Arithmetic and Logic Unit (ALU)
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Lesson 2: the Multiplication of Polynomials
NYS COMMON CORE MATHEMATICS CURRICULUM Lesson 2 M1 ALGEBRA II Lesson 2: The Multiplication of Polynomials Student Outcomes . Students develop the distributive property for application to polynomial multiplication. Students connect multiplication of polynomials with multiplication of multi-digit integers. Lesson Notes This lesson begins to address standards A-SSE.A.2 and A-APR.C.4 directly and provides opportunities for students to practice MP.7 and MP.8. The work is scaffolded to allow students to discern patterns in repeated calculations, leading to some general polynomial identities that are explored further in the remaining lessons of this module. As in the last lesson, if students struggle with this lesson, they may need to review concepts covered in previous grades, such as: The connection between area properties and the distributive property: Grade 7, Module 6, Lesson 21. Introduction to the table method of multiplying polynomials: Algebra I, Module 1, Lesson 9. Multiplying polynomials (in the context of quadratics): Algebra I, Module 4, Lessons 1 and 2. Since division is the inverse operation of multiplication, it is important to make sure that your students understand how to multiply polynomials before moving on to division of polynomials in Lesson 3 of this module. In Lesson 3, division is explored using the reverse tabular method, so it is important for students to work through the table diagrams in this lesson to prepare them for the upcoming work. There continues to be a sharp distinction in this curriculum between justification and proof, such as justifying the identity (푎 + 푏)2 = 푎2 + 2푎푏 + 푏 using area properties and proving the identity using the distributive property. -
Chapter 2. Multiplication and Division of Whole Numbers in the Last Chapter You Saw That Addition and Subtraction Were Inverse Mathematical Operations
Chapter 2. Multiplication and Division of Whole Numbers In the last chapter you saw that addition and subtraction were inverse mathematical operations. For example, a pay raise of 50 cents an hour is the opposite of a 50 cents an hour pay cut. When you have completed this chapter, you’ll understand that multiplication and division are also inverse math- ematical operations. 2.1 Multiplication with Whole Numbers The Multiplication Table Learning the multiplication table shown below is a basic skill that must be mastered. Do you have to memorize this table? Yes! Can’t you just use a calculator? No! You must know this table by heart to be able to multiply numbers, to do division, and to do algebra. To be blunt, until you memorize this entire table, you won’t be able to progress further than this page. MULTIPLICATION TABLE ϫ 012 345 67 89101112 0 000 000LEARNING 00 000 00 1 012 345 67 89101112 2 024 681012Copy14 16 18 20 22 24 3 036 9121518212427303336 4 0481216 20 24 28 32 36 40 44 48 5051015202530354045505560 6061218243036424854606672Distribute 7071421283542495663707784 8081624324048566472808896 90918273HAWKESReview645546372819099108 10 0 10 20 30 40 50 60 70 80 90 100 110 120 ©11 0 11 22 33 44NOT 55 66 77 88 99 110 121 132 12 0 12 24 36 48 60 72 84 96 108 120 132 144 Do Let’s get a couple of things out of the way. First, any number times 0 is 0. When we multiply two numbers, we call our answer the product of those two numbers. -
Grade 7/8 Math Circles the Scale of Numbers Introduction
Faculty of Mathematics Centre for Education in Waterloo, Ontario N2L 3G1 Mathematics and Computing Grade 7/8 Math Circles November 21/22/23, 2017 The Scale of Numbers Introduction Last week we quickly took a look at scientific notation, which is one way we can write down really big numbers. We can also use scientific notation to write very small numbers. 1 × 103 = 1; 000 1 × 102 = 100 1 × 101 = 10 1 × 100 = 1 1 × 10−1 = 0:1 1 × 10−2 = 0:01 1 × 10−3 = 0:001 As you can see above, every time the value of the exponent decreases, the number gets smaller by a factor of 10. This pattern continues even into negative exponent values! Another way of picturing negative exponents is as a division by a positive exponent. 1 10−6 = = 0:000001 106 In this lesson we will be looking at some famous, interesting, or important small numbers, and begin slowly working our way up to the biggest numbers ever used in mathematics! Obviously we can come up with any arbitrary number that is either extremely small or extremely large, but the purpose of this lesson is to only look at numbers with some kind of mathematical or scientific significance. 1 Extremely Small Numbers 1. Zero • Zero or `0' is the number that represents nothingness. It is the number with the smallest magnitude. • Zero only began being used as a number around the year 500. Before this, ancient mathematicians struggled with the concept of `nothing' being `something'. 2. Planck's Constant This is the smallest number that we will be looking at today other than zero. -
Title Studies on Hardware Algorithms for Arithmetic Operations
