Differential and Integral Calculus for Logical Operations a Matrix-Vector Approach
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Handbook Vatican 2014
HANDBOOK OF THE WORLD CONGRESS ON THE SQUARE OF OPPOSITION IV Pontifical Lateran University, Vatican May 5-9, 2014 Edited by Jean-Yves Béziau and Katarzyna Gan-Krzywoszyńska www.square-of-opposition.org 1 2 Contents 1. Fourth World Congress on the Square of Opposition ..................................................... 7 1.1. The Square : a Central Object for Thought ..................................................................................7 1.2. Aim of the Congress.....................................................................................................................8 1.3. Scientific Committee ...................................................................................................................9 1.4. Organizing Committee .............................................................................................................. 10 2. Plenary Lectures ................................................................................................... 11 Gianfranco Basti "Scientia una contrariorum": Paraconsistency, Induction, and Formal Ontology ..... 11 Jean-Yves Béziau Square of Opposition: Past, Present and Future ....................................................... 12 Manuel Correia Machuca The Didactic and Theoretical Expositions of the Square of Opposition in Aristotelian logic ....................................................................................................................... 13 Rusty Jones Bivalence and Contradictory Pairs in Aristotle’s De Interpretatione ................................ -
Antiderivatives and the Area Problem
Chapter 7 antiderivatives and the area problem Let me begin by defining the terms in the title: 1. an antiderivative of f is another function F such that F 0 = f. 2. the area problem is: ”find the area of a shape in the plane" This chapter is concerned with understanding the area problem and then solving it through the fundamental theorem of calculus(FTC). We begin by discussing antiderivatives. At first glance it is not at all obvious this has to do with the area problem. However, antiderivatives do solve a number of interesting physical problems so we ought to consider them if only for that reason. The beginning of the chapter is devoted to understanding the type of question which an antiderivative solves as well as how to perform a number of basic indefinite integrals. Once all of this is accomplished we then turn to the area problem. To understand the area problem carefully we'll need to think some about the concepts of finite sums, se- quences and limits of sequences. These concepts are quite natural and we will see that the theory for these is easily transferred from some of our earlier work. Once the limit of a sequence and a number of its basic prop- erties are established we then define area and the definite integral. Finally, the remainder of the chapter is devoted to understanding the fundamental theorem of calculus and how it is applied to solve definite integrals. I have attempted to be rigorous in this chapter, however, you should understand that there are superior treatments of integration(Riemann-Stieltjes, Lesbeque etc..) which cover a greater variety of functions in a more logically complete fashion. -
Proceedings of the 30 Nordic Workshop on Programming Theory
Proceedings of the 30th Nordic Workshop on Programming Theory Daniel S. Fava Einar B. Johnsen Olaf Owe Editors Report Nr. 485 ISBN 978-82-7368-450-9 Department of Informatics Faculty of Mathematics and Natural Sciences UNIVERSITY OF OSLO October 24, 2018 NWPT'18 Preface Preface This volume contains the extended abstracts of the talks presented at the 30th Nordic Workshop on Programming Theory held on October 24-26, 2018 in Oslo, Norway. The objective of Nordic Workshop on Programming Theory is to bring together researchers from the Nordic and Baltic countries interested in programming theory, in order to improve mutual contacts and co-operation. However, the workshop also attracts researchers outside this geographical area. In particular, it is targeted at early- stage researchers as a friendly meeting where one can present work in progress. Typical topics of the workshop include: • semantics of programming