt nverter capactance s 3.6fF Parastc or ntrnsc delay s ( )/2=20ps Slope of delay vs. load capactance s the average of rsng and fallng K load values ( )/2 ns/pf Normalzed Delay: d Recall d abs = (gh+p) τ nput NAND Electrcal Ef f ort: h = C out / C n Inverter g = /3 p = 2 d = (/3)h + 2 g = p = d = h + Ef f ort Delay: f Parastc Delay: p t pd = 20ps + (3.6fF/gate)(h gates)[( )/2 ns/pf] = (20ps + 2.h) ps = tau (20ps/tau + (2./tau)h) p nv = 20ps/2.ps =.6 g==2./tau à tau=2. d=(gh+p)=(h+.6) 3

4 NAND2 Determne p, g and τ for NAND2X from datasheet Unt NAND2X capactance s.2ff Parastc or ntrnsc delay s ( )/2 Slope of delay vs. load capactance s the average of rsng and fallng K load values ( )/2 ns/pf Normalzed Delay: d Recall d abs = (gh+p) τ nput NAND Electrcal Ef f ort: h = C out / C n Inverter g = /3 p = 2 d = (/3)h + 2 g = p = d = h + Ef f ort Delay: f Parastc Delay: p t pd = ( )/2 + (.2fF/gate)(h gates)[( )/2 ns/pf] = (25.ps + 5.5h) ps p nv = 25.ps/2.ps = 2.05 g=5.5/tau=.25=5/ Example Ben Btdddle s the memory desgner for the Motorol 68W86, an embedded automotve processor. Help Ben desgn the decoder for a regster fle. A[3:0] A[3:0] 32 bts Decoder specfcatons: 6 word regster fle Each word s 32 bts wde Each bt presents load of 3 unt-szed transstors True and complementary address nputs A[3:0] Each nput may drve 0 unt-szed transstors Ben needs to decde: How many stages to use? How large should each gate be? How fast can decoder operate? :6 Decoder 6 Regster Fle 6 words

5 Intal Dlema You need the path effort to calculate the optmum number of stages N = log ρ F You need the path logcal effort to calculate the path effort F = f = gh = GBH From ρ=f /N Stage effort ρ=3- Wthout knowng the number of stages you cannot draw a path, determne the logcal effort of the path and fnd the path effort G= g Number of Stages Decoder effort s manly electrcal and branchng Electrcal Effort: H = (32*3) / 0 = 9.6 Branchng Effort: B = 8 If we neglect logcal effort (assume G = ) Path Effort: F = GBH = 76.8 Number of Stages: N = log F = 3. Try a 3-stage decoder desgn Each address s used to compute Half of the 6 word lnes; ts Complement Is used for the other half

6 Delay Logcal Effort: G = * 6/3 * = 2 Path Effort: F = GBH = 2*8*9.6=5 Stage Effort: /3 f ˆ = F = 5.36 Path Delay: D= 3fˆ = 22. A[3] A[3] A[2] A[2] A[] A[] A[0] A[0] y z word[0] 96 unts of wordlne capactance y z word[5] Gate Szes & Delay Gate szes: z = 96*/5.36 = 8 y = 8*2/5.36 = 6.7 fˆ = gh = g C C out n gc Cn = fˆ out A[3] A[3] A[2] A[2] A[] A[] A[0] A[0] y z word[0] 96 unts of wordlne capactance y z word[5] 6

7 Comparson Compare many alternatves wth a spreadsheet Desgn N G P D NAND-INV NAND2-NOR2 2 20/9 30. INV-NAND-INV NAND-INV-INV-INV NAND2-NOR2-INV-INV 20/ NAND2-INV-NAND2-INV 6/ INV-NAND2-INV-NAND2-INV 5 6/ NAND2-INV-NAND2-INV-INV-INV 6 6/ Revew of Defntons Term Stage Path number of stages logcal effort electrcal effort branchng effort effort effort delay parastc delay delay g h = b = Cout Cn Con-path + Coff-path Con-path f = gh f p d = f + p N G= g H = Cout-path Cn-path B= b F = GBH D F = f P= p D = d = D + P F 7

8 Method of Logcal Effort ) Compute path effort 2) Estmate best number of stages 3) Sketch path wth N stages ) Estmate least delay 5) Determne best stage effort F = GBH N = log F N D= NF + P ˆ N f = F 6) Fnd gate szes C n = gc fˆ out Lmts of Logcal Effort Chcken and egg problem Need path to compute G But don t know number of stages wthout G Smplstc delay model Neglects nput rse tme effects Interconnect Iteraton requred n desgns wth wre Maxmum speed only Not mnmum area/power for constraned delay 8

9 Summary Logcal effort s useful for thnkng of delay n crcuts Numerc logcal effort characterzes gates NANDs are faster than NORs n CMOS Paths are fastest when effort delays are ~ Path delay s weakly senstve to stages, szes But usng fewer stages doesn t mean faster paths Delay of path s about log F FO nverter delays (NxFO delay) Inverters and NAND2 best for drvng large caps 9

Logic effort and gate sizing

Logic effort and gate sizing EEN454 Dgtal Integrated rcut Desgn Logc effort and gate szng EEN 454 Introducton hp desgners face a bewlderng arra of choces What s the best crcut topolog for a functon? How man stages of logc gve least

