Vector Spaces. 1 Theory. 2 Matlab. Rules and Operations
|
|
- Collin Peters
- 5 years ago
- Views:
Transcription
1 Vector Spaces Rules and Operations 1 Theory Recall that we can specify a point in the plane by an ordered pair of numbers or coordinates (x, y) and a point in space with an order triple of numbers (x, y, z). This also defines a vector with base at the origin and terminal point at the specified point in the plane or in space. In general, an n-dimensional real vector is an ordered n-tuple of numbers (x 1, x 2..., x n ) and is a point in R n. If u and v are two vectors positioned so that the initial point of v is at the terminal point of u, then the vector that is the sum u + v, is the vector from the initial point of u to the terminal point of v. If v is a vectors and c is a scalar, then the scalar multiple cv is a vector whose magnitude is c times the magnitude of v pointing in the same direction as v if c > 0 and in the opposite direction of v if c < 0. If c = 0 or v = (0, 0,..., 0) then cv = (0, 0,..., 0). The difference v u is v+ 1u and is a vector pointing from the terminal point of u to the terminal point of v The centroid of a collection of points in R n can be thought of as the collection s center of mass. It is the point whose ith component is the average value of the ith components of all the points in the collection. 2 Matlab Useful Matlab Functions/Concepts: Manipulating Vectors A k-dimensional real vector is stored in Matlab as an ordered list of real numbers. Vectors can be written as row vectors or column vectors. When defining vectors the coordinates in a row vector are separated by commas and coordinates in a column vector are separated by semicolons. We have to be careful when trying to add vectors: row(column) vectors can only be added to row(column) vectors and they must be the same dimension. 1
2 >> rowvector1 = [1, 2, 3]; >> rowvector2 = [4, 2, -1]; >> columnvector1 = [1 ; 2 ; 3]; >> columnvector2 = [1 ; 2 ; 3 ; 4]; >> rowvector1+rowvector2 >> rowvector1+columnvector1 >> columnvector1+columnvector2 (Hint: The last two commands should give you errors.) Scalar multiplication is achieved using the * symbol with a scalar and a vector. >> vector = [1, 2, 3]; >> scaledvector = 5*rowvector1 The dot product of two vectors is also achieved with the * symbol but you must be careful that the first term is a row vector and the second term is a column vector. >> rowvector1 = [1, 2, 3]; >> columnvector1 = [1 ; 2 ; 3]; >> rowvector1*columnvector1 Note that >> rowvector1*rowvector1 will produce an error and the operation >> columnvector1*rowvector1 is beyond the scope of this course. Structures Matlab can store many different types of data. Integers, real numbers, and strings are among the most commonly used. However, a table in Matlab can only contain data of one type. Often we may wish to group data of different types. For example, if our data is patient medical information we may want to record the patients name (a string), their age (an integer), and their weight and height (positive real numbers). One way to do this in Matlab is with a data type called a 2
3 structure. A structure is like a database of patient information where each patient gets an entry in the database and each entry can contain fields with data of different types. If the variable patients is a structure in Matlab, the syntax for accessing the value in the ith entry of a structure is patients(i). This will return all of the fields in that entry. If one of those fields is given the variable name age, the syntax for accessing that particular field for the ith entry is patients(i).age. >> patients = struct( name,[], age,[],); >> patients(1).name = John Smith ; >> patients(1).age = 47; >> patients(1).weight = 198.1; >> patients(1).height = 6.1; >> patients(2).name = Jane Doe ; >> patients(2).age = 26; >> patients(2).weight = 109.6; >> patients(2).height = 5.5; rand(rows,columns) There are many reasons one might want to generate random numbers. Matlab can produce a table with r rows and c columns with real numbers entries randomly chosen between 0 and 1 using the command >> rand(r,c). So rand(1,3) can be used to generate a random RGB color. This can also be used to generate a random number between a and b by >> a+(b-a)*rand(r,c). >> minvalue = -3; >> maxvalue = 17.2; >> rows = 5; >> cols = 8; >> randoms = minvalue + (maxvalue-minvalue)*rand(rows,cols); scatter(x,y,size,color) scatter(x,y,size,color) performs the same same function as scatter3(x,y,size,color) but it takes two dimensions of data instead of three. 3