languages, • programming language design and programming methodology, • programming logics, • formal specification of programs, • program verification, • program construction, • tools for program verification and construction, • program transformation and refinement, • real-time and hybrid systems, • models of concurrency and distributed computing, • language-based security. This volume contains 29 extended abstracts of the presentations at the workshop including the abstracts of the three distinguished invited speakers. Prof. Andrei Sabelfeld, Chalmers University, Sweden Prof. Erika Abrah´am,RWTH´ Aachen University, Germany Prof. Peter Olveczky,¨ University of Oslo, Norway After the workshop selected papers will be invited, based on the quality and topic of their presentation at the workshop, for submission to a special issue of The Journal of Logic and Algebraic Methods in Programming. -
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 -
Notes Chapter 4(Integration) Definition of an Antiderivative
1 Notes Chapter 4(Integration) Definition of an Antiderivative: A function F is an antiderivative of f on an interval I if for all x in I. Representation of Antiderivatives: If F is an antiderivative of f on an interval I, then G is an antiderivative of f on the interval I if and only if G is of the form G(x) = F(x) + C, for all x in I where C is a constant. Sigma Notation: The sum of n terms a1,a2,a3,…,an is written as where I is the index of summation, ai is the ith term of the sum, and the upper and lower bounds of summation are n and 1. Summation Formulas: 1. 2. 3. 4. Limits of the Lower and Upper Sums: Let f be continuous and nonnegative on the interval [a,b]. The limits as n of both the lower and upper sums exist and are equal to each other. That is, where are the minimum and maximum values of f on the subinterval. Definition of the Area of a Region in the Plane: Let f be continuous and nonnegative on the interval [a,b]. The area if a region bounded by the graph of f, the x-axis and the vertical lines x=a and x=b is Area = where . Definition of a Riemann Sum: Let f be defined on the closed interval [a,b], and let be a partition of [a,b] given by a =x0<x1<x2<…<xn-1<xn=b where xi is the width of the ith subinterval. -
4.1 AP Calc Antiderivatives and Indefinite Integration.Notebook November 28, 2016
4.1 AP Calc Antiderivatives and Indefinite Integration.notebook November 28, 2016 4.1 Antiderivatives and Indefinite Integration Learning Targets 1. Write the general solution of a differential equation 2. Use indefinite integral notation for antiderivatives 3. Use basic integration rules to find antiderivatives 4. Find a particular solution of a differential equation 5. Plot a slope field 6. Working backwards in physics Intro/Warmup 1 4.1 AP Calc Antiderivatives and Indefinite Integration.notebook November 28, 2016 Note: I am changing up the procedure of the class! When you walk in the class, you will put a tally mark on those problems that you would like me to go over, and you will turn in your homework with your name, the section and the page of the assignment. Order of the day 2 4.1 AP Calc Antiderivatives and Indefinite Integration.notebook November 28, 2016 Vocabulary First, find a function F whose derivative is . because any other function F work? So represents the family of all antiderivatives of . The constant C is called the constant of integration. The family of functions represented by F is the general antiderivative of f, and is the general solution to the differential equation The operation of finding all solutions to the differential equation is called antidifferentiation (or indefinite integration) and is denoted by an integral sign: is read as the antiderivative of f with respect to x. Vocabulary 3 4.1 AP Calc Antiderivatives and Indefinite Integration.notebook November 28, 2016 Nov 289:38 AM 4 4.1 AP Calc Antiderivatives and Indefinite Integration.notebook November 28, 2016 ∫ Use basic integration rules to find antiderivatives The Power Rule: where 1. -
Web Corrections-Vector Logic and Counterfactuals-Rev 2