More information

Estimating Delays. Gate Delay Model. Gate Delay. Effort Delay. Computing Logical Effort. Logical Effort

Estimating Delays. Gate Delay Model. Gate Delay. Effort Delay. Computing Logical Effort. Logical Effort Estmatng Delas Would be nce to have a back of the envelope method for szng gates for speed Logcal Effort ook b Sutherland, Sproull, Harrs Chapter s on our web page Gate Dela Model Frst, normalze a model

More information

Lecture 6: Logical Effort

Lecture 6: Logical Effort Lecture 6: Logical Effort Outline Logical Effort Delay in a Logic Gate Multistage Logic Networks Choosing the Best Number of Stages Example Summary Introduction Chip designers face a bewildering array

More information

EE 447 VLSI Design. Lecture 5: Logical Effort

EE 447 VLSI Design. Lecture 5: Logical Effort EE 447 VLSI Design Lecture 5: Logical Effort Outline Introduction Delay in a Logic Gate Multistage Logic Networks Choosing the Best Number of Stages Example Summary EE 4475: VLSI Logical Design Effort

More information

ECE429 Introduction to VLSI Design

ECE429 Introduction to VLSI Design ECE429 Introduction to VLSI Design Lecture 5: LOGICAL EFFORT Erdal Oruklu Illinois Institute of Technology Some of these slides have been adapted from the slides provided by David Harris, Harvey Mudd College

More information

Introduction to CMOS VLSI Design. Lecture 5: Logical Effort. David Harris. Harvey Mudd College Spring Outline

Introduction to CMOS VLSI Design. Lecture 5: Logical Effort. David Harris. Harvey Mudd College Spring Outline Introduction to CMOS VLSI Design Lecture 5: Logical Effort David Harris Harve Mudd College Spring 00 Outline Introduction Dela in a Logic Gate Multistage Logic Networks Choosing the Best Number of Stages

More information

VLSI Design, Fall Logical Effort. Jacob Abraham

VLSI Design, Fall Logical Effort. Jacob Abraham 6. Logical Effort 6. Logical Effort Jacob Abraham Department of Electrical and Computer Engineering The University of Texas at Austin VLSI Design Fall 207 September 20, 207 ECE Department, University of

More information

Introduction to CMOS VLSI Design. Logical Effort B. Original Lecture by Jay Brockman. University of Notre Dame Fall 2008

Introduction to CMOS VLSI Design. Logical Effort B. Original Lecture by Jay Brockman. University of Notre Dame Fall 2008 Introduction to CMOS VLSI Design Logical Effort Part B Original Lecture b Ja Brockman Universit of Notre Dame Fall 2008 Modified b Peter Kogge Fall 2010,2011,2015, 2018 Based on lecture slides b David

More information

Lecture 8: Combinational Circuit Design

Lecture 8: Combinational Circuit Design Lecture 8: Combinational Circuit Design Mark McDermott Electrical and Computer Engineering The University of Texas at ustin 9/5/8 Verilog to Gates module mux(input s, d0, d, output y); assign y = s? d

More information

Logical Effort. Sizing Transistors for Speed. Estimating Delays

Logical Effort. Sizing Transistors for Speed. Estimating Delays Logical Effort Sizing Transistors for Speed Estimating Delays Would be nice to have a back of the envelope method for sizing gates for speed Logical Effort Book by Sutherland, Sproull, Harris Chapter 1

More information

Logical Effort: Designing for Speed on the Back of an Envelope David Harris Harvey Mudd College Claremont, CA

Logical Effort: Designing for Speed on the Back of an Envelope David Harris Harvey Mudd College Claremont, CA Logical Effort: Designing for Speed on the Back of an Envelope David Harris David_Harris@hmc.edu Harvey Mudd College Claremont, CA Outline o Introduction o Delay in a Logic Gate o Multi-stage Logic Networks

More information

Logical Effort of Higher Valency Adders

Logical Effort of Higher Valency Adders Logcal Effort of gher Valency Adders Davd arrs arvey Mudd College E. Twelfth St. Claremont, CA Davd_arrs@hmc.edu Abstract gher valency parallel prefx adders reduce the number of logc levels at the expense

More information

Very Large Scale Integration (VLSI)

Very Large Scale Integration (VLSI) Very Large Scale Integration (VLSI) Lecture 4 Dr. Ahmed H. Madian Ah_madian@hotmail.com Dr. Ahmed H. Madian-VLSI Contents Delay estimation Simple RC model Penfield-Rubenstein Model Logical effort Delay

More information

7. Combinational Circuits

7. Combinational Circuits 7. Combinational Circuits Jacob Abraham Department of Electrical and Computer Engineering The University of Texas at Austin VLSI Design Fall 2017 September 25, 2017 ECE Department, University of Texas

More information

Lecture 8: Logic Effort and Combinational Circuit Design

Lecture 8: Logic Effort and Combinational Circuit Design Lecture 8: Logic Effort and Combinational Circuit Design Slides courtesy of Deming Chen Slides based on the initial set from David Harris CMOS VLSI Design Outline q Logical Effort q Delay in a Logic Gate

More information

( ) = ( ) + ( 0) ) ( )

( ) = ( ) + ( 0) ) ( ) EETOMAGNETI OMPATIBIITY HANDBOOK 1 hapter 9: Transent Behavor n the Tme Doman 9.1 Desgn a crcut usng reasonable values for the components that s capable of provdng a tme delay of 100 ms to a dgtal sgnal.