4 hold You may have reason to plot several plots on the same figure. To do so you must toggle on the command hold after the first figure is plotted, otherwise Matlab will overwrite the existing plot. Alternatively you can open a blank figure window with the command figure and toggle on the command hold after that blank figure is made. All subsequent plots will be put into the same figure window until hold is toggled off. >> points1 = rand(50,2); >> points2 = rand(50,2)-1; >> figure >> hold >> scatter(points1(:,1),points1(:,2),10,[1,0,0]) >> scatter(points2(:,1),points2(:,2),5,rand(1,3)) 3 Experimentation A program called dotproduct.m can be found on the course website. Download it and place it in your Matlab working directory. This function takes in two real (equal length) vectors in R 2 or R 3 and plots the vectors in the plane or in space. This program also outputs the computation of the dot product of these two vectors to the command window. >> v = [1,0,-1]; >> w = [sqrt(3),sqrt(3),sqrt(3)]; >> d = dotproduct(v,w); After running the above example, try a few other input vectors in both two and three dimensions to familiarize yourself with the program, then proceed with the investigations below. 4
5 3.1 Investigation 1 Step 1: Define the parameter c = 1; and vectors v = c*[1,2,3]; and w = [2,0,0];. Notice that the vector v depends on what you chose for the parameter c. Step 2: Run dotproduct(v,w) for several choices of c. What do you observe about the relationship between c and the dot product? Does the dot product appear to depend on the magnitude of the vectors? Step 3: Run dotproduct(v,w) for several choices of unit vectors. Does the dot product appear to depend on the angle between the vectors? 3.2 Investigation 2: Step 1: Define the parameter theta = 0; and vectors v = [cos(theta),sin(theta)]; and w = [1,0];. Notice that the vector v depends on what you chose for the parameter theta. Step 2: Run dotproduct(v,w) for several choices of theta. What do you observe about the relationship between theta and v? What do you observe about the relationship between theta and the dot product? Can the dot product be made positive? Negative? Zero? If so, what can you say about the relationship between the vectors v and w in each case? 3.3 Bonus: Step 1: Fix w = [1 ; 0] and define v = [cos(theta),sin(theta)]. Step 2: Using a for loop, compute the dot product of w with v for many choices of theta in the range 0 to π and store these in a list. 5
6 Step 3: Plot the list of dot product values against the list of different theta values. Do you recognize the function which you plotted? Conjecture an answer to the following question: How does the dot product between two unit vectors depend on the angle between them? 4 Application The antigenic binding data for 79 different antisera was collected for 273 influenza viruses between 1968 and Building on the ideas in the previous lab, we think of this data as 273 points in 79-dimensional antigenic space. Since we cannot visualize such a high dimensional space, a complicated projection onto a plane was carried out. The resulting data can be thought of as a collection of 273 points in R 2 and can be used to visualize the antigenic evolution of influenza between 1968 and This data has been provided for you in a file on the course website called antigenicdata.mat. Download the data file antigenicdata.mat from the course website and load it into Matlab. This will load a structure, antigenicdata, which contains 273 entries, each of which contains the fields id (a unique string identifying the virus), coords (a 2-dimensional row vector), and strain (an integer between 1 and 11 identifying a strain). Note: Strains are listed in chronological order over the time period 1968 to Create a new Matlab script called lastname operations.m which performs the following steps and use it to answer the questions in this lab. It may be useful to use the following command throughout your code: >> strain = [antigenicdata([antigenicdata.strain]==i).coords]; This is an example of a powerful technique called logical indexing. This stores a list of the xy-coordinates of only those entries in the structure whose strain value is equal to i. In this way you can easily access only the strain you are interested in. 4.1 Coding: Step 1: Scatter plot the planar antigenic data and color code the viruses according to strain. 6
7 Step 2: Create a variable named straincentroids which contains the centroids of the 11 different strains. Step 3: Add the 11 centroids of the different strains to the plot. Make them large black dots. Step 4: Create a variable named strainchangemagnitudes which contains the magnitude of vector which points from the centroid of strain i to the centroid of strain i + 1. These indicate how much antigenic change occured between strains. 4.2 Questions: Question 1: Between which two strains did the largest antigenic change occur? Question 2: What was the total antigenic change between 1968 and 2003 (i.e. between strains 1 and 11)? Question 3: Compute and record the vector which points from the centroid of strain 3 to strain 4 and the vector which points from strain 4 to strain 5 to at least 6 demical places. Compute the sum of these two vectors and explain this sum of vectors in terms of the antigenic change between the centroids of strains. Question 3: Print the scatter plot antigenic data and strain centroids and draw and label (by hand) the vectors described in question 3. Bonus: The triangle inequality for vectors states that a + b a + b. Verify this claim by computing a+b and a + b if a is the difference between the centroid of strain 11 and the centroid of strain 10 and if b is the difference between the centroid of strain 10 and the centroid of strain 9. Explain what the triangle inequality means in terms of antigenic change. 7