This article was published in: "Logic Journal of IGPL" Online version: doi:10.1093/jigpal/jzaa026, 2020 Vector logic allows counterfactual virtualization by The Square Root of NOT Eduardo Mizraji Group of Cognitive Systems Modeling, Biophysics and Systems Biology Section, Facultad de Ciencias, Universidad de la República Montevideo, Uruguay Abstract In this work we investigate the representation of counterfactual conditionals using the vector logic, a matrix-vectors formalism for logical functions and truth values. Inside this formalism, the counterfactuals can be transformed in complex matrices preprocessing an implication matrix with one of the square roots of NOT, a complex matrix. This mathematical approach puts in evidence the virtual character of the counterfactuals. This happens because this representation produces a valuation of a counterfactual that is the superposition of the two opposite truth values weighted, respectively, by two complex conjugated coefficients. This result shows that this procedure gives an uncertain evaluation projected on the complex domain. After this basic representation, the judgment of the plausibility of a given counterfactual allows us to shift the decision towards an acceptance or a refusal. This shift is the result of applying for a second time one of the two square roots of NOT. Keywords : Vector logic; Conditionals; Counterfactuals; Square Roots of NOT. Address: Dr. Eduardo Mizraji Sección Biofísica y Biología de Sistemas, Facultad de Ciencias, UdelaR Iguá 4225, Montevideo 11400, Uruguay e-mails: 1) [email protected], 2) [email protected] Phone-Fax: +598 25258629 1 1. Introduction The comprehension and further formalization of the conditionals have a long and complex history, full of controversies, famously described in an article of Lukasiewicz [20]. -
12.4 Calculus Review
Appendix 445 12.4 Calculus review This section is a very brief summary of Calculus skills required for reading this book. 12.4.1 Inverse function Function g is the inverse function of function f if g(f(x)) = x and f(g(y)) = y for all x and y where f(x) and g(y) exist. 1 Notation Inverse function g = f − 1 (Don’t confuse the inverse f − (x) with 1/f(x). These are different functions!) To find the inverse function, solve the equation f(x) = y. The solution g(y) is the inverse of f. For example, to find the inverse of f(x)=3+1/x, we solve the equation 1 3 + 1/x = y 1/x = y 3 x = . ⇒ − ⇒ y 3 − The inverse function of f is g(y) = 1/(y 3). − 12.4.2 Limits and continuity A function f(x) has a limit L at a point x0 if f(x) approaches L when x approaches x0. To say it more rigorously, for any ε there exists such δ that f(x) is ε-close to L when x is δ-close to x0. That is, if x x < δ then f(x) L < ε. | − 0| | − | A function f(x) has a limit L at + if f(x) approaches L when x goes to + . Rigorously, for any ε there exists such N that f∞(x) is ε-close to L when x gets beyond N∞, i.e., if x > N then f(x) L < ε. | − | Similarly, f(x) has a limit L at if for any ε there exists such N that f(x) is ε-close to L when x gets below ( N), i.e.,−∞ − if x < N then f(x) L < ε. -
1. Antiderivatives for Exponential Functions Recall That for F(X) = Ec⋅X, F ′(X) = C ⋅ Ec⋅X (For Any Constant C)
1. Antiderivatives for exponential functions Recall that for f(x) = ec⋅x, f ′(x) = c ⋅ ec⋅x (for any constant c). That is, ex is its own derivative. So it makes sense that it is its own antiderivative as well! Theorem 1.1 (Antiderivatives of exponential functions). Let f(x) = ec⋅x for some 1 constant c. Then F x ec⋅c D, for any constant D, is an antiderivative of ( ) = c + f(x). 1 c⋅x ′ 1 c⋅x c⋅x Proof. Consider F (x) = c e +D. Then by the chain rule, F (x) = c⋅ c e +0 = e . So F (x) is an antiderivative of f(x). Of course, the theorem does not work for c = 0, but then we would have that f(x) = e0 = 1, which is constant. By the power rule, an antiderivative would be F (x) = x + C for some constant C. 1 2. Antiderivative for f(x) = x We have the power rule for antiderivatives, but it does not work for f(x) = x−1. 1 However, we know that the derivative of ln(x) is x . So it makes sense that the 1 antiderivative of x should be ln(x). Unfortunately, it is not. But it is close. 1 1 Theorem 2.1 (Antiderivative of f(x) = x ). Let f(x) = x . Then the antiderivatives of f(x) are of the form F (x) = ln(SxS) + C. Proof. Notice that ln(x) for x > 0 F (x) = ln(SxS) = . ln(−x) for x < 0 ′ 1 For x > 0, we have [ln(x)] = x . -
Antiderivatives Math 121 Calculus II D Joyce, Spring 2013