Studies on Hardware Algorithms for Arithmetic Operations Title with a Redundant Binary Representation( Dissertation_全文 ) Author(s) Takagi, Naofumi Citation Kyoto University (京都大学) Issue Date 1988-01-23 URL http://dx.doi.org/10.14989/doctor.r6406 Right Type Thesis or Dissertation Textversion author Kyoto University Studies on Hardware Algorithms for Arithmetic Operations with a Redundant Binary Representation Naofumi TAKAGI Department of Information Science Faculty of Engineering Kyoto University August 1987 Studies on Hardware Algorithms for Arithmetic Operations with a Redundant Binary Representation Naofumi Takagi Abstract Arithmetic has played important roles in human civilization, especially in the area of science, engineering and technology. With recent advances of IC (Integrated Circuit) technology, more and more sophisticated arithmetic processors have become standard hardware for high-performance digital computing systems. It is desired to develop high-speed multipliers, dividers and other specialized arithmetic circuits suitable for VLSI (Very Large Scale Integrated circuit) implementation. In order to develop such high-performance arithmetic circuits, it is important to design hardware algorithms for these operations, i.e., algorithms suitable for hardware implementation. The design of hardware algorithms for arithmetic operations has become a very attractive research subject. In this thesis, new hardware algorithms for multiplication, division, square root extraction and computations of several elementary functions are proposed. In these algorithms a redundant binary representation which has radix 2 and a digit set {l,O,l} is used for internal computation. In the redundant binary number system, addition can be performed in a constant time i independent of the word length of the operands. The hardware algorithms proposed in this thesis achieve high-speed computation by using this property. -
Compressor Based 32-32 Bit Vedic Multiplier Using Reversible Logic
IAETSD JOURNAL FOR ADVANCED RESEARCH IN APPLIED SCIENCES. ISSN NO: 2394-8442 COMPRESSOR BASED 32-32 BIT VEDIC MULTIPLIER USING REVERSIBLE LOGIC KAVALI USMAVATHI *, PROF. NAVEEN RATHEE** * PG SCHOLAR, Department of VLSI System Design, Bharat Institute of Engineering and Technology ** Professor, Department of Electronics and Communication Engineering at Bharat Institute of Engineering and Technology, TS, India. ABSTRACT: Vedic arithmetic is the name arithmetic and algebraic operations which given to the antiquated Indian arrangement are accepted by worldwide. The origin of of arithmetic that was rediscovered in the Vedic mathematics is from Vedas and to early twentieth century from antiquated more specific Atharva Veda which deals Indian figures (Vedas). This paper proposes with Engineering branches, Mathematics, the plan of fast Vedic Multiplier utilizing the sculpture, Medicine and all other sciences procedures of Vedic Mathematics that have which are ruling today’s world. Vedic been altered to improve execution. A fast mathematics, which simplifies arithmetic processor depends enormously on the and algebraic operations, can be multiplier as it is one of the key equipment implemented both in decimal and binary obstructs in most computerized flag number systems. It is an ancient technique, preparing frameworks just as when all is which simplifies multiplication, division, said in done processors. Vedic Mathematics complex numbers, squares, cubes, square has an exceptional strategy of estimations roots and cube roots. Recurring decimals based on 16 Sutras. This paper presents and auxiliary fractions can be handled by think about on rapid 32x32 piece Vedic Vedic mathematics. This made possible to multiplier design which is very not quite the solve many Engineering applications, Signal same as the Traditional technique for processing Applications, DFT’s, FFT’s and augmentation like include and move. -
Design and Implementation of Floating Point Multiplier for Better Timing Performance
ISSN: 2278 – 1323 International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume 1, Issue 7, September 2012 Design and Implementation of Floating Point Multiplier for Better Timing Performance B.Sreenivasa Ganesh1,J.E.N.Abhilash2, G. Rajesh Kumar3 SwarnandhraCollege of Engineering& Technology1,2, Vishnu Institute of Technology3 Abstract— IEEE Standard 754 floating point is the p0 = a0b0, p1 = a0b1 + a1b0, p2 = a0b2 + a1b1 + a2b0 + most common representation today for real numbers on carry(p1), etc. This circuit operates only with positive computers. This paper gives a brief overview of IEEE (unsigned) inputs, also producing a positive floating point and its representation. This paper describes (unsigned) output. a single precision floating point multiplier for better timing performance. The main object of this paper is to reduce the power consumption and to increase the speed of execution by implementing certain algorithm for multiplying two floating point numbers. In order to design this VHDL is the hardware description language is used and targeted on a Xilinx Spartan-3 FPGA. The implementation’s tradeoffs are area speed and accuracy. This multiplier also handles overflow and underflow cases. For high accuracy of the results normalization is also applied. By the use of pipelining process this multiplier is very good at speed and accuracy compared with the previous multipliers. This pipelined architecture is described in VHDL and is implemented on Xilinx Spartan 3 FPGA. Timing performance is measured with Xilinx Timing Analyzer. Timing performance is compared with standard multipliers. Fig 1 Binary Multiplication Index Terms— Floating This unsigned multiplier is useful in the point,multiplication,VHDL,Spartan-3 FPGA, Pipelined multiplication of mantissa part of floating point architecture, Timing Analyzer, IEEE Standard 754 numbers. -