Lab 2 Worksheet. Problems. Problem 1: Geometry and Linear Equations
Lab 2 Worksheet Problems Problem : Geometry and Linear Equations Linear algebra is, first and foremost, the study of systems of linear equations. You are going to encounter linear systems frequently in
More informationProblem 1: (3 points) Recall that the dot product of two vectors in R 3 is
Linear Algebra, Spring 206 Homework 3 Name: Problem : (3 points) Recall that the dot product of two vectors in R 3 is a x b y = ax + by + cz, c z and this is essentially the same as the matrix multiplication
More informationLinear Algebra Using MATLAB
Linear Algebra Using MATLAB MATH 5331 1 May 12, 2010 1 Selected material from the text Linear Algebra and Differential Equations Using MATLAB by Martin Golubitsky and Michael Dellnitz Contents 1 Preliminaries
More informationOctave. Tutorial. Daniel Lamprecht. March 26, Graz University of Technology. Slides based on previous work by Ingo Holzmann
Tutorial Graz University of Technology March 26, 2012 Slides based on previous work by Ingo Holzmann Introduction What is? GNU is a high-level interactive language for numerical computations mostly compatible
More informationMatrix-Vector Operations
Week3 Matrix-Vector Operations 31 Opening Remarks 311 Timmy Two Space View at edx Homework 3111 Click on the below link to open a browser window with the Timmy Two Space exercise This exercise was suggested
More informationTOPIC 2 Computer application for manipulating matrix using MATLAB
YOGYAKARTA STATE UNIVERSITY MATHEMATICS AND NATURAL SCIENCES FACULTY MATHEMATICS EDUCATION STUDY PROGRAM TOPIC 2 Computer application for manipulating matrix using MATLAB Definition of Matrices in MATLAB
More informationMatrix-Vector Operations
Week3 Matrix-Vector Operations 31 Opening Remarks 311 Timmy Two Space View at edx Homework 3111 Click on the below link to open a browser window with the Timmy Two Space exercise This exercise was suggested
More informationBCMB/CHEM 8190 Lab Exercise Using Maple for NMR Data Processing and Pulse Sequence Design March 2012
BCMB/CHEM 8190 Lab Exercise Using Maple for NMR Data Processing and Pulse Sequence Design March 2012 Introduction Maple is a powerful collection of routines to aid in the solution of mathematical problems
More informationIntroduction to SVD and Applications
Introduction to SVD and Applications Eric Kostelich and Dave Kuhl MSRI Climate Change Summer School July 18, 2008 Introduction The goal of this exercise is to familiarize you with the basics of the singular
More informationLab 2: Static Response, Cantilevered Beam
Contents 1 Lab 2: Static Response, Cantilevered Beam 3 1.1 Objectives.......................................... 3 1.2 Scalars, Vectors and Matrices (Allen Downey)...................... 3 1.2.1 Attribution.....................................
More informationMAT 343 Laboratory 6 The SVD decomposition and Image Compression
MA 4 Laboratory 6 he SVD decomposition and Image Compression In this laboratory session we will learn how to Find the SVD decomposition of a matrix using MALAB Use the SVD to perform Image Compression
More informationLinear Algebra: A Constructive Approach
Chapter 2 Linear Algebra: A Constructive Approach In Section 14 we sketched a geometric interpretation of the simplex method In this chapter, we describe the basis of an algebraic interpretation that allows
More information1. Vectors.
1. Vectors 1.1 Vectors and Matrices Linear algebra is concerned with two basic kinds of quantities: vectors and matrices. 1.1 Vectors and Matrices Scalars and Vectors - Scalar: a numerical value denoted
More informationJanuary 18, 2008 Steve Gu. Reference: Eta Kappa Nu, UCLA Iota Gamma Chapter, Introduction to MATLAB,
Introduction to MATLAB January 18, 2008 Steve Gu Reference: Eta Kappa Nu, UCLA Iota Gamma Chapter, Introduction to MATLAB, Part I: Basics MATLAB Environment Getting Help Variables Vectors, Matrices, and
More informationVECTORS AND MATRICES
VECTORS AND MATRICES COMPUTER SESSION C1 BACKGROUND PREPARATIONS The session is divided into two parts. The first part involves experimenting in the Mathematics Laboratory and the second part involves
More informationMath Assignment 3 - Linear Algebra
Math 216 - Assignment 3 - Linear Algebra Due: Tuesday, March 27. Nothing accepted after Thursday, March 29. This is worth 15 points. 10% points off for being late. You may work by yourself or in pairs.