More information

How Strong Are Weak Patents? Joseph Farrell and Carl Shapiro. Supplementary Material Licensing Probabilistic Patents to Cournot Oligopolists *

How Strong Are Weak Patents? Joseph Farrell and Carl Shapiro. Supplementary Material Licensing Probabilistic Patents to Cournot Oligopolists * How Strong Are Weak Patents? Joseph Farrell and Carl Shapro Supplementary Materal Lcensng Probablstc Patents to Cournot Olgopolsts * September 007 We study here the specal case n whch downstream competton

More information

Grover s Algorithm + Quantum Zeno Effect + Vaidman

Grover s Algorithm + Quantum Zeno Effect + Vaidman Grover s Algorthm + Quantum Zeno Effect + Vadman CS 294-2 Bomb 10/12/04 Fall 2004 Lecture 11 Grover s algorthm Recall that Grover s algorthm for searchng over a space of sze wors as follows: consder the

More information

Chapter Newton s Method

Chapter Newton s Method Chapter 9. Newton s Method After readng ths chapter, you should be able to:. Understand how Newton s method s dfferent from the Golden Secton Search method. Understand how Newton s method works 3. Solve

More information

1.4 Small-signal models of BJT

1.4 Small-signal models of BJT 1.4 Small-sgnal models of J Analog crcuts often operate wth sgnal levels that are small compared to the bas currents and voltages n the crcut. Under ths condton, ncremental or small-sgnal models can be

More information

Coarse-Grain MTCMOS Sleep

Coarse-Grain MTCMOS Sleep Coarse-Gran MTCMOS Sleep Transstor Szng Usng Delay Budgetng Ehsan Pakbazna and Massoud Pedram Unversty of Southern Calforna Dept. of Electrcal Engneerng DATE-08 Munch, Germany Leakage n CMOS Technology

More information

Lecture 4: Adders. Computer Systems Laboratory Stanford University

Lecture 4: Adders. Computer Systems Laboratory Stanford University Lecture 4: Adders Computer Systems Laboratory Stanford Unversty horowtz@stanford.edu Copyrght 2004 by Mark Horowtz (w/ Fgures from Hgh-Performance Mcroprocessor Desgn IEEE And Fgures from Bora Nkolc 1

More information

Errors for Linear Systems

Errors for Linear Systems Errors for Lnear Systems When we solve a lnear system Ax b we often do not know A and b exactly, but have only approxmatons  and ˆb avalable. Then the best thng we can do s to solve ˆx ˆb exactly whch

More information

Stanford University CS359G: Graph Partitioning and Expanders Handout 4 Luca Trevisan January 13, 2011

Stanford University CS359G: Graph Partitioning and Expanders Handout 4 Luca Trevisan January 13, 2011 Stanford Unversty CS359G: Graph Parttonng and Expanders Handout 4 Luca Trevsan January 3, 0 Lecture 4 In whch we prove the dffcult drecton of Cheeger s nequalty. As n the past lectures, consder an undrected

More information

Basic Statistical Analysis and Yield Calculations

Basic Statistical Analysis and Yield Calculations October 17, 007 Basc Statstcal Analyss and Yeld Calculatons Dr. José Ernesto Rayas Sánchez 1 Outlne Sources of desgn-performance uncertanty Desgn and development processes Desgn for manufacturablty A general

More information

EE M216A.:. Fall Lecture 5. Logical Effort. Prof. Dejan Marković

EE M216A.:. Fall Lecture 5. Logical Effort. Prof. Dejan Marković EE M26A.:. Fall 200 Lecture 5 Logical Effort Prof. Dejan Marković ee26a@gmail.com Logical Effort Recap Normalized delay d = g h + p g is the logical effort of the gate g = C IN /C INV Inverter is sized

More information

AGC Introduction

AGC Introduction . Introducton AGC 3 The prmary controller response to a load/generaton mbalance results n generaton adjustment so as to mantan load/generaton balance. However, due to droop, t also results n a non-zero

More information

Abstract. The assumptions made for rank computation are as follows. (see Figure 1)

Abstract. The assumptions made for rank computation are as follows. (see Figure 1) A Novel Metrc for Interconnect Archtecture Performance Parthasarath Dasgupta, Andrew B. Kahng, and Swamy Muddu CSE Department, UCSD, La Jolla, CA 92093-0114 ECE Department, UCSD, La Jolla, CA 92093-0407

More information

V V. This calculation is repeated now for each current I.

V V. This calculation is repeated now for each current I. Page1 Page2 The power supply oltage V = +5 olts and the load resstor R = 1 k. For the range of collector bas currents, I = 0.5 ma, 1 ma, 2.5 ma, 4 ma and 4.5 ma, determne the correspondng collector-to-emtter

More information

EEL 6266 Power System Operation and Control. Chapter 3 Economic Dispatch Using Dynamic Programming

EEL 6266 Power System Operation and Control. Chapter 3 Economic Dispatch Using Dynamic Programming EEL 6266 Power System Operaton and Control Chapter 3 Economc Dspatch Usng Dynamc Programmng Pecewse Lnear Cost Functons Common practce many utltes prefer to represent ther generator cost functons as sngle-

