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UCLA - ELEC ENGR - 101
EE 101 Homework 4:DUE NOVEMBER 14TH Monday noon (12pm);(THERE IS A COLLECTION HW CABINET MARKED EE101 IN ROOM 67-112 ON THE 6TH FLOOR OF ENGR IV.)1. A long wire carrying a current I folds back with a semicircular bend of radius b as in figurebelow. De
UCLA - ELEC ENGR - 101
EE 101 Homework 5: DUE NOVEMBER 23TH Wednesday (5pm);(THERE IS A COLLECTION HW CABINET MARKED EE101 IN ROOM 67-112 ON THE 6TH FLOOR OF ENGR IV.)
UCLA - ELEC ENGR - 101
EE 101 Homework 6: DUE NOVEMBER 30TH Wednesday (5pm);(THERE IS A COLLECTION HW CABINET MARKED EE101 IN ROOM 67-112 ON THE 6TH FLOOR OF ENGR IV.)1. A lossy transmission line with characteristic impedance Z0 is terminated in an arbitrary loadimpedance ZL
UCLA - ELEC ENGR - 101
EE 101 Homework 2:DUE OCTOBER 19TH Wednesday 2PM;(THERE WILL BE A COLLECTION CABINET MARK EE101 IN ROOM 67-112 ON THE 6TH FLOOR OF ENGR IV.)1. Three point charges, each with q=3 nC, are located at the corners of a triangle in the x-y plane, with oneco
UCLA - ELEC ENGR - 101
EE101 HW# 7 Solutions1) (30 points)2) (30 points)3) (40 Points)
UCLA - ELEC ENGR - 102
UCLAFall 2011Systems and SignalsLecture 4: Systems CharacteristicsOctober 5, 2011EE102: Systems and Signals; Fall 2011, Jin Hyung Lee1Agenda My oce hours is now T 2-4pm. Zhongnans oce hour is now T 11-12pm. Discussion C (T 2-3pm) and D (T 3-4pm)
UCLA - ELEC ENGR - 102
UCLAFall 2011Systems and SignalsLecture 7: Continuous-Time Fourier Series IOctober 17, 2011EE102: Systems and Signals; Fall 2011, Jin Hyung Lee1MidtermOct. 26 2011 In class, 2 hours. 4 problems. Closed book, closed notes. You can bring 1 hand-
UCLA - ELEC ENGR - 102
UCLAFall 2011Systems and SignalsLecture 8: Continuous Time Fourier Series IIOctober 19, 2011EE102: Systems and Signals; Fall 2011, Jin Hyung Lee1IntroductionTodays topics: Review: Fourier series Properties of continuous time Fourier series Intr
UCLA - ELEC ENGR - 102
UCLAFall 2011Systems and SignalsLecture 10: The Continuous Time Fourier TransformOctober 31, 2011EE102: Systems and Signals; Fall 2011, Jin Hyung Lee1Introduction to Fourier Transforms Fourier transform as a limit of Fourier series Inverse Fourie
UCLA - ELEC ENGR - 102
UCLAFall 2011Systems and SignalsLecture 11: Fourier Transform TheoremsNovember 2, 2011EE102: Systems and Signals; Fall 2011, Jin Hyung Lee1Administration MATLAB Project Opportunity to do hands-on signal processing Will be handed out on Monday (N
UCLA - ELEC ENGR - 102
UCLAFall 2011Systems and SignalsLecture 12: Fourier Transform and Frequency Response of SystemsNovember 7, 2011EE102: Systems and Signals; Fall 2011, Jin Hyung Lee1Todays topics: Review Fourier Transforms of periodic signals Limiting transforms
UCLA - ELEC ENGR - 102
UCLAFall 2011Systems and SignalsLecture 13: Introduction to Laplace TransformNovember 09, 2011EE102: Systems and Signals; Fall 2011, Jin Hyung Lee1Administration Review Session: Monday, Nov. 14. Second Midterm: Wednesday, Nov. 16, 10:00am-12:00pm
UCLA - ELEC ENGR - 102
UCLAFall 2011Systems and SignalsLecture 15: Inversion of Laplace TransformNovember 21, 2011EE102: Systems and Signals; Fall 2011, Jin Hyung Lee1ReviewLast class we introduced Laplace transform: Generalizes Fourier transform Allows handling of gr
UCLA - ELEC ENGR - 102
UCLAFall 2011Systems and SignalsLecture 16: Time and Frequency Characterization of Systems and SignalsNovember 23, 2011EE102: Systems and Signals; Fall 2011, Jin Hyung Lee1Time & Frequency Characterization of SystemsWhy use frequency domain? Alte
UCLA - ELEC ENGR - 102
UCLAFall 2011Systems and SignalsLecture 17: Sampling Theorem INovember 28, 2011EE102: Systems and Signals; Fall 2011, Jin Hyung Lee1AgendaTodays topics Sampling of continuous-time signals Interpolation of band-limited signals (Sampling theorem)
UCLA - ELEC ENGR - 102
