Elementary Functions the Sine Wave Cosine Symmetries of Sine And
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Trigonometric Functions
Trigonometric Functions This worksheet covers the basic characteristics of the sine, cosine, tangent, cotangent, secant, and cosecant trigonometric functions. Sine Function: f(x) = sin (x) • Graph • Domain: all real numbers • Range: [-1 , 1] • Period = 2π • x intercepts: x = kπ , where k is an integer. • y intercepts: y = 0 • Maximum points: (π/2 + 2kπ, 1), where k is an integer. • Minimum points: (3π/2 + 2kπ, -1), where k is an integer. • Symmetry: since sin (–x) = –sin (x) then sin(x) is an odd function and its graph is symmetric with respect to the origin (0, 0). • Intervals of increase/decrease: over one period and from 0 to 2π, sin (x) is increasing on the intervals (0, π/2) and (3π/2 , 2π), and decreasing on the interval (π/2 , 3π/2). Tutoring and Learning Centre, George Brown College 2014 www.georgebrown.ca/tlc Trigonometric Functions Cosine Function: f(x) = cos (x) • Graph • Domain: all real numbers • Range: [–1 , 1] • Period = 2π • x intercepts: x = π/2 + k π , where k is an integer. • y intercepts: y = 1 • Maximum points: (2 k π , 1) , where k is an integer. • Minimum points: (π + 2 k π , –1) , where k is an integer. • Symmetry: since cos(–x) = cos(x) then cos (x) is an even function and its graph is symmetric with respect to the y axis. • Intervals of increase/decrease: over one period and from 0 to 2π, cos (x) is decreasing on (0 , π) increasing on (π , 2π). Tutoring and Learning Centre, George Brown College 2014 www.georgebrown.ca/tlc Trigonometric Functions Tangent Function : f(x) = tan (x) • Graph • Domain: all real numbers except π/2 + k π, k is an integer. -
Lesson 6: Trigonometric Identities
1. Introduction An identity is an equality relationship between two mathematical expressions. For example, in basic algebra students are expected to master various algbriac factoring identities such as a2 − b2 =(a − b)(a + b)or a3 + b3 =(a + b)(a2 − ab + b2): Identities such as these are used to simplifly algebriac expressions and to solve alge- a3 + b3 briac equations. For example, using the third identity above, the expression a + b simpliflies to a2 − ab + b2: The first identiy verifies that the equation (a2 − b2)=0is true precisely when a = b: The formulas or trigonometric identities introduced in this lesson constitute an integral part of the study and applications of trigonometry. Such identities can be used to simplifly complicated trigonometric expressions. This lesson contains several examples and exercises to demonstrate this type of procedure. Trigonometric identities can also used solve trigonometric equations. Equations of this type are introduced in this lesson and examined in more detail in Lesson 7. For student’s convenience, the identities presented in this lesson are sumarized in Appendix A 2. The Elementary Identities Let (x; y) be the point on the unit circle centered at (0; 0) that determines the angle t rad : Recall that the definitions of the trigonometric functions for this angle are sin t = y tan t = y sec t = 1 x y : cos t = x cot t = x csc t = 1 y x These definitions readily establish the first of the elementary or fundamental identities given in the table below. For obvious reasons these are often referred to as the reciprocal and quotient identities. -
Music Synthesis
MUSIC SYNTHESIS Sound synthesis is the art of using electronic devices to create & modify signals that are then turned into sound waves by a speaker. Making Waves: WGRL - 2015 Oscillators An oscillator generates a consistent, repeating signal. Signals from oscillators and other sources are used to control the movement of the cones in our speakers, which make real sound waves which travel to our ears. An oscillator wiggles an audio signal. DEMONSTRATE: If you tie one end of a rope to a doorknob, stand back a few feet, and wiggle the other end of the rope up and down really fast, you're doing roughly the same thing as an oscillator. REVIEW: Frequency and pitch Frequency, measured in cycles/second AKA Hertz, is the rate at which a sound wave moves in and out. The length of a signal cycle of a waveform is the span of time it takes for that waveform to repeat. People generally hear an increase in the frequency of a sound wave as an increase in pitch. F DEMONSTRATE: an oscillator generating a signal that repeats at the rate of 440 cycles per second will have the same pitch as middle A on a piano. An oscillator generating a signal that repeats at 880 cycles per second will have the same pitch as the A an octave above middle A. Types of Waveforms: SINE The SINE wave is the most basic, pure waveform. These simple waves have only one frequency. Any other waveform can be created by adding up a series of sine waves. In this picture, the first two sine waves In this picture, a sine wave is added to its are added together to produce a third. -