More information

VQ widely used in coding speech, image, and video

VQ widely used in coding speech, image, and video at Scalar quantzers are specal cases of vector quantzers (VQ): they are constraned to look at one sample at a tme (memoryless) VQ does not have such constrant better RD perfomance expected Source codng

More information

Interconnect Optimization for Deep-Submicron and Giga-Hertz ICs

Interconnect Optimization for Deep-Submicron and Giga-Hertz ICs Interconnect Optmzaton for Deep-Submcron and Gga-Hertz ICs Le He http://cadlab.cs.ucla.edu/~hele UCLA Computer Scence Department Los Angeles, CA 90095 Outlne Background and overvew LR-based STIS optmzaton

More information

Module 9. Lecture 6. Duality in Assignment Problems

Module 9. Lecture 6. Duality in Assignment Problems Module 9 1 Lecture 6 Dualty n Assgnment Problems In ths lecture we attempt to answer few other mportant questons posed n earler lecture for (AP) and see how some of them can be explaned through the concept

More information

T E C O L O T E R E S E A R C H, I N C.

T E C O L O T E R E S E A R C H, I N C. T E C O L O T E R E S E A R C H, I N C. B rdg n g En g neern g a nd Econo mcs S nce 1973 THE MINIMUM-UNBIASED-PERCENTAGE ERROR (MUPE) METHOD IN CER DEVELOPMENT Thrd Jont Annual ISPA/SCEA Internatonal Conference

More information

Problem Set 9 Solutions

Problem Set 9 Solutions Desgn and Analyss of Algorthms May 4, 2015 Massachusetts Insttute of Technology 6.046J/18.410J Profs. Erk Demane, Srn Devadas, and Nancy Lynch Problem Set 9 Solutons Problem Set 9 Solutons Ths problem

More information

Transfer Characteristic

Transfer Characteristic Eeld-Effect Transstors (FETs 3.3 The CMS Common-Source Amplfer Transfer Characterstc Electronc Crcuts, Dept. of Elec. Eng., The Chnese Unersty of Hong Kong, Prof. K.-L. Wu Lesson 8&9 Eeld-Effect Transstors

More information

Logic Gate Sizing. The method of logical effort. João Canas Ferreira. March University of Porto Faculty of Engineering

Logic Gate Sizing. The method of logical effort. João Canas Ferreira. March University of Porto Faculty of Engineering Logic Gate Sizing The method of logical effort João Canas Ferreira University of Porto Faculty of Engineering March 016 Topics 1 Modeling CMOS Gates Chain of logic gates João Canas Ferreira (FEUP) Logic

More information

CS4495/6495 Introduction to Computer Vision. 3C-L3 Calibrating cameras

CS4495/6495 Introduction to Computer Vision. 3C-L3 Calibrating cameras CS4495/6495 Introducton to Computer Vson 3C-L3 Calbratng cameras Fnally (last tme): Camera parameters Projecton equaton the cumulatve effect of all parameters: M (3x4) f s x ' 1 0 0 0 c R 0 I T 3 3 3 x1

More information

ELCT 503: Semiconductors. Fall 2014

ELCT 503: Semiconductors. Fall 2014 EL503 Semconductors Fall 2014 Lecture 09: BJ rcut Analyss Dr. Hassan Mostafa د. حسن مصطفى hmostafa@aucegypt.edu EL 503: Semconductors ntroducton npn transstor pnp transstor EL 503: Semconductors ntroducton

More information

Graphical Analysis of a BJT Amplifier

Graphical Analysis of a BJT Amplifier 4/6/2011 A Graphcal Analyss of a BJT Amplfer lecture 1/18 Graphcal Analyss of a BJT Amplfer onsder agan ths smple BJT amplfer: ( t) = + ( t) O O o B + We note that for ths amplfer, the output oltage s

More information

Multilayer Perceptrons and Backpropagation. Perceptrons. Recap: Perceptrons. Informatics 1 CG: Lecture 6. Mirella Lapata

Multilayer Perceptrons and Backpropagation. Perceptrons. Recap: Perceptrons. Informatics 1 CG: Lecture 6. Mirella Lapata Multlayer Perceptrons and Informatcs CG: Lecture 6 Mrella Lapata School of Informatcs Unversty of Ednburgh mlap@nf.ed.ac.uk Readng: Kevn Gurney s Introducton to Neural Networks, Chapters 5 6.5 January,

More information

Lecture 9: Combinational Circuit Design

Lecture 9: Combinational Circuit Design Lecture 9: Combinational Circuit Design Outline Bubble Pushing Compound Gates Logical Effort Example Input Ordering symmetric Gates Skewed Gates Best P/N ratio 0: Combinational Circuits CMOS VLSI Design

More information

Design and Analysis of Algorithms

Design and Analysis of Algorithms Desgn and Analyss of Algorthms CSE 53 Lecture 4 Dynamc Programmng Junzhou Huang, Ph.D. Department of Computer Scence and Engneerng CSE53 Desgn and Analyss of Algorthms The General Dynamc Programmng Technque

More information

Physics 1202: Lecture 11 Today s Agenda

Physics 1202: Lecture 11 Today s Agenda Physcs 122: Lecture 11 Today s Agenda Announcements: Team problems start ths Thursday Team 1: Hend Ouda, Mke Glnsk, Stephane Auger Team 2: Analese Bruder, Krsten Dean, Alson Smth Offce hours: Monday 2:3-3:3

More information

18.1 Introduction and Recap

18.1 Introduction and Recap CS787: Advanced Algorthms Scrbe: Pryananda Shenoy and Shjn Kong Lecturer: Shuch Chawla Topc: Streamng Algorthmscontnued) Date: 0/26/2007 We contnue talng about streamng algorthms n ths lecture, ncludng

More information

PHYSICS - CLUTCH CH 28: INDUCTION AND INDUCTANCE.