Antiderivatives Math 121 Calculus II D Joyce, Spring 2013 Antiderivatives and the constant of integration. We'll start out this semester talking about antiderivatives. If the derivative of a function F isf, that is, F 0 = f, then we say F is an antiderivative of f. Of course, antiderivatives are important in solving problems when you know a derivative but not the function, but we'll soon see that lots of questions involving areas, volumes, and other things also come down to finding antiderivatives. That connection we'll see soon when we study the Fundamental Theorem of Calculus (FTC). For now, we'll just stick to the basic concept of antiderivatives. We can find antiderivatives of polynomials pretty easily. Suppose that we want to find an antiderivative F (x) of the polynomial f(x) = 4x3 + 5x2 − 3x + 8: We can find one by finding an antiderivative of each term and adding the results together. Since the derivative of x4 is 4x3, therefore an antiderivative of 4x3 is x4. It's not much harder to find an antiderivative of 5x2. Since the derivative of x3 is 3x2, an antiderivative of 5x2 is 5 3 3 x . Continue on and soon you see that an antiderivative of f(x) is 4 5 3 3 2 F (x) = x + 3 x − 2 x + 8x: There are, however, other antiderivatives of f(x). Since the derivative of a constant is 0, 4 5 3 3 2 we can add any constant to F (x) to find another antiderivative. Thus, x + 3 x − 2 x +8x+7 4 5 3 3 2 is another antiderivative of f(x). -
1.1 Logic 1.1.1
Section 1.1 Logic 1.1.1 1.1 LOGIC Mathematics is used to predict empirical reality, and is therefore the foundation of engineering. Logic gives precise meaning to mathematical statements. PROPOSITIONS def: A proposition is a statement that is either true (T) or false (F), but not both. Example 1.1.1: 1+1=2.(T) 2+2=5.(F) Example 1.1.2: A fact-based declaration is a proposition, even if no one knows whether it is true. 11213 is prime. 1isprime. There exists an odd perfect number. Coursenotes by Prof. Jonathan L. Gross for use with Rosen: Discrete Math and Its Applic., 5th Ed. Chapter 1 FOUNDATIONS 1.1.2 Example 1.1.3: Logical analysis of rhetoric begins with the modeling of fact-based natural language declarations by propositions. Portland is the capital of Oregon. Columbia University was founded in 1754 by Romulus and Remus. If 2+2 = 5, then you are the pope. (a conditional fact-based declaration). Example 1.1.4: A statement cannot be true or false unless it is declarative. This excludes commands and questions. Go directly to jail. What time is it? Example 1.1.5: Declarations about semantic tokens of non-constant value are NOT proposi- tions. x+2=5. Coursenotes by Prof. Jonathan L. Gross for use with Rosen: Discrete Math and Its Applic., 5th Ed. Section 1.1 Logic 1.1.3 TRUTH TABLES def: The boolean domain is the set {T,F}. Either of its elements is called a boolean value. An n-tuple (p1,...,pn)ofboolean values is called a boolean n-tuple. -
Exclusive Or from Wikipedia, the Free Encyclopedia
New features Log in / create account Article Discussion Read Edit View history Exclusive or From Wikipedia, the free encyclopedia "XOR" redirects here. For other uses, see XOR (disambiguation), XOR gate. Navigation "Either or" redirects here. For Kierkegaard's philosophical work, see Either/Or. Main page The logical operation exclusive disjunction, also called exclusive or (symbolized XOR, EOR, Contents EXOR, ⊻ or ⊕, pronounced either / ks / or /z /), is a type of logical disjunction on two Featured content operands that results in a value of true if exactly one of the operands has a value of true.[1] A Current events simple way to state this is "one or the other but not both." Random article Donate Put differently, exclusive disjunction is a logical operation on two logical values, typically the values of two propositions, that produces a value of true only in cases where the truth value of the operands differ. Interaction Contents About Wikipedia Venn diagram of Community portal 1 Truth table Recent changes 2 Equivalencies, elimination, and introduction but not is Contact Wikipedia 3 Relation to modern algebra Help 4 Exclusive “or” in natural language 5 Alternative symbols Toolbox 6 Properties 6.1 Associativity and commutativity What links here 6.2 Other properties Related changes 7 Computer science Upload file 7.1 Bitwise operation Special pages 8 See also Permanent link 9 Notes Cite this page 10 External links 4, 2010 November Print/export Truth table on [edit] archived The truth table of (also written as or ) is as follows: Venn diagram of Create a book 08-17094 Download as PDF No.