More information(Linear equations) Applied Linear Algebra in Geoscience Using MATLAB
Applied Linear Algebra in Geoscience Using MATLAB (Linear equations) Contents Getting Started Creating Arrays Mathematical Operations with Arrays Using Script Files and Managing Data Two-Dimensional Plots
More informationLab 6: Linear Algebra
6.1 Introduction Lab 6: Linear Algebra This lab is aimed at demonstrating Python s ability to solve linear algebra problems. At the end of the assignment, you should be able to write code that sets up
More informationThree-Dimensional Coordinate Systems. Three-Dimensional Coordinate Systems. Three-Dimensional Coordinate Systems. Three-Dimensional Coordinate Systems
To locate a point in a plane, two numbers are necessary. We know that any point in the plane can be represented as an ordered pair (a, b) of real numbers, where a is the x-coordinate and b is the y-coordinate.
More informationJane and Joe are measuring the circumference of a dime with a string. Jane' s result is: 55 mm Joe's result is: 58 mm
A LESSON ON ABSOLUTE VALUE Jane and Joe are measuring the circumference of a dime with a string. Jane' s result is: 55 mm Joe's result is: 58 mm Tom knows the true length of the circumference: 56 mm. He
More informationCompleting this project will help you learn about two-dimensional arrays, structures, and structure arrays. More on Matlab graphics and GUI design.
CS1115 Fall 2013 Project 4 Due Tuesday October 29 at 11pm You must work either on your own or with one partner. You may discuss background issues and general solution strategies with others, but the project
More informationThink about systems of linear equations, their solutions, and how they might be represented with matrices.
Think About This Situation Unit 4 Lesson 3 Investigation 1 Name: Think about systems of linear equations, their solutions, and how they might be represented with matrices. a Consider a system of two linear
More informationAnnouncements August 31
Announcements August 31 Homeworks 1.1 and 1.2 are due Friday. The first quiz is on Friday, during recitation. Quizzes mostly test your understanding of the homework. There will generally be a quiz every
More informationCSCE 155N Fall Homework Assignment 2: Stress-Strain Curve. Assigned: September 11, 2012 Due: October 02, 2012
CSCE 155N Fall 2012 Homework Assignment 2: Stress-Strain Curve Assigned: September 11, 2012 Due: October 02, 2012 Note: This assignment is to be completed individually - collaboration is strictly prohibited.
More information3 The language of proof
3 The language of proof After working through this section, you should be able to: (a) understand what is asserted by various types of mathematical statements, in particular implications and equivalences;
More informationLINEAR ALGEBRA - CHAPTER 1: VECTORS
LINEAR ALGEBRA - CHAPTER 1: VECTORS A game to introduce Linear Algebra In measurement, there are many quantities whose description entirely rely on magnitude, i.e., length, area, volume, mass and temperature.
More informationMATH 22A: LINEAR ALGEBRA Chapter 1
MATH 22A: LINEAR ALGEBRA Chapter 1 Steffen Borgwardt, UC Davis original version of these slides: Jesús De Loera, UC Davis January 10, 2015 Vectors and Matrices (1.1-1.3). CHAPTER 1 Vectors and Linear Combinations
More informationAlgebra I Calculator Activities
First Nine Weeks SOL Objectives Calculating Measures of Central Tendency SOL A.17 Organize a set of data Calculate the mean, median, mode, and range of a set of data Describe the relationships between
More informationHomework 1 Solutions
18-9 Signals and Systems Profs. Byron Yu and Pulkit Grover Fall 18 Homework 1 Solutions Part One 1. (8 points) Consider the DT signal given by the algorithm: x[] = 1 x[1] = x[n] = x[n 1] x[n ] (a) Plot
More informationEquilibrium of rigid bodies Mehrdad Negahban (1999)
Equilibrium of rigid bodies Mehrdad Negahban (1999) Static equilibrium for a rigid body: A body (or any part of it) which is currently stationary will remain stationary if the resultant force and resultant
More informationchapter 12 MORE MATRIX ALGEBRA 12.1 Systems of Linear Equations GOALS
chapter MORE MATRIX ALGEBRA GOALS In Chapter we studied matrix operations and the algebra of sets and logic. We also made note of the strong resemblance of matrix algebra to elementary algebra. The reader
More informationMAC 1105 Lecture Outlines for Ms. Blackwelder s lecture classes
MAC 1105 Lecture Outlines for Ms. Blackwelder s lecture classes These notes are prepared using software that is designed for typing mathematics; it produces a pdf output. Alternative format is not available.