PHYSICS - CLUTCH CH 28: INDUCTION AND INDUCTANCE. !! www.clutchprep.com CONCEPT: ELECTROMAGNETIC INDUCTION A col of wre wth a VOLTAGE across each end wll have a current n t - Wre doesn t HAVE to have voltage source, voltage can be INDUCED V Common ways

More information

University of Toronto. Final Exam

University of Toronto. Final Exam University of Toronto Final Exam Date - Apr 18, 011 Duration:.5 hrs ECE334 Digital Electronics Lecturer - D. Johns ANSWER QUESTIONS ON THESE SHEETS USING BACKS IF NECESSARY 1. Equation sheet is on last

More information

Copyright 2004 by Oxford University Press, Inc.

Copyright 2004 by Oxford University Press, Inc. JT as an Amplfer &a Swtch, Large Sgnal Operaton, Graphcal Analyss, JT at D, asng JT, Small Sgnal Operaton Model, Hybrd P-Model, TModel. Lecture # 7 1 Drecton of urrent Flow & Operaton for Amplfer Applcaton

More information

Announcements. Lecture #2

Announcements. Lecture #2 Announcements Lectures wll be n 4 LeConte begnnng Frday 8/29 Addtonal dscusson TA Denns Chang (Sectons 101, 105) Offce hours: Mo 2-3 PM; Th 5-6 PM Lab sectons begn Tuesday 9/2 Read Experment #1 onlne Download

More information

College of Engineering Department of Electronics and Communication Engineering. Test 1 With Model Answer

College of Engineering Department of Electronics and Communication Engineering. Test 1 With Model Answer Name: Student D Number: Secton Number: 01/0/03/04 A/B Lecturer: Dr Jamaludn/ Dr Jehana Ermy/ Dr Azn Wat Table Number: College of Engneerng Department of Electroncs and Communcaton Engneerng Test 1 Wth

More information

ELE B7 Power Systems Engineering. Power Flow- Introduction

ELE B7 Power Systems Engineering. Power Flow- Introduction ELE B7 Power Systems Engneerng Power Flow- Introducton Introducton to Load Flow Analyss The power flow s the backbone of the power system operaton, analyss and desgn. It s necessary for plannng, operaton,

More information

Module 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur

Module 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur Module 3 LOSSY IMAGE COMPRESSION SYSTEMS Verson ECE IIT, Kharagpur Lesson 6 Theory of Quantzaton Verson ECE IIT, Kharagpur Instructonal Objectves At the end of ths lesson, the students should be able to:

More information

Energy-Delay Space Exploration of Clocked Storage Elements Using Circuit Sizing

Energy-Delay Space Exploration of Clocked Storage Elements Using Circuit Sizing Energy-elay Space Exploraton of locked Storage Elements Usng rcut Szng Mustafa Aktan Svakumar Paramesvaran Joosk Moon Vojn Oklobdzja Electrcal Engneerng Rchardson, TX 75080 e-mal:aktanmus@utdallas.edu

More information

Outline and Reading. Dynamic Programming. Dynamic Programming revealed. Computing Fibonacci. The General Dynamic Programming Technique

Outline and Reading. Dynamic Programming. Dynamic Programming revealed. Computing Fibonacci. The General Dynamic Programming Technique Outlne and Readng Dynamc Programmng The General Technque ( 5.3.2) -1 Knapsac Problem ( 5.3.3) Matrx Chan-Product ( 5.3.1) Dynamc Programmng verson 1.4 1 Dynamc Programmng verson 1.4 2 Dynamc Programmng

More information

Linear regression. Regression Models. Chapter 11 Student Lecture Notes Regression Analysis is the

Linear regression. Regression Models. Chapter 11 Student Lecture Notes Regression Analysis is the Chapter 11 Student Lecture Notes 11-1 Lnear regresson Wenl lu Dept. Health statstcs School of publc health Tanjn medcal unversty 1 Regresson Models 1. Answer What Is the Relatonshp Between the Varables?.

More information

6.01: Introduction to EECS 1 Week 6 October 15, 2009

6.01: Introduction to EECS 1 Week 6 October 15, 2009 6.0: ntroducton to EECS Week 6 October 5, 2009 6.0: ntroducton to EECS Crcuts The Crcut Abstracton Crcuts represent systems as connectons of component through whch currents (through arables) flow and across

More information

Lecture 8 Modal Analysis

Lecture 8 Modal Analysis Lecture 8 Modal Analyss 16.0 Release Introducton to ANSYS Mechancal 1 2015 ANSYS, Inc. February 27, 2015 Chapter Overvew In ths chapter free vbraton as well as pre-stressed vbraton analyses n Mechancal

More information

Boise State University Department of Electrical and Computer Engineering ECE 212L Circuit Analysis and Design Lab

Boise State University Department of Electrical and Computer Engineering ECE 212L Circuit Analysis and Design Lab Bose State Unersty Department of Electrcal and omputer Engneerng EE 1L rcut Analyss and Desgn Lab Experment #8: The Integratng and Dfferentatng Op-Amp rcuts 1 Objectes The objectes of ths laboratory experment

More information

Math Review. CptS 223 Advanced Data Structures. Larry Holder School of Electrical Engineering and Computer Science Washington State University

Math Review. CptS 223 Advanced Data Structures. Larry Holder School of Electrical Engineering and Computer Science Washington State University Math Revew CptS 223 dvanced Data Structures Larry Holder School of Electrcal Engneerng and Computer Scence Washngton State Unversty 1 Why do we need math n a data structures course? nalyzng data structures

More information

I certify that I have not given unauthorized aid nor have I received aid in the completion of this exam.

