note6 - CSCI 120 Introduction to Computation Its only a...

Info iconThis preview shows pages 1–3. Sign up to view the full content.

View Full Document Right Arrow Icon
CSCI 120 Introduction to Computation It’s only a matter of representation (cont.) (draft) Saad Mneimneh Visiting Professor Hunter College of CUNY 1 What about negative numbers? People confronted the problem or representing negative numbers even before the first electronic computer. After all, negative numbers existed long time ago. Before we address this issue, let’s see how many (positive) numbers can we represent with n bits. To answer this question, it is enough to determine the largest possible number, since we know that the smallest is zero. Let’s transpose this back to the decimal system since we are much more familiar with it. What is the largest number that we can represent with n decimal digits? Well, it is 999. ..9 ( n times). Therefore, the largest number is 10 n - 1. For instance, with 3 decimal digits, the largest number we can represent is 10 3 - 1 = 999. The same rule applies for the binary system. The largest number we can represent with n bits is 2 n - 1. For instance, with 4 bits, the largest number that we can represent is 2 4 - 1 = 15. Therefore, we have a total of 16 (positive) numbers (including 0). 0 0000 1 0001 2 0010 3 0011 4 0100 5 0101 6 0110 7 0111 8 1000 9 1001 10 1010 11 1011 12 1100 13 1101 14 1110 15 1111 In general, we have a total of 2 n numbers, and they are all positive ranging from 0 to 2 n - 1. Current machines use n = 32 or even n = 64 bits (so that’s a huge number). One way of introducing negative numbers is by using one of the bits (usu- ally the leftmost bit) as a sign bit. This seems natural because this is how we represent negative numbers on paper. We simply put a sign to the left of the
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
number. Therefore, in an n -bit computer, the leftmost bit (also called most significant bit) would be the sign bit followed by the n - 1 bit number. We end up with the range [0 ... 2 n - 1 - 1] for positive numbers and [ - (2 n - 1 - 1) ... 0] for negative numbers. This technique is called signed magnitude. Note that zero has two representations now, minus zero and positive zero. For n = 4 bits, this is what we get: 0 0000 1 0001 2 0010 3 0011 4 0100 5 0101 6 0110 7 0111 -0 1000 -1 1001 -2 1010 -3 1011 -4 1100 -5 1101 -6 1110 -7 1111 Basically, each number is interpreted as a sign bit followed by the represen- tation of an n - 1 bit number. So 1101 is -(101) and 101 in binary is 5, so 1101 is a representation of -5. Although this seems natural to us, it is not natural to computers at all. Consider for instance when the computer adds two numbers. First it has to look at the signs of both numbers, then decide, based upon the signs, whether to add them or subtract one from the other, and what sign the result will have. Wouldn’t it be nice if the computer’s arithmetic unit never needed to know if a number is positive or negative and simply added any two numbers and still got the correct result? This turns out to be possible indeed. 2 One’s complement
Background image of page 2
Image of page 3
This is the end of the preview. Sign up to access the rest of the document.

Page1 / 8

note6 - CSCI 120 Introduction to Computation Its only a...

This preview shows document pages 1 - 3. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online