More informationMath 309 Notes and Homework for Days 4-6
Math 309 Notes and Homework for Days 4-6 Day 4 Read Section 1.2 and the notes below. The following is the main definition of the course. Definition. A vector space is a set V (whose elements are called
More informationHomework #1. Denote the sum we are interested in as To find we subtract the sum to find that
Homework #1 CMSC351 - Spring 2013 PRINT Name : Due: Feb 12 th at the start of class o Grades depend on neatness and clarity. o Write your answers with enough detail about your approach and concepts used,
More informationExperiment 1: Linear Regression
Experiment 1: Linear Regression August 27, 2018 1 Description This first exercise will give you practice with linear regression. These exercises have been extensively tested with Matlab, but they should
More informationOrthogonal Projection, Low Rank Approximation, and Orthogonal Bases
Week Orthogonal Projection, Low Rank Approximation, and Orthogonal Bases. Opening Remarks.. Low Rank Approximation 38 Week. Orthogonal Projection, Low Rank Approximation, and Orthogonal Bases 38.. Outline..
More informationBIOMED Programming & Modeling for BME Final Exam, , Instructor: Ahmet Sacan
BIOMED 201 - Programming & Modeling for BME Final Exam, 2011.12.01, Instructor: Ahmet Sacan Sign the honor code below. No credit will be given for the exam without a signed pledge. I have neither given
More informationCompA - Complex Analyzer
CompA - Complex Analyzer Xiping Liu(xl2639), Jianshuo Qiu(jq2253), Tianwu Wang(tw2576), Yingshuang Zheng(yz3083), Zhanpeng Su(zs2329) Septembee 25, 2017 1 Introduction The motivation for writing this language
More informationLAB 2: Orthogonal Projections, the Four Fundamental Subspaces, QR Factorization, and Inconsistent Linear Systems
Math 550A MATLAB Assignment #2 1 Revised 8/14/10 LAB 2: Orthogonal Projections, the Four Fundamental Subspaces, QR Factorization, and Inconsistent Linear Systems In this lab you will use Matlab to study
More informationOn my honor, as an Aggie, I have neither given nor received unauthorized aid on this academic work
Lab 5 : Linking Name: Sign the following statement: On my honor, as an Aggie, I have neither given nor received unauthorized aid on this academic work 1 Objective The main objective of this lab is to experiment
More informationIntroduction to ArcMap
Introduction to ArcMap ArcMap ArcMap is a Map-centric GUI tool used to perform map-based tasks Mapping Create maps by working geographically and interactively Display and present Export or print Publish
More informationPrecalculus, Quarter 4, Unit 4.1. Matrices. Overview
Precalculus, Quarter 4, Unit 4.1 Matrices Overview Number of instructional days: 11 (1 day = 45 60 minutes) Content to be learned Add, subtract, and use scalar multiplication with matrices and equivalent
More informationDesigning Information Devices and Systems I Fall 2018 Lecture Notes Note Introduction to Linear Algebra the EECS Way
EECS 16A Designing Information Devices and Systems I Fall 018 Lecture Notes Note 1 1.1 Introduction to Linear Algebra the EECS Way In this note, we will teach the basics of linear algebra and relate it
More informationVectors and Vector Arithmetic
Vectors and Vector Arithmetic Introduction and Goals: The purpose of this lab is to become familiar with the syntax of Maple commands for manipulating and graphing vectors. It will introduce you to basic
More informationProject 2: Using linear systems for numerical solution of boundary value problems
LINEAR ALGEBRA, MATH 124 Instructor: Dr. T.I. Lakoba Project 2: Using linear systems for numerical solution of boundary value problems Goal Introduce one of the most important applications of Linear Algebra
More informationSTEP Support Programme. Hints and Partial Solutions for Assignment 4
STEP Support Programme Hints and Partial Solutions for Assignment 4 Warm-up 1 (i) This question was asking you to prove that the angle at the centre of a circle is twice the angle at the circumference.
More informationWe know how to identify the location of a point by means of coordinates: (x, y) for a point in R 2, or (x, y,z) for a point in R 3.
Vectors We know how to identify the location of a point by means of coordinates: (x, y) for a point in R 2, or (x, y,z) for a point in R 3. More generally, n-dimensional real Euclidean space R n is the
More informationCS1112 Lecture 20. Lecture slides 1. Data are often related
Previous Lecture: File I/O, use of cell arra Toda s Lecture: Structures Structure arra (i.e., an arra of structures) A structure with arra fields Announcements: Project 5 due Thurs /5 at pm. Reduced late
More informationProblem Solving. Kurt Bryan. Here s an amusing little problem I came across one day last summer.
Introduction Problem Solving Kurt Bryan Here s an amusing little problem I came across one day last summer. Problem: Find three distinct positive integers whose reciprocals add up to one. Prove that the
More informationGive a geometric description of the set of points in space whose coordinates satisfy the given pair of equations.
