The Computable Differential Equation Lecture ... - Bruce E. Shapiro
The Computable Differential Equation Lecture ... - Bruce E. Shapiro The Computable Differential Equation Lecture ... - Bruce E. Shapiro
vi CONTENTS Math 582B, Spring 2007 California State University Northridge c○2007, B.E.Shapiro Last revised: May 23, 2007
Chapter 1 Classifying The Problem 1.1 Defining ODEs Definition 1.1 (Ordinary Differential Equation, ODE). Let y ∈ R n be a variable 1 that depends on t. Then we define a differential equation as any equation of the form F (t, y, y ′ ) = 0 (1.1) where F is any function of the 2n + 1 variables t, y 1 , y 2 , . . . , y n , y ′ 1 , y′ 2 , . . . , y′ n+1 . Definition 1.2. We will call any function φ(t) that satisfies a solution of the differential equation. F ( t, φ(t), φ ′ (t) ) = 0 (1.2) We will use the terms “Ordinary Differential Equation” and “Differential Equation”, as well as the abbreviations ODE and DE, interchangeably. More generally, on can include partial derivatives in the definition, in which case one must distinguish between “Partial” DEs (PDEs) and “Ordinary” DEs (ODEs). We will leave the study of PDEs to another class. Equation 1.1 is, in general, very difficult, and often, impossible, to solve, either analytically (e.g., by finding a formula that describes y), or numerically (e.g., for example, by using a computer to draw a picture of the graph of the solution). Often it is possible to solve 1.1 explicitly for the derivatives: y ′ = f(t, y) (1.3) Many important problems can be put into this form, and solutions are known to exists for a wide class of functions, particular as a result of theorem 1.3. The class of problems in which equation 1.1 can be converted to the form 1.3, at least locally, is not seriously restrictive from a practical point of view. The only requirements are 1 It may be either a scalar variable, in which case n = 1, or a vector variables, in which case n is the number of components of the vector. 1
- Page 1 and 2: The Computable Differential Equatio
- Page 3 and 4: Contents 1 Classifying The Problem
- Page 5: CONTENTS v Timeline on Computable D
- Page 9 and 10: CHAPTER 1. CLASSIFYING THE PROBLEM
- Page 11 and 12: CHAPTER 1. CLASSIFYING THE PROBLEM
- Page 13 and 14: CHAPTER 1. CLASSIFYING THE PROBLEM
- Page 15 and 16: CHAPTER 1. CLASSIFYING THE PROBLEM
- Page 17 and 18: CHAPTER 1. CLASSIFYING THE PROBLEM
- Page 19 and 20: CHAPTER 1. CLASSIFYING THE PROBLEM
- Page 21 and 22: CHAPTER 1. CLASSIFYING THE PROBLEM
- Page 23 and 24: CHAPTER 1. CLASSIFYING THE PROBLEM
- Page 25 and 26: CHAPTER 1. CLASSIFYING THE PROBLEM
- Page 27 and 28: CHAPTER 1. CLASSIFYING THE PROBLEM
- Page 29 and 30: CHAPTER 1. CLASSIFYING THE PROBLEM
- Page 31 and 32: Chapter 2 Successive Approximations
- Page 33 and 34: CHAPTER 2. SUCCESSIVE APPROXIMATION
- Page 35 and 36: CHAPTER 2. SUCCESSIVE APPROXIMATION
- Page 37 and 38: CHAPTER 2. SUCCESSIVE APPROXIMATION
- Page 39 and 40: CHAPTER 2. SUCCESSIVE APPROXIMATION
- Page 41 and 42: CHAPTER 2. SUCCESSIVE APPROXIMATION
- Page 43 and 44: CHAPTER 2. SUCCESSIVE APPROXIMATION
- Page 45 and 46: CHAPTER 2. SUCCESSIVE APPROXIMATION
- Page 47 and 48: CHAPTER 2. SUCCESSIVE APPROXIMATION
- Page 49 and 50: Chapter 3 Approximate Solutions 3.1
- Page 51 and 52: CHAPTER 3. APPROXIMATE SOLUTIONS 45
- Page 53 and 54: CHAPTER 3. APPROXIMATE SOLUTIONS 47
- Page 55 and 56: CHAPTER 3. APPROXIMATE SOLUTIONS 49
vi<br />
CONTENTS<br />
Math 582B, Spring 2007<br />
California State University Northridge<br />
c○2007, B.E.<strong>Shapiro</strong><br />
Last revised: May 23, 2007