UCLAFall 2011Systems and SignalsLecture 18: Sampling Theorem IINovember 30, 2011EE102: Systems and Signals; Fall 2011, Jin Hyung Lee1Administration Project due Wednesday Nov. 30 2011 at 10 am (grace period till 5 pm).Submission Guidelines: A sho
UCLA - ELEC ENGR - 102
1EE102Fall Quarter 2011Systems and SignalsJin Hyung LeeHomework #1Due: Wednesday October 05, 2011 at 5 PM.1. Find the even and odd decomposition of this signal:21-2-1x(t)012t2. Given the signal x(t) shown belowx(t )1-2-10-112tdr
UCLA - ELEC ENGR - 102
1EE102Fall Quarter 2011Systems and SignalsJin Hyung LeeHomework #2Due: Wednesday, Oct 12, 2011 at 5 PM.1. State whether the following systems are linear or nonlinear; time invariant or time variant;and why.(a) y (t) = x(t) sin(t + )(b) y (t) = x
UCLA - ELEC ENGR - 102
1EE102Fall Quarter 2011Systems and SignalsJin Hyung LeeMatlab Assignment 1Getting Started MatlabFor this lab we only need the basic abilities of matlab to create and manipulate vectors, andplot the results. The documentation for matlab exists in m
UCLA - ELEC ENGR - 102
1EE102Fall Quarter 2011Systems and SignalsJin Hyung LeeMatlab Assignment #1 SolutionGetting Started MatlabFor this lab we only need the basic abilities of matlab to create and manipulate vectors, andplot the results. The documentation for matlab e
UCLA - ELEC ENGR - 102
1EE102Fall Quarter 2011Systems and SignalsJin Hyung LeeHomework #3Due: Wednesday, October 19, 2011 at 5 PM.1. Analytically compute the convolution (f g )(t), where f (t) and g (t) aref (t) = u(t)etg (t) = rect(t)and sketch a plot of the result.
UCLA - ELEC ENGR - 102
1EE102Fall Quarter 2011Systems and SignalsJin Hyung LeeMatlab Assignment 2Due: Friday, October 21, 2011 at 5 PM.This laboratory will be concerned with numerically evaluating continuous time convolutionintegrals. Matlab provides a function conv() t
UCLA - ELEC ENGR - 102
1EE102Fall Quarter 2011Systems and SignalsJin Hyung LeeMatlab Assignment #2 SolutionThis laboratory will be concerned with numerically evaluating continuous time convolutionintegrals. Matlab provides a function conv() that performs a discrete-time
UCLA - ELEC ENGR - 102
1EE102Fall Quarter 2011Systems and SignalsJin Hyung LeeHomework #4Due: Wednesday, November 2, 2011 at 5 PM.1. Suppose that f (t) is a periodic signal with period T0 , and that f (t) has a Fourier series. If is a real number, show that f (t ) can b
UCLA - ELEC ENGR - 102
1EE102Fall Quarter 2011Systems and SignalsJin Hyung LeeMatlab Assignment 3 SolutionIn this lab we will use matlab to compute the Fourier series for several signals, and comparethe errors that results from the approximation of the signals by truncat
UCLA - ELEC ENGR - 102
1EE102Fall Quarter 2011Systems and SignalsJin Hyung LeeHomework #5Due: Wednesday, November 9, 2011 at 5 PM.1. Each of these signals can be written as a sum of scaled and shifted unit rectangles andtriangles,a)2x(t)b)210-201-1x(t)12-
UCLA - ELEC ENGR - 102
1EE102Fall Quarter 2011Systems and SignalsJin Hyung LeeHomework #5 Solution1. Each of these signals can be written as a sum of scaled and shifted unit rectangles andtriangles,a)2x(t)b)210-21-1x(t)102-21-1-1-22-1-2Find a simpl
UCLA - ELEC ENGR - 102
1EE102Fall Quarter 2011Systems and SignalsJin Hyung LeeCourse ProjectAmplitude Modulation (AM) is a technique widely used in communication area. One example you can see in your everyday life is the AM radio. The basic principle of the AM techniquei
UCLA - ELEC ENGR - 102
Astha Kalia80379143411/30/2011EE 102 Course ProjectTask 1> ds = d(16000+1:16000+2560);> Ds=fft(ds);> f= [0:0.1:256-0.1];> plot(f, abs(Ds);> xlabel('Frequency');> ylabel('Amplitude');Task 2> t= [1:length(d)]/256000;> demod= d.*exp(-1*j*47000*2
UCLA - ELEC ENGR - 102
Astha Kalia803791434EE 102 MatlabLeeHomework #3-Matlab1.) Task 1:Nconv scriptfunction [ y, ty ] = nconv( x, tx, h, th)% nconv performs a numerical approximation to the% continuous time convolution using matlabs conv()% function%% [y, ty]= ncon
UCLA - ELEC ENGR - 102