Calculus Terminology
AP Calculus BC Calculus Terminology Absolute Convergence Asymptote Continued Sum Absolute Maximum Average Rate of Change Continuous Function Absolute Minimum Average Value of a Function Continuously Differentiable Function Absolutely Convergent Axis of Rotation Converge Acceleration Boundary Value Problem Converge Absolutely Alternating Series Bounded Function Converge Conditionally Alternating Series Remainder Bounded Sequence Convergence Tests Alternating Series Test Bounds of Integration Convergent Sequence Analytic Methods Calculus Convergent Series Annulus Cartesian Form Critical Number Antiderivative of a Function Cavalieri’s Principle Critical Point Approximation by Differentials Center of Mass Formula Critical Value Arc Length of a Curve Centroid Curly d Area below a Curve Chain Rule Curve Area between Curves Comparison Test Curve Sketching Area of an Ellipse Concave Cusp Area of a Parabolic Segment Concave Down Cylindrical Shell Method Area under a Curve Concave Up Decreasing Function Area Using Parametric Equations Conditional Convergence Definite Integral Area Using Polar Coordinates Constant Term Definite Integral Rules Degenerate Divergent Series Function Operations Del Operator e Fundamental Theorem of Calculus Deleted Neighborhood Ellipsoid GLB Derivative End Behavior Global Maximum Derivative of a Power Series Essential Discontinuity Global Minimum Derivative Rules Explicit Differentiation Golden Spiral Difference Quotient Explicit Function Graphic Methods Differentiable Exponential Decay Greatest Lower Bound Differential -
Derivation of Sum and Difference Identities for Sine and Cosine
Derivation of sum and difference identities for sine and cosine John Kerl January 2, 2012 The authors of your trigonometry textbook give a geometric derivation of the sum and difference identities for sine and cosine. I find this argument unwieldy | I don't expect you to remember it; in fact, I don't remember it. There's a standard algebraic derivation which is far simpler. The only catch is that you need to use complex arithmetic, which we don't cover in Math 111. Nonetheless, I will present the derivation so that you will have seen how simple the truth can be, and so that you may come to understand it after you've had a few more math courses. And in fact, all you need are the following facts: • Complex numbers are of the form a+bi, where a and b are real numbers and i is defined to be a square root of −1. That is, i2 = −1. (Of course, (−i)2 = −1 as well, so −i is the other square root of −1.) • The number a is called the real part of a + bi; the number b is called the imaginary part of a + bi. All the real numbers you're used to working with are already complex numbers | they simply have zero imaginary part. • To add or subtract complex numbers, add the corresponding real and imaginary parts. For example, 2 + 3i plus 4 + 5i is 6 + 8i. • To multiply two complex numbers a + bi and c + di, just FOIL out the product (a + bi)(c + di) and use the fact that i2 = −1. -
Complex Numbers and Functions
Complex Numbers and Functions Richard Crew January 20, 2018 This is a brief review of the basic facts of complex numbers, intended for students in my section of MAP 4305/5304. I will discuss basic facts of com- plex arithmetic, limits and derivatives of complex functions, power series and functions like the complex exponential, sine and cosine which can be defined by convergent power series. This is a preliminary version and will be added to later. 1 Complex Numbers 1.1 Arithmetic. A complex number is an expression a + bi where i2 = −1. Here the real number a is the real part of the complex number and bi is the imaginary part. If z is a complex number we write <(z) and =(z) for the real and imaginary parts respectively. Two complex numbers are equal if and only if their real and imaginary parts are equal. In particular a + bi = 0 only when a = b = 0. The set of complex numbers is denoted by C. Complex numbers are added, subtracted and multiplied according to the usual rules of algebra: (a + bi) + (c + di) = (a + c) + (b + di) (1.1) (a + bi) − (c + di) = (a − c) + (b − di) (1.2) (a + bi)(c + di) = (ac − bd) + (ad + bc)i (1.3) (note how i2 = −1 has been used in the last equation). Division performed by rationalizing the denominator: a + bi (a + bi)(c − di) (ac − bd) + (bc − ad)i = = (1.4) c + di (c + di)(c − di) c2 + d2 Note that denominator only vanishes if c + di = 0, so that a complex number can be divided by any nonzero complex number. -