I certify that I have not given unauthorized aid nor have I received aid in the completion of this exam. ME 270 Fall 2012 Fnal Exam Please revew the followng statement: I certfy that I have not gven unauthorzed ad nor have I receved ad n the completon of ths exam. Sgnature: INSTRUCTIONS Begn each problem

More information

IV. Performance Optimization

IV. Performance Optimization IV. Performance Optmzaton A. Steepest descent algorthm defnton how to set up bounds on learnng rate mnmzaton n a lne (varyng learnng rate) momentum learnng examples B. Newton s method defnton Gauss-Newton

More information

55:041 Electronic Circuits

55:041 Electronic Circuits 55:04 Electronc Crcuts Feedback & Stablty Sectons of Chapter 2. Kruger Feedback & Stablty Confguraton of Feedback mplfer S o S ε S o ( S β S ) o Negate feedback S S o + β β s the feedback transfer functon

More information

Calculation of time complexity (3%)

Calculation of time complexity (3%) Problem 1. (30%) Calculaton of tme complexty (3%) Gven n ctes, usng exhaust search to see every result takes O(n!). Calculaton of tme needed to solve the problem (2%) 40 ctes:40! dfferent tours 40 add

More information

Simultaneous Device and Interconnect Optimization

Simultaneous Device and Interconnect Optimization Smultaneous Devce and Interconnect Optmaton Smultaneous devce and wre sng Smultaneous buffer nserton and wre sng Smultaneous topology constructon, buffer nserton and wre sng WBA tree (student presentaton)

More information

Boise State University Department of Electrical and Computer Engineering ECE 212L Circuit Analysis and Design Lab

Boise State University Department of Electrical and Computer Engineering ECE 212L Circuit Analysis and Design Lab Bose State Unersty Department of Electrcal and omputer Engneerng EE 1L rcut Analyss and Desgn Lab Experment #8: The Integratng and Dfferentatng Op-Amp rcuts 1 Objectes The objectes of ths laboratory experment

More information

55:041 Electronic Circuits

55:041 Electronic Circuits 55:04 Electronc Crcuts Feedback & Stablty Sectons of Chapter 2. Kruger Feedback & Stablty Confguraton of Feedback mplfer Negate feedback β s the feedback transfer functon S o S S o o S S o f S S S S fb

More information

Lecture 5. Logical Effort Using LE on a Decoder

Lecture 5. Logical Effort Using LE on a Decoder Lecture 5 Logical Effort Using LE on a Decoder Mark Horowitz Computer Systems Laboratory Stanford University horowitz@stanford.edu Copyright 00 by Mark Horowitz Overview Reading Harris, Logical Effort

More information

A 2D Bounded Linear Program (H,c) 2D Linear Programming

A 2D Bounded Linear Program (H,c) 2D Linear Programming A 2D Bounded Lnear Program (H,c) h 3 v h 8 h 5 c h 4 h h 6 h 7 h 2 2D Lnear Programmng C s a polygonal regon, the ntersecton of n halfplanes. (H, c) s nfeasble, as C s empty. Feasble regon C s unbounded

More information

Dr. Shalabh Department of Mathematics and Statistics Indian Institute of Technology Kanpur

Dr. Shalabh Department of Mathematics and Statistics Indian Institute of Technology Kanpur Analyss of Varance and Desgn of Exerments-I MODULE III LECTURE - 2 EXPERIMENTAL DESIGN MODELS Dr. Shalabh Deartment of Mathematcs and Statstcs Indan Insttute of Technology Kanur 2 We consder the models

More information

THE ROYAL STATISTICAL SOCIETY 2006 EXAMINATIONS SOLUTIONS HIGHER CERTIFICATE

THE ROYAL STATISTICAL SOCIETY 2006 EXAMINATIONS SOLUTIONS HIGHER CERTIFICATE THE ROYAL STATISTICAL SOCIETY 6 EXAMINATIONS SOLUTIONS HIGHER CERTIFICATE PAPER I STATISTICAL THEORY The Socety provdes these solutons to assst canddates preparng for the eamnatons n future years and for

More information

Chapter 4. Digital Integrated Circuit Design I. ECE 425/525 Chapter 4. CMOS design can be realized meet requirements from

Chapter 4. Digital Integrated Circuit Design I. ECE 425/525 Chapter 4. CMOS design can be realized meet requirements from Digital Integrated Circuit Design I ECE 425/525 Professor R. Daasch Depar tment of Electrical and Computer Engineering Portland State University Portland, OR 97207-0751 (daasch@ece.pdx.edu) http://ece.pdx.edu/~ecex25