Astha KaliaUID: 80379143410/14/2011MatLab Assignment #11.) >t=0:.1:10> w=exp(-t);> x=t.*exp(-t);> y=exp(-t)+ t.*exp(-t);> plot(t,w);> grid on;> xlabel('t(sec)');> ylabel('w(volts)');> title('sample waveform w vs. time');2.)> plot(t,w,t,x,t,y
Indian Institute of Technology, Madras - CSE,IT - 101
Boyce-Codd Normal FormBy:P.MirunaliniAsst. Prof, CSESSN College of EngineeringOverview Dependency preservation Boyce/Codd Normal FormDependency Preservation Relvar SECOND could be decomposed into:A: SC cfw_ SUPPLIER_NUMBER, CITY CS cfw_ CITY, S
Indian Institute of Technology, Madras - CSE,IT - 101
Closure of Attribute SetsGiven a set of attributes of R and a set of functional dependencies F, we need a way tofind all of the attributes of R that are functionally determined by . This set of attributesis called the closure of under F and is denoted
Indian Institute of Technology, Madras - CSE,IT - 101
Database Base ArchitectureDatabaseClick to edit Master subtitle style12/16/11overviewDatabase UsersDatabase AdministratorDatabase System ArchitectureStorage ManagerThe Query ProcessorApplication Architecture12/16/11DATABASE USERSUsers are dif
Indian Institute of Technology, Madras - CSE,IT - 101
DATABASE MANGEMENT SYSTEMSB.E V SEM A SECP.MirunaliniAP ,CSESSNCEB.E. IV Sem Database ManagementSystemsOverviewAn IntroductionWhat is DBMS?Purpose of Database SystemView of DataData ModelsDatabase LanguagesB.E. IV Sem Database ManagementSys
Indian Institute of Technology, Madras - CSE,IT - 101
Domain Relational CalculusOverviewAn IntroductionDomain calculus SyntaxSuppliers-parts databaseExamplesLanguages Based on Relational CalculusSQLQUELQBEAn introductionAnother variation of relational calculus called the domainrelational calculus
Indian Institute of Technology, Madras - CSE,IT - 101
Enhanced Entity Relation ModelEER stands for Enhanced ER or Extended EREER Model ConceptsIncludes all modeling concepts of basic ERAdditional concepts:subclasses/superclassesspecialization/generalizationattribute and relationship inheritanceThese
Indian Institute of Technology, Madras - CSE,IT - 101
EMBEDDED SQLP.MirunaliniA.P,CSESSNCESQL in Application CodeSQL commands can be called from within a host language(e.g., C+ or Java) program.SQL statements can refer to host variables (includingspecial variables used to return status).Must include
Indian Institute of Technology, Madras - CSE,IT - 101
Entity-Relationship Model[ER Model]OUTLINEER Model ConceptsEntities and AttributesEntity Types, Value Sets, and Key AttributesRelationships and Relationship TypesWeak Entity TypesRoles and Attributes in Relationship TypesER Diagrams - NotationER
Indian Institute of Technology, Madras - CSE,IT - 101
Entity-Relationship Model[ER Model]OUTLINEOverview of Database modelsER Diagram for COMPANY SchemaConstraintsStructural ConstraintsOverview of Database DesignProcessTwo main activities:Database designApplications designFocus in this session on
Indian Institute of Technology, Madras - CSE,IT - 101
Functional DependenciesOverviewBasic DefinitionsTrivial and nontrivial dependenciesClosure of a set of dependenciesClosure of a set of attributesIrreducible sets of dependenciesFunctional DependenciesA functional dependency is basically a many-to-
Indian Institute of Technology, Madras - CSE,IT - 101
For Evaluation Only.Copyright (c) by VeryPDF.com IncEdited by VeryPDF PDF Editor Version 2.6L OG ON o r m a l i z a ti o n - R e l a ti o n a lD a ta b a s e sENTOverviewNormalization An introductionDefinition of Keys RecapFirst Normal Form (1NF
Indian Institute of Technology, Madras - CSE,IT - 101
NormalizationOverviewAn introductionNonloss decompositionFunctional dependenciesNormal Forms [NF]First Normal Form 1NFSecond Normal Form 2NFThird Normal Form 3NFNormalizationNormalization first proposed by Codd (1972)Normalization: The process
Indian Institute of Technology, Madras - CSE,IT - 101
Introduction to Relational DatabasesInformal look to Relational DatabasesThe relational model is having the three aspects:Structural aspect:The data in the database is perceived by the user astablesIntegrity aspect:Those tables satisfy certain inte