Interference: Two Spherical Sources Superposition
Interference: Two Spherical Sources Superposition Interference Waves ADD: Constructive Interference. Waves SUBTRACT: Destructive Interference. In Phase Out of Phase Superposition Traveling waves move through each other, interfere, and keep on moving! Pulsed Interference Superposition Waves ADD in space. Any complex wave can be built from simple sine waves. Simply add them point by point. Simple Sine Wave Simple Sine Wave Complex Wave Fourier Synthesis of a Square Wave Any periodic function can be represented as a series of sine and cosine terms in a Fourier series: y() t ( An sin2ƒ n t B n cos2ƒ) n t n Superposition of Sinusoidal Waves • Case 1: Identical, same direction, with phase difference (Interference) Both 1-D and 2-D waves. • Case 2: Identical, opposite direction (standing waves) • Case 3: Slightly different frequencies (Beats) Superposition of Sinusoidal Waves • Assume two waves are traveling in the same direction, with the same frequency, wavelength and amplitude • The waves differ in phase • y1 = A sin (kx - wt) • y2 = A sin (kx - wt + f) • y = y1+y2 = 2A cos (f/2) sin (kx - wt + f/2) Resultant Amplitude Depends on phase: Spatial Interference Term Sinusoidal Waves with Constructive Interference y = y1+y2 = 2A cos (f/2) sin (kx - wt + f /2) • When f = 0, then cos (f/2) = 1 • The amplitude of the resultant wave is 2A – The crests of one wave coincide with the crests of the other wave • The waves are everywhere in phase • The waves interfere constructively Sinusoidal Waves with Destructive Interference y = y1+y2 = 2A cos (f/2) -
Inverse Trig Functions Summary
Inverse trigonometric functions 1 1 z = sec ϑ The inverse sine function. The sine function restricted to [ π, π ] is one-to-one, and its inverse on this 3 − 2 2 ϑ = π ϑ = arcsec z interval is called the arcsine (arcsin) function. The domain of arcsin is [ 1, 1] and the range of arcsin is 2 1 1 1 −1 [ π, π ]. Below is a graph of y = sin ϑ, with the the part over [ π, π ] emphasized, and the graph − 2 2 − 2 2 of ϑ y. π 1 = arcsin ϑ = 2 π y = sin ϑ ϑ = arcsin y 1 π π 2 π − 1 ϑ 1 1 z − 1 π 1 π ϑ 1 1 y − 2 2 − 1 − 1 1 3 π ϑ = 2 π ϑ = 2 π − 2 By definition, By definition, 1 1 1 3 ϑ = arcsin y means that sin ϑ = y and π 6 ϑ 6 π. ϑ = arcsec z means that sec ϑ = t and 0 6 ϑ< 2 π or π 6 ϑ< 2 π. − 2 2 Differentiating the equation on the right implicitly with respect to y, gives Again, differentiating the equation on the right implicitly with respect to z, and using the restriction in ϑ, dϑ dϑ 1 1 1 one computes the derivative cos ϑ = 1, or = , provided π<ϑ< π. dy dy cos ϑ − 2 2 d 1 (arcsec z)= 2 , for z > 1. 1 1 2 2 dz z√z 1 | | Since cos ϑ> 0 on ( 2 π, 2 π ), it follows that cos ϑ = p1 sin ϑ = p1 y . -
Chapter 1 Waves in Two and Three Dimensions
Chapter 1 Waves in Two and Three Dimensions In this chapter we extend the ideas of the previous chapter to the case of waves in more than one dimension. The extension of the sine wave to higher dimensions is the plane wave. Wave packets in two and three dimensions arise when plane waves moving in different directions are superimposed. Diffraction results from the disruption of a wave which is impingent upon an object. Those parts of the wave front hitting the object are scattered, modified, or destroyed. The resulting diffraction pattern comes from the subsequent interference of the various pieces of the modified wave. A knowl- edge of diffraction is necessary to understand the behavior and limitations of optical instruments such as telescopes. Diffraction and interference in two and three dimensions can be manipu- lated to produce useful devices such as the diffraction grating. 1.1 Math Tutorial — Vectors Before we can proceed further we need to explore the idea of a vector. A vector is a quantity which expresses both magnitude and direction. Graph- ically we represent a vector as an arrow. In typeset notation a vector is represented by a boldface character, while in handwriting an arrow is drawn over the character representing the vector. Figure 1.1 shows some examples of displacement vectors, i. e., vectors which represent the displacement of one object from another, and introduces 1 CHAPTER 1. WAVES IN TWO AND THREE DIMENSIONS 2 y Paul B y B C C y George A A y Mary x A x B x C x Figure 1.1: Displacement vectors in a plane. -