1. Give a geometric description of the set of points in space whose coordinates satisfy the given pair of equations. x + y = 5, z = 4 Choose the correct description. A. The circle with center (0,0, 4)
More informationDesigning Information Devices and Systems I Spring 2019 Lecture Notes Note 2
EECS 6A Designing Information Devices and Systems I Spring 9 Lecture Notes Note Vectors and Matrices In the previous note, we introduced vectors and matrices as a way of writing systems of linear equations
More informationRatio of Polynomials Fit Many Variables
Chapter 376 Ratio of Polynomials Fit Many Variables Introduction This program fits a model that is the ratio of two polynomials of up to fifth order. Instead of a single independent variable, these polynomials
More informationHomework 9: Protein Folding & Simulated Annealing : Programming for Scientists Due: Thursday, April 14, 2016 at 11:59 PM
Homework 9: Protein Folding & Simulated Annealing 02-201: Programming for Scientists Due: Thursday, April 14, 2016 at 11:59 PM 1. Set up We re back to Go for this assignment. 1. Inside of your src directory,
More informationLecture 3: Vectors. In Song Kim. September 1, 2011
Lecture 3: Vectors In Song Kim September 1, 211 1 Solving Equations Up until this point we have been looking at different types of functions, often times graphing them. Each point on a graph is a solution
More information9.6 r-combinations with Repetition Allowed
584 Chapter 9 Counting and Probability Exercises 32 38 refer to the sequence of Stirling numbers of the second kind. 32. Find S 3,4 by exhibiting all the partitions of {x 1, x 2, x 3, x 4, x 5 } into four
More information4.2 SOLVING A LINEAR INEQUALITY
Algebra - II UNIT 4 INEQUALITIES Structure 4.0 Introduction 4.1 Objectives 4. Solving a Linear Inequality 4.3 Inequalities and Absolute Value 4.4 Linear Inequalities in two Variables 4.5 Procedure to Graph
More informationDesigning Information Devices and Systems I Spring 2015 Note 3
EECS 16A Designing Information Devices and Systems I Spring 2015 Note 3 Lecture notes by Christine Wang (01/27/2015) Introduction to Vectors Remark. Often, vectors are represented as letters in boldface(x),
More informationStatic and Kinetic Friction
Experiment 12 If you try to slide a heavy box resting on the floor, you may find it difficult to get the box moving. Static friction is the force that is acting against the box. If you apply a light horizontal
More informationAM205: Assignment 2. i=1
AM05: Assignment Question 1 [10 points] (a) [4 points] For p 1, the p-norm for a vector x R n is defined as: ( n ) 1/p x p x i p ( ) i=1 This definition is in fact meaningful for p < 1 as well, although
More informationMathematical Tools for Neuroscience (NEU 314) Princeton University, Spring 2016 Jonathan Pillow. Homework 8: Logistic Regression & Information Theory
Mathematical Tools for Neuroscience (NEU 34) Princeton University, Spring 206 Jonathan Pillow Homework 8: Logistic Regression & Information Theory Due: Tuesday, April 26, 9:59am Optimization Toolbox One
More informationIFM Chemistry Computational Chemistry 2010, 7.5 hp LAB2. Computer laboratory exercise 1 (LAB2): Quantum chemical calculations
Computer laboratory exercise 1 (LAB2): Quantum chemical calculations Introduction: The objective of the second computer laboratory exercise is to get acquainted with a program for performing quantum chemical
More informationOrthogonal Projection, Low Rank Approximation, and Orthogonal Bases
Week Orthogonal Projection, Low Rank Approximation, and Orthogonal Bases. Opening Remarks.. Low Rank Approximation 463 Week. Orthogonal Projection, Low Rank Approximation, and Orthogonal Bases 464.. Outline..
More informationCS 420/594: Complex Systems & Self-Organization Project 1: Edge of Chaos in 1D Cellular Automata Due: Sept. 20
CS 420/594: Complex Systems & Self-Organization Project 1: Edge of Chaos in 1D Cellular Automata Due: Sept. 20 Introduction In this project you will explore Edge of Chaos phenomena (Wolfram class IV behavior)
More informationMATH.2720 Introduction to Programming with MATLAB Vector and Matrix Algebra
MATH.2720 Introduction to Programming with MATLAB Vector and Matrix Algebra A. Vectors A vector is a quantity that has both magnitude and direction, like velocity. The location of a vector is irrelevant;
More informationLAB 1: MATLAB - Introduction to Programming. Objective:
LAB 1: MATLAB - Introduction to Programming Objective: The objective of this laboratory is to review how to use MATLAB as a programming tool and to review a classic analytical solution to a steady-state
More informationCalifornia Common Core State Standards for Mathematics Standards Map Mathematics I
A Correlation of Pearson Integrated High School Mathematics Mathematics I Common Core, 2014 to the California Common Core State s for Mathematics s Map Mathematics I Copyright 2017 Pearson Education, Inc.