The Notion Of" Unimaginable Numbers" in Computational Number Theory
Beyond Knuth’s notation for “Unimaginable Numbers” within computational number theory Antonino Leonardis1 - Gianfranco d’Atri2 - Fabio Caldarola3 1 Department of Mathematics and Computer Science, University of Calabria Arcavacata di Rende, Italy e-mail: [email protected] 2 Department of Mathematics and Computer Science, University of Calabria Arcavacata di Rende, Italy 3 Department of Mathematics and Computer Science, University of Calabria Arcavacata di Rende, Italy e-mail: [email protected] Abstract Literature considers under the name unimaginable numbers any positive in- teger going beyond any physical application, with this being more of a vague description of what we are talking about rather than an actual mathemati- cal definition (it is indeed used in many sources without a proper definition). This simply means that research in this topic must always consider shortened representations, usually involving recursion, to even being able to describe such numbers. One of the most known methodologies to conceive such numbers is using hyper-operations, that is a sequence of binary functions defined recursively starting from the usual chain: addition - multiplication - exponentiation. arXiv:1901.05372v2 [cs.LO] 12 Mar 2019 The most important notations to represent such hyper-operations have been considered by Knuth, Goodstein, Ackermann and Conway as described in this work’s introduction. Within this work we will give an axiomatic setup for this topic, and then try to find on one hand other ways to represent unimaginable numbers, as well as on the other hand applications to computer science, where the algorith- mic nature of representations and the increased computation capabilities of 1 computers give the perfect field to develop further the topic, exploring some possibilities to effectively operate with such big numbers. -
New Realization and Implementation Booth Multiplier
Farheen Sultana et al, International Journal of Computer Science and Mobile Computing, Vol.5 Issue.7, July- 2016, pg. 304-311 Available Online at www.ijcsmc.com International Journal of Computer Science and Mobile Computing A Monthly Journal of Computer Science and Information Technology ISSN 2320–088X IMPACT FACTOR: 5.258 IJCSMC, Vol. 5, Issue. 7, July 2016, pg.304 – 311 NEW REALIZATION AND IMPLEMENTATION BOOTH MULTIPLIER Farheen Sultana A.Venkat Reddy M. Tech, PG Student Associate Professor [email protected] [email protected] Abstract— In this paper, we proposed a new architecture of multiplier-and-accumulator (MAC) for high-speed arithmetic. By combining multiplication with accumulation and devising a hybrid type of carry save adder (CSA), the performance was improved. Since the accumulator that has the largest delay in MAC was merged into CSA, the overall performance was elevated. The proposed CSA tree uses 1’s-complement-based radix-2 modified Booth’s algorithm (MBA) and has the modified array for the sign extension in order to increase the bit density of the operands. The CSA propagates the carries to the least significant bits of the partial products and generates the least significant bits in advance to decrease the number of the input bits of the final adder. Also, the proposed MAC accumulates the intermediate results in the type of sum and carry bits instead of the output of the final adder, which made it possible to optimize the pipeline scheme to improve the performance. The proposed architecture was synthesized with and performance of the entire calculation. Because the multiplier requires the longest delay among the basic operational blocks in digital system, the critical path is determined by the multiplier, in general. -
Multiplication Fact Strategies Assessment Directions and Analysis
Multiplication Fact Strategies Wichita Public Schools Curriculum and Instructional Design Mathematics Revised 2014 KCCRS version Table of Contents Introduction Page Research Connections (Strategies) 3 Making Meaning for Operations 7 Assessment 9 Tools 13 Doubles 23 Fives 31 Zeroes and Ones 35 Strategy Focus Review 41 Tens 45 Nines 48 Squared Numbers 54 Strategy Focus Review 59 Double and Double Again 64 Double and One More Set 69 Half and Then Double 74 Strategy Focus Review 80 Related Equations (fact families) 82 Practice and Review 92 Wichita Public Schools 2014 2 Research Connections Where Do Fact Strategies Fit In? Adapted from Randall Charles Fact strategies are considered a crucial second phase in a three-phase program for teaching students basic math facts. The first phase is concept learning. Here, the goal is for students to understand the meanings of multiplication and division. In this phase, students focus on actions (i.e. “groups of”, “equal parts”, “building arrays”) that relate to multiplication and division concepts. An important instructional bridge that is often neglected between concept learning and memorization is the second phase, fact strategies. There are two goals in this phase. First, students need to recognize there are clusters of multiplication and division facts that relate in certain ways. Second, students need to understand those relationships. These lessons are designed to assist with the second phase of this process. If you have students that are not ready, you will need to address the first phase of concept learning. The third phase is memorization of the basic facts. Here the goal is for students to master products and quotients so they can recall them efficiently and accurately, and retain them over time. -