Tektronix Signal Generator
Signal Generator Fundamentals Signal Generator Fundamentals Table of Contents The Complete Measurement System · · · · · · · · · · · · · · · 5 Complex Waves · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 15 The Signal Generator · · · · · · · · · · · · · · · · · · · · · · · · · · · · 6 Signal Modulation · · · · · · · · · · · · · · · · · · · · · · · · · · · 15 Analog or Digital? · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 7 Analog Modulation · · · · · · · · · · · · · · · · · · · · · · · · · 15 Basic Signal Generator Applications· · · · · · · · · · · · · · · · 8 Digital Modulation · · · · · · · · · · · · · · · · · · · · · · · · · · 15 Verification · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 8 Frequency Sweep · · · · · · · · · · · · · · · · · · · · · · · · · · · 16 Testing Digital Modulator Transmitters and Receivers · · 8 Quadrature Modulation · · · · · · · · · · · · · · · · · · · · · 16 Characterization · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 8 Digital Patterns and Formats · · · · · · · · · · · · · · · · · · · 16 Testing D/A and A/D Converters · · · · · · · · · · · · · · · · · 8 Bit Streams · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 17 Stress/Margin Testing · · · · · · · · · · · · · · · · · · · · · · · · · · · 9 Types of Signal Generators · · · · · · · · · · · · · · · · · · · · · · 17 Stressing Communication Receivers · · · · · · · · · · · · · · 9 Analog and Mixed Signal Generators · · · · · · · · · · · · · · 18 Signal Generation Techniques -
American Protestantism and the Kyrias School for Girls, Albania By
Of Women, Faith, and Nation: American Protestantism and the Kyrias School For Girls, Albania by Nevila Pahumi A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (History) in the University of Michigan 2016 Doctoral Committee: Professor Pamela Ballinger, Co-Chair Professor John V.A. Fine, Co-Chair Professor Fatma Müge Göçek Professor Mary Kelley Professor Rudi Lindner Barbara Reeves-Ellington, University of Oxford © Nevila Pahumi 2016 For my family ii Acknowledgements This project has come to life thanks to the support of people on both sides of the Atlantic. It is now the time and my great pleasure to acknowledge each of them and their efforts here. My long-time advisor John Fine set me on this path. John’s recovery, ten years ago, was instrumental in directing my plans for doctoral study. My parents, like many well-intended first generation immigrants before and after them, wanted me to become a different kind of doctor. Indeed, I made a now-broken promise to my father that I would follow in my mother’s footsteps, and study medicine. But then, I was his daughter, and like him, I followed my own dream. When made, the choice was not easy. But I will always be grateful to John for the years of unmatched guidance and support. In graduate school, I had the great fortune to study with outstanding teacher-scholars. It is my committee members whom I thank first and foremost: Pamela Ballinger, John Fine, Rudi Lindner, Müge Göcek, Mary Kelley, and Barbara Reeves-Ellington. -
Fourier Analysis
FOURIER ANALYSIS Lucas Illing 2008 Contents 1 Fourier Series 2 1.1 General Introduction . 2 1.2 Discontinuous Functions . 5 1.3 Complex Fourier Series . 7 2 Fourier Transform 8 2.1 Definition . 8 2.2 The issue of convention . 11 2.3 Convolution Theorem . 12 2.4 Spectral Leakage . 13 3 Discrete Time 17 3.1 Discrete Time Fourier Transform . 17 3.2 Discrete Fourier Transform (and FFT) . 19 4 Executive Summary 20 1 1. Fourier Series 1 Fourier Series 1.1 General Introduction Consider a function f(τ) that is periodic with period T . f(τ + T ) = f(τ) (1) We may always rescale τ to make the function 2π periodic. To do so, define 2π a new independent variable t = T τ, so that f(t + 2π) = f(t) (2) So let us consider the set of all sufficiently nice functions f(t) of a real variable t that are periodic, with period 2π. Since the function is periodic we only need to consider its behavior on one interval of length 2π, e.g. on the interval (−π; π). The idea is to decompose any such function f(t) into an infinite sum, or series, of simpler functions. Following Joseph Fourier (1768-1830) consider the infinite sum of sine and cosine functions 1 a0 X f(t) = + [a cos(nt) + b sin(nt)] (3) 2 n n n=1 where the constant coefficients an and bn are called the Fourier coefficients of f. The first question one would like to answer is how to find those coefficients.