More informationFoundations of Computation
The Australian National University Semester 2, 2018 Research School of Computer Science Tutorial 1 Dirk Pattinson Foundations of Computation The tutorial contains a number of exercises designed for the
More informationMOL410/510 Problem Set 1 - Linear Algebra - Due Friday Sept. 30
MOL40/50 Problem Set - Linear Algebra - Due Friday Sept. 30 Use lab notes to help solve these problems. Problems marked MUST DO are required for full credit. For the remainder of the problems, do as many
More informationIntroduction to Computational Neuroscience
CSE2330 Introduction to Computational Neuroscience Basic computational tools and concepts Tutorial 1 Duration: two weeks 1.1 About this tutorial The objective of this tutorial is to introduce you to: the
More informationNotes for Math 152: Linear Systems Spring, 2013
Notes for Math 5: Linear Systems Spring, 3 Richard Froese and Brian Wetton Richard Froese and Brian Wetton. Permission is granted to make and distribute copies of this document provided the copyright notice
More informationCS154, Lecture 15: Cook-Levin Theorem SAT, 3SAT
CS154, Lecture 15: Cook-Levin Theorem SAT, 3SAT Definition: A language B is NP-complete if: 1. B NP 2. Every A in NP is poly-time reducible to B That is, A P B When this is true, we say B is NP-hard On
More informationTMA4220: Programming project - part 1
TMA4220: Programming project - part 1 TMA4220 - Numerical solution of partial differential equations using the finite element method The programming project will be split into two parts. This is the first
More informationPRIMES Math Problem Set
PRIMES Math Problem Set PRIMES 017 Due December 1, 01 Dear PRIMES applicant: This is the PRIMES 017 Math Problem Set. Please send us your solutions as part of your PRIMES application by December 1, 01.
More informationSECONDARY MATHEMATICS I
SECONDARY MATHEMATICS I THE FUNDAMENTAL PURPOSE OF SECONDARY MATHEMATICS I is to formalize and extend the mathematics that students learned in the middle grades. The critical areas, organized into units,
More informationCovariance and Dot Product
Covariance and Dot Product 1 Introduction. As you learned in Calculus III and Linear Algebra, the dot product of two vectors x = (x 1,..., x n ) and y = (y 1,..., y n ) in R n is the number n := x i y
More informationLinear Algebra Homework and Study Guide
Linear Algebra Homework and Study Guide Phil R. Smith, Ph.D. February 28, 20 Homework Problem Sets Organized by Learning Outcomes Test I: Systems of Linear Equations; Matrices Lesson. Give examples of
More information1.2 The Role of Variables
1.2 The Role of Variables variables sentences come in several flavors true false conditional In this section, a name is given to mathematical sentences that are sometimes true, sometimes false they are
More informationMon Jan Improved acceleration models: linear and quadratic drag forces. Announcements: Warm-up Exercise:
Math 2250-004 Week 4 notes We will not necessarily finish the material from a given day's notes on that day. We may also add or subtract some material as the week progresses, but these notes represent
More informationLecture 3: Special Matrices
Lecture 3: Special Matrices Feedback of assignment1 Random matrices The magic matrix commend magic() doesn t give us random matrix. Random matrix means we will get different matrices each time when we
More informationStudent Activity Sheet- Denali Topo Map
Student Activity Sheet- Denali Topo Map Directions: Follow the steps in order and answer the associated questions as you proceed through the activity. The first part of the activity will be guided by your
More informationMatter & Interactions I Fall 2016
33-151 Matter & Interactions I Fall 2016 Name (Printed) Instructor Signature for 9.P70 (a): Instructor Signature for 9.P70 (b): Instructor Signature for 9.P70 (c): Instructor Signature for 9.P71: Due Date:
More informationApplied Linear Algebra in Geoscience Using MATLAB
Applied Linear Algebra in Geoscience Using MATLAB Contents Getting Started Creating Arrays Mathematical Operations with Arrays Using Script Files and Managing Data Two-Dimensional Plots Programming in
More informationMATH 12 CLASS 2 NOTES, SEP Contents. 2. Dot product: determining the angle between two vectors 2
MATH 12 CLASS 2 NOTES, SEP 23 2011 Contents 1. Dot product: definition, basic properties 1 2. Dot product: determining the angle between two vectors 2 Quick links to definitions/theorems Dot product definition
More informationVideo : Numerical Methods for PDEs : IntroductionJanuary to Matlab 30, and 2015 Vectors1 / 13
