Binary Flashcards

1
Q

Define unsigned binary:

A

Binary that only represents positive numbers

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2
Q

0+0:

A

0

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3
Q

0+1:

A

1

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4
Q

1+1:

A

0, carry 1

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5
Q

1+1+1:

A

1, carry 1

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6
Q

Binary multiplication rules:

A

Multiply the first number by each digit of the second, shifting one left each time. Each result will be 0 or the original number shifted by an appropriate amount. Then add all the results.

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7
Q

Define two’s complement:

A

A method of working with signed binary values

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8
Q

How does two’s complement work:

A

The most significant bit is negative, the rest are positive.

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9
Q

How to convert positive numbers to negative ones:

A

Flip all the digits, then add 1

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10
Q

Binary subtraction rules:

A

Convert the number being subtracted into a negative number, then add them

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11
Q

Define fixed point:

A

Where the decimal point is in a fixed position in a number

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12
Q

Where is the decimal point in a fixed point number:

A

It can be anywhere, it just can’t move so the size of the number is limited by where it is

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13
Q

Define floating point:

A

Where the decimal point can move within a number

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14
Q

What is the benefit of floating point numbers:

A

It means less bits are needed, and that a wider range of numbers is available

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15
Q

Define mantissa:

A

The actual number being represented in floating point, not to the actual power

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16
Q

Define exponent:

A

What power the mantissa is raised to to give the actual number

17
Q

If the exponent is positive, what happens to the point:

A

The point shifts left - the mantissa increases in size

18
Q

If the exponent is negative, what happens to the point:

A

The point shifts right - the mantissa becomes smaller

19
Q

Where is the decimal point in a normalised floating point number:

A

After the most significant bit of the mantissa

20
Q

What are floating point numbers equivalent to in decimal:

A

Standard form

21
Q

What is the benefit of fixed point numbers:

A

Less processing is required, so it’s faster and the absolute error is always the same

22
Q

Define signed binary:

A

Binary that can represent positive and negative numbers

23
Q

Define overflow error:

A

When a number is too big to be represented with the allocated number of bits

24
Q

Define underflow error:

A

When a number is too small to be represented with the allocated number of bits

25
Q

Define precision:

A

How accurate a number is

26
Q

Define normalisation:

A

A process for adjusting numbers onto a common scale

27
Q

How much is a positive number adjusted to be normalised:

A

It should have a 0 as the most significant bit, and a 1 after it

28
Q

How much is a negative number adjusted to be normalised:

A

It should have a 1 as the most significant bit, and a 0 after it

29
Q

Define rounding error:

A

When the actual number can’t be represented in the available number of bits or at all (like 1/3), so it is up to the programmer to decide how accurate it needs to be

30
Q

Define absolute error:

A

The error interval between the actual number and the number being used

31
Q

How to calculate the absolute error:

A

The smaller number subtracted from the larger number (it’s always positive)

32
Q

Define relative error:

A

The comparative error between the number and how accurate it needs to be

33
Q

How to calculate the relative error:

A

The absolute error divided by the actual number

34
Q

Where is the point in a normalised number:

A

After the MSB