Indian Institute of Technology, Madras - CSE,IT - 101
Introduction to RelationalAlgebraOverviewIntroductionUnary Relational OperationsSELECT, PROJECT, RenameRelational Algebra Operations from Set TheoryBinary Relational OperationsAdditional Relational OperationsExamples of Queries in Relational Alge
Indian Institute of Technology, Madras - CSE,IT - 101
DATABASE MANGEMENT SYSTEMSB.E IV SEM A SECP.MirunaliniAP ,CSESSNCEoverviewWhat are Triggers?Procedures Vs TriggersTrigger IssuesWhen to use Triggers?ECA ModelSyntaxRow vs Statement TriggersBefore Vs After TriggersWhat are Triggers?Triggers
Indian Institute of Technology, Madras - CSE,IT - 101
JOINSCARTESIAN PRODUCTA Cartesian product is formed when:A join condition is omittedA join condition is invalidAll rows in the first table are joined to all rows in the secondtableTo avoid a Cartesian product, include a valid join condition in aWH
Indian Institute of Technology, Madras - CSE,IT - 101
Nested Query (Sub Query)Nested QueryConsider the relations:Employees (ssn, last_name, first_name, salary, d_id)Department (dept_id, d_name)Nested QueryWhich employees have salaries greater than 'john' salary?1. find what john earns, and then2. fin
Indian Institute of Technology, Madras - CSE,IT - 101
SQLSQL refers to query language and defines the structure of thedata, modify the db and specify security constraints.SQL has serval language parts:DDL: Provides commands for defining,deleting,modifyingrelation schemas.DML:Includes commands for inser
Indian Institute of Technology, Madras - CSE,IT - 101
Security ViewsBy:B.Senthil KumarAsst. Prof, CSEDatabase Management Systems IV SemTable of ContentsAn IntroductionWhat is a View?Why use Views?Creating a ViewGuidelines Creating a ViewCreating a View using column aliasQuerying a ViewUpdates on
Indian Institute of Technology, Madras - CSE,IT - 101
Higher NormalizationPresentation by:P.MirunaliniAsst. ProfessorSSNCEB.E. IV Sem Database Management SystemsOverview Multi-valued Dependencies Fourth Normal Form 4NFFirst Normal Form 1NFNormalizng nested relations into PROJS is a nested relation
Indian Institute of Technology, Madras - CSE,IT - 101
Higher NormalizationHigherOverviewOverviewJoin Dependencies [JD]JoinFifth Normal Form 5NFJoin DependencyJoinThere exists relvars that cannot be nonloss-decomposed into tworelvars thatnonloss decomposedprojections but can be nonloss-decomposed
Indian Institute of Technology, Madras - CSE,IT - 101
Concurrency ControlOverviewThree concurrency problemsLockingThree concurrency problems RevisitedDeadlockConcurrencyConcurrency DBMS allow many transactions to access the samedatabase at the same time.A kind of control is needed to ensure that con
Indian Institute of Technology, Madras - CSE,IT - 101
Distributed SystemsP.MirunaliniA.P,CSESSNCEOVERVIEWDistributed SystemsHomogeneous / HeterogeneousDistributed Data StorageData ReplicationData FragmentationHorizontal FragmentationVertical FragmentationTransparencyCentralized DatabaseIn a cen
Indian Institute of Technology, Madras - CSE,IT - 101
Concurrency(Intent Locking)P.Mirunalini,A.P,CSESSNCEIsolation LevelsSerializability guarantees isolation for ACID properties.Protocols used to guarantee serializability reduce the degree ofconcurrency or overall system throughput.System supports
Indian Institute of Technology, Madras - CSE,IT - 101
RecoveryP.MIRUNALINIAP,CSESSNCEOverviewTransactionsTransaction RecoveryWrite Ahead Log [WAL] RuleACID PropertiesSystem RecoveryCheckpointTwo Phase Commit [2PC]Database RecoveryPurpose of Database RecoveryTo bring the database into the last c
Indian Institute of Technology, Madras - CSE,IT - 101
Database RecoveryTechniquesPresentation by:P.MirunaliniA.P/ CSESSNCEB.E. IV Semester BDatabase RecoveryPurpose of Database RecoveryTo bring the database into the last consistent state, which existed prior tothe failure.To preserve transaction p