More information

Leakage and Dynamic Glitch Power Minimization Using Integer Linear Programming for V th Assignment and Path Balancing

Leakage and Dynamic Glitch Power Minimization Using Integer Linear Programming for V th Assignment and Path Balancing Leakage and Dynamc Gltch Power Mnmzaton Usng Integer Lnear Programmng for V th Assgnment and Path Balancng Yuanln Lu and Vshwan D. Agrawal Auburn Unversty, Department of ECE, Auburn, AL 36849, USA luyuanl@auburn.edu,

More information

Section 8.3 Polar Form of Complex Numbers

Section 8.3 Polar Form of Complex Numbers 80 Chapter 8 Secton 8 Polar Form of Complex Numbers From prevous classes, you may have encountered magnary numbers the square roots of negatve numbers and, more generally, complex numbers whch are the

More information

CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE

CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE Analytcal soluton s usually not possble when exctaton vares arbtrarly wth tme or f the system s nonlnear. Such problems can be solved by numercal tmesteppng

More information

3.6 Limiting and Clamping Circuits

3.6 Limiting and Clamping Circuits 3/10/2008 secton_3_6_lmtng_and_clampng_crcuts 1/1 3.6 Lmtng and Clampng Crcuts Readng Assgnment: pp. 184-187 (.e., neglect secton 3.6.2) Another applcaton of juncton dodes Q: What s a lmter? A: A 2-port

More information

Lecture 4: Universal Hash Functions/Streaming Cont d

Lecture 4: Universal Hash Functions/Streaming Cont d CSE 5: Desgn and Analyss of Algorthms I Sprng 06 Lecture 4: Unversal Hash Functons/Streamng Cont d Lecturer: Shayan Oves Gharan Aprl 6th Scrbe: Jacob Schreber Dsclamer: These notes have not been subjected

More information

A Novel Gate-Level NBTI Delay Degradation Model with Stacking Effect

A Novel Gate-Level NBTI Delay Degradation Model with Stacking Effect A Novel Gate-Level NBTI Delay Degradaton Model wth Stackng Effect Hong Luo 1,YuWang 1,KuHe 1, Rong Luo 1, Huazhong Yang 1,,andYuanXe 2, 1 Crcuts and Systems Dvson, Dept. of EE, Tsnghua Unv., Bejng, 100084,

More information

SIO 224. m(r) =(ρ(r),k s (r),µ(r))

SIO 224. m(r) =(ρ(r),k s (r),µ(r)) SIO 224 1. A bref look at resoluton analyss Here s some background for the Masters and Gubbns resoluton paper. Global Earth models are usually found teratvely by assumng a startng model and fndng small

More information

Second Order Analysis

Second Order Analysis Second Order Analyss In the prevous classes we looked at a method that determnes the load correspondng to a state of bfurcaton equlbrum of a perfect frame by egenvalye analyss The system was assumed to

More information

Digital Microelectronic Circuits ( ) Logical Effort. Lecture 7: Presented by: Adam Teman

Digital Microelectronic Circuits ( ) Logical Effort. Lecture 7: Presented by: Adam Teman Digital Microelectronic ircuits (361-1-3021 ) Presented by: Adam Teman Lecture 7: Logical Effort Digital Microelectronic ircuits The VLSI Systems enter - BGU Lecture 7: Logical Effort 1 Last Lectures The

More information

Please review the following statement: I certify that I have not given unauthorized aid nor have I received aid in the completion of this exam.

Please review the following statement: I certify that I have not given unauthorized aid nor have I received aid in the completion of this exam. Please revew the followng statement: I certfy that I have not gven unauthorzed ad nor have I receved ad n the completon of ths exam. Sgnature: Instructor s Name and Secton: (Crcle Your Secton) Sectons:

More information

Lecture (02) NAND and NOR Gates

Lecture (02) NAND and NOR Gates Lecture (02) NAND and NOR Gates By: Dr. Ahmed ElShafee ١ Dr. Ahmed ElShafee, ACU : Spring 2018, CSE303 Logic design II NAND gates and NOR gates In this section we will define NAND and NOR gates. Logic

More information

Lecture 21: Numerical methods for pricing American type derivatives

Lecture 21: Numerical methods for pricing American type derivatives Lecture 21: Numercal methods for prcng Amercan type dervatves Xaoguang Wang STAT 598W Aprl 10th, 2014 (STAT 598W) Lecture 21 1 / 26 Outlne 1 Fnte Dfference Method Explct Method Penalty Method (STAT 598W)

More information

Lecture 4 Hypothesis Testing

Lecture 4 Hypothesis Testing Lecture 4 Hypothess Testng We may wsh to test pror hypotheses about the coeffcents we estmate. We can use the estmates to test whether the data rejects our hypothess. An example mght be that we wsh to

More information

Kernel Methods and SVMs Extension

Kernel Methods and SVMs Extension Kernel Methods and SVMs Extenson The purpose of ths document s to revew materal covered n Machne Learnng 1 Supervsed Learnng regardng support vector machnes (SVMs). Ths document also provdes a general

More information

COMBINATIONAL CIRCUITS

COMBINATIONAL CIRCUITS OMINTIONL IRUIT pplcatons Half dder ssumpton : Two one-bt bnary varables and 1 1 1 1 1 1 1 The truth table of the Half dder Parallel dder for -bt varables H Implementaton of the Half dder Least gnfcant

More information

Lossy Compression. Compromise accuracy of reconstruction for increased compression.