Matrix Multiplication. Diagonal Matrices. Inverse Matrix. Matrices
MATH 304 Linear Algebra Lecture 4: Matrix multiplication. Diagonal matrices. Inverse matrix. Matrices Definition. An m-by-n matrix is a rectangular array of numbers that has m rows and n columns: a11 a12 ... a1n a21 a22 ... a2n . .. . am1 am2 ... amn Notation: A = (aij )1≤i≤n, 1≤j≤m or simply A = (aij ) if the dimensions are known. Matrix algebra: linear operations Addition: two matrices of the same dimensions can be added by adding their corresponding entries. Scalar multiplication: to multiply a matrix A by a scalar r, one multiplies each entry of A by r. Zero matrix O: all entries are zeros. Negative: −A is defined as (−1)A. Subtraction: A − B is defined as A + (−B). As far as the linear operations are concerned, the m×n matrices can be regarded as mn-dimensional vectors. Properties of linear operations (A + B) + C = A + (B + C) A + B = B + A A + O = O + A = A A + (−A) = (−A) + A = O r(sA) = (rs)A r(A + B) = rA + rB (r + s)A = rA + sA 1A = A 0A = O Dot product Definition. The dot product of n-dimensional vectors x = (x1, x2,..., xn) and y = (y1, y2,..., yn) is a scalar n x · y = x1y1 + x2y2 + ··· + xnyn = xk yk . Xk=1 The dot product is also called the scalar product. Matrix multiplication The product of matrices A and B is defined if the number of columns in A matches the number of rows in B. Definition. Let A = (aik ) be an m×n matrix and B = (bkj ) be an n×p matrix. -
Multiplication and Divisions
Third Grade Math nd 2 Grading Period Power Objectives: Academic Vocabulary: multiplication array Represent and solve problems involving multiplication and divisor commutative division. (P.O. #1) property Understand properties of multiplication and the distributive property relationship between multiplication and divisions. estimation division factor column (P.O. #2) Multiply and divide with 100. (P.O. #3) repeated addition multiple Solve problems involving the four operations, and identify associative property quotient and explain the patterns in arithmetic. (P.O. #4) rounding row product equation Multiplication and Division Enduring Understandings: Essential Questions: Mathematical operations are used in solving problems In what ways can operations affect numbers? in which a new value is produced from one or more How can different strategies be helpful when solving a values. problem? Algebraic thinking involves choosing, combining, and How does knowing and using algorithms help us to be applying effective strategies for answering questions. Numbers enable us to use the four operations to efficient problem solvers? combine and separate quantities. How are multiplication and addition alike? See below for additional enduring understandings. How are subtraction and division related? See below for additional essential questions. Enduring Understandings: Multiplication is repeated addition, related to division, and can be used to solve story problems. For a given set of numbers, there are relationships that -
AUTHOR Multiplication and Division. Mathematics-Methods
DOCUMENT RESUME ED 221 338 SE 035 008, AUTHOR ,LeBlanc, John F.; And Others TITLE Multiplication and Division. Mathematics-Methods 12rogram Unipt. INSTITUTION Indiana ,Univ., Bloomington. Mathematics Education !Development Center. , SPONS AGENCY ,National Science Foundation, Washington, D.C. REPORT NO :ISBN-0-201-14610-x PUB DATE 76 . GRANT. NSF-GY-9293 i 153p.; For related documents, see SE 035 006-018. NOTE . ,. EDRS PRICE 'MF01 Plus Postage. PC Not Available from EDRS. DESCRIPTORS iAlgorithms; College Mathematics; *Division; Elementary Education; *Elementary School Mathematics; 'Elementary School Teachers; Higher Education; 'Instructional1 Materials; Learning Activities; :*Mathematics Instruction; *Multiplication; *Preservice Teacher Education; Problem Solving; :Supplementary Reading Materials; Textbooks; ;Undergraduate Study; Workbooks IDENTIFIERS i*Mathematics Methods Program ABSTRACT This unit is 1 of 12 developed for the university classroom portign_of the Mathematics-Methods Program(MMP), created by the Indiana pniversity Mathematics EducationDevelopment Center (MEDC) as an innovative program for the mathematics training of prospective elenientary school teachers (PSTs). Each unit iswritten in an activity format that involves the PST in doing mathematicswith an eye towardaiplication of that mathematics in the elementary school. This do ument is one of four units that are devoted tothe basic number wo k in the elementary school. In addition to an introduction to the unit, the text has sections on the conceptual development of nultiplication