Video : 22.520 Numerical Methods for PDEs : Introduction to Matlab and January 30, 2015 Video : 22.520 Numerical Methods for PDEs : IntroductionJanuary to Matlab 30, and 2015 1 / 13 What is the goal of
More informationRelations and Functions
Algebra 1, Quarter 2, Unit 2.1 Relations and Functions Overview Number of instructional days: 10 (2 assessments) (1 day = 45 60 minutes) Content to be learned Demonstrate conceptual understanding of linear
More informationExample 1 (Characteristic Equation, Eigenvalue, and Eigenvector)
Matlab Lab 3 Example 1 (Characteristic Equation, Eigenvalue, and Eigenvector) A polynomial equation is uniquely determined by the coefficients of the monomial terms. For example, the quadratic equation
More informationAMS 27L LAB #8 Winter 2009
AMS 27L LAB #8 Winter 29 Solving ODE s in Matlab Objectives:. To use Matlab s ODE Solvers 2. To practice using functions and in-line functions Matlab s ODE Suite Matlab offers a suite of ODE solvers including:
More informationComputer projects for Mathematical Statistics, MA 486. Some practical hints for doing computer projects with MATLAB:
Computer projects for Mathematical Statistics, MA 486. Some practical hints for doing computer projects with MATLAB: You can save your project to a text file (on a floppy disk or CD or on your web page),
More informationLecture 5b: Starting Matlab
Lecture 5b: Starting Matlab James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University August 7, 2013 Outline 1 Resources 2 Starting Matlab 3 Homework
More informationTutorial Three: Loops and Conditionals
Tutorial Three: Loops and Conditionals Imad Pasha Chris Agostino February 18, 2015 1 Introduction In lecture Monday we learned that combinations of conditionals and loops could make our code much more
More informationVectors Part 1: Two Dimensions
Vectors Part 1: Two Dimensions Last modified: 20/02/2018 Links Scalars Vectors Definition Notation Polar Form Compass Directions Basic Vector Maths Multiply a Vector by a Scalar Unit Vectors Example Vectors
More informationRoss Program 2017 Application Problems
Ross Program 2017 Application Problems This document is part of the application to the Ross Mathematics Program, and is posted at http://u.osu.edu/rossmath/. The Admission Committee will start reading
More information(a) Compute the projections of vectors [1,0,0] and [0,1,0] onto the line spanned by a Solution: The projection matrix is P = 1
6 [3] 3. Consider the plane S defined by 2u 3v+w = 0, and recall that the normal to this plane is the vector a = [2, 3,1]. (a) Compute the projections of vectors [1,0,0] and [0,1,0] onto the line spanned
More informationPROOF WITHOUT WORDS MATH CIRCLE (BEGINNERS) 05/06/2012
PROOF WITHOUT WORDS MATH CIRCLE (BEGINNERS) 05/06/2012 If you ve been with us for a little while, you ve already seen some examples of proofs without words. Remember a proof is just an airtight argument
More informationL3: Review of linear algebra and MATLAB
L3: Review of linear algebra and MATLAB Vector and matrix notation Vectors Matrices Vector spaces Linear transformations Eigenvalues and eigenvectors MATLAB primer CSCE 666 Pattern Analysis Ricardo Gutierrez-Osuna
More informationContinuing Quadratic/Polynomial Real-World Problems
Algebra 1, Quarter 3, Unit 3.1 Continuing Quadratic/Polynomial Real-World Problems Overview Number of instructional days: 15 (1 day = 45 60 minutes) Content to be learned Understand closed operations.
More informationNotes for Math 152: Linear Systems Spring, 2017
Notes for Math 5: Linear Systems Spring, 7 Richard Froese and Brian Wetton 6 Richard Froese and Brian Wetton Permission is granted to make and distribute copies of this document provided the copyright
More informationVectors for Beginners
Vectors for Beginners Leo Dorst September 6, 2007 1 Three ways of looking at linear algebra We will always try to look at what we do in linear algebra at three levels: geometric: drawing a picture. This
More informationQuadratics and Other Polynomials
Algebra 2, Quarter 2, Unit 2.1 Quadratics and Other Polynomials Overview Number of instructional days: 15 (1 day = 45 60 minutes) Content to be learned Know and apply the Fundamental Theorem of Algebra
More informationDesigning Information Devices and Systems I Spring 2017 Babak Ayazifar, Vladimir Stojanovic Midterm 1
EECS 16A Designing Information Devices and Systems I Spring 2017 Babak Ayazifar, Vladimir Stojanovic Midterm 1 Exam location: 2050 VLSB, Last Name: Surpenant-Zzz PRINT your student ID: PRINT AND SIGN your
More information