Lossy Compression. Compromise accuracy of reconstruction for increased compression. Lossy Compresson Compromse accuracy of reconstructon for ncreased compresson. The reconstructon s usually vsbly ndstngushable from the orgnal mage. Typcally, one can get up to 0:1 compresson wth almost

More information

55:141 Advanced Circuit Techniques Two-Port Theory

55:141 Advanced Circuit Techniques Two-Port Theory 55:4 Adanced Crcut Technques Two-Port Theory Materal: Lecture Notes A. Kruger 55:4: Adanced Crcut Technques The Unersty of Iowa, 205 Two-Port Theory, Slde Two-Port Networks Note, the BJT s all are hghly

More information

The stream cipher MICKEY

The stream cipher MICKEY The stream cpher MICKEY-128 2.0 Steve Babbage Vodafone Group R&D, Newbury, UK steve.babbage@vodafone.com Matthew Dodd Independent consultant matthew@mdodd.net www.mdodd.net 30 th June 2006 Abstract: We

More information

PHYSICS - CLUTCH 1E CH 28: INDUCTION AND INDUCTANCE.

PHYSICS - CLUTCH 1E CH 28: INDUCTION AND INDUCTANCE. !! www.clutchprep.com CONCEPT: ELECTROMAGNETIC INDUCTION A col of wre wth a VOLTAGE across each end wll have a current n t - Wre doesn t HAVE to have voltage source, voltage can be INDUCED V Common ways

More information

Gated Clock Routing Minimizing the Switched Capacitance *

Gated Clock Routing Minimizing the Switched Capacitance * Gated Clock Routng Mnmzng the Swtched Capactance * Jaewon Oh and Massoud Pedram Dept. of Electrcal Engneerng Systems Unversty of Southern Calforna Los Angeles, CA 989 Tel: (3) 74-448 e-mal: [oh, massoud]@zugros.usc.edu

More information

Math1110 (Spring 2009) Prelim 3 - Solutions

Math1110 (Spring 2009) Prelim 3 - Solutions Math 1110 (Sprng 2009) Solutons to Prelm 3 (04/21/2009) 1 Queston 1. (16 ponts) Short answer. Math1110 (Sprng 2009) Prelm 3 - Solutons x a 1 (a) (4 ponts) Please evaluate lm, where a and b are postve numbers.

More information

The Concept of Beamforming

The Concept of Beamforming ELG513 Smart Antennas S.Loyka he Concept of Beamformng Generc representaton of the array output sgnal, 1 where w y N 1 * = 1 = w x = w x (4.1) complex weghts, control the array pattern; y and x - narrowband

More information

Lecture 12: Classification

Lecture 12: Classification Lecture : Classfcaton g Dscrmnant functons g The optmal Bayes classfer g Quadratc classfers g Eucldean and Mahalanobs metrcs g K Nearest Neghbor Classfers Intellgent Sensor Systems Rcardo Guterrez-Osuna

More information

Module 14: THE INTEGRAL Exploring Calculus

Module 14: THE INTEGRAL Exploring Calculus Module 14: THE INTEGRAL Explorng Calculus Part I Approxmatons and the Defnte Integral It was known n the 1600s before the calculus was developed that the area of an rregularly shaped regon could be approxmated

More information

Chapter 3 Describing Data Using Numerical Measures

Chapter 3 Describing Data Using Numerical Measures Chapter 3 Student Lecture Notes 3-1 Chapter 3 Descrbng Data Usng Numercal Measures Fall 2006 Fundamentals of Busness Statstcs 1 Chapter Goals To establsh the usefulness of summary measures of data. The

More information

Week 11: Differential Amplifiers

Week 11: Differential Amplifiers ELE 0A Electronc rcuts Week : Dfferental Amplfers Lecture - Large sgnal analyss Topcs to coer A analyss Half-crcut analyss eadng Assgnment: hap 5.-5.8 of Jaeger and Blalock or hap 7. - 7.3, of Sedra and

More information

Annexes. EC.1. Cycle-base move illustration. EC.2. Problem Instances

Annexes. EC.1. Cycle-base move illustration. EC.2. Problem Instances ec Annexes Ths Annex frst llustrates a cycle-based move n the dynamc-block generaton tabu search. It then dsplays the characterstcs of the nstance sets, followed by detaled results of the parametercalbraton

More information

CHAPTER 13. Exercises. E13.1 The emitter current is given by the Shockley equation:

CHAPTER 13. Exercises. E13.1 The emitter current is given by the Shockley equation: HPT 3 xercses 3. The emtter current s gen by the Shockley equaton: S exp VT For operaton wth, we hae exp >> S >>, and we can wrte VT S exp VT Solng for, we hae 3. 0 6ln 78.4 mv 0 0.784 5 4.86 V VT ln 4

More information

U.C. Berkeley CS294: Beyond Worst-Case Analysis Luca Trevisan September 5, 2017

U.C. Berkeley CS294: Beyond Worst-Case Analysis Luca Trevisan September 5, 2017 U.C. Berkeley CS94: Beyond Worst-Case Analyss Handout 4s Luca Trevsan September 5, 07 Summary of Lecture 4 In whch we ntroduce semdefnte programmng and apply t to Max Cut. Semdefnte Programmng Recall that

More information