-480.529 600 000 000 14 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -480.529 600 000 000 14(10) to 64 bit double precision IEEE 754 binary floating point representation standard (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

What are the steps to convert decimal number
-480.529 600 000 000 14(10) to 64 bit double precision IEEE 754 binary floating point representation (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

1. Start with the positive version of the number:

|-480.529 600 000 000 14| = 480.529 600 000 000 14


2. First, convert to binary (in base 2) the integer part: 480.
Divide the number repeatedly by 2.

Keep track of each remainder.

We stop when we get a quotient that is equal to zero.


  • division = quotient + remainder;
  • 480 ÷ 2 = 240 + 0;
  • 240 ÷ 2 = 120 + 0;
  • 120 ÷ 2 = 60 + 0;
  • 60 ÷ 2 = 30 + 0;
  • 30 ÷ 2 = 15 + 0;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 1 ÷ 2 = 0 + 1;

3. Construct the base 2 representation of the integer part of the number.

Take all the remainders starting from the bottom of the list constructed above.

480(10) =


1 1110 0000(2)


4. Convert to binary (base 2) the fractional part: 0.529 600 000 000 14.

Multiply it repeatedly by 2.


Keep track of each integer part of the results.


Stop when we get a fractional part that is equal to zero.


  • #) multiplying = integer + fractional part;
  • 1) 0.529 600 000 000 14 × 2 = 1 + 0.059 200 000 000 28;
  • 2) 0.059 200 000 000 28 × 2 = 0 + 0.118 400 000 000 56;
  • 3) 0.118 400 000 000 56 × 2 = 0 + 0.236 800 000 001 12;
  • 4) 0.236 800 000 001 12 × 2 = 0 + 0.473 600 000 002 24;
  • 5) 0.473 600 000 002 24 × 2 = 0 + 0.947 200 000 004 48;
  • 6) 0.947 200 000 004 48 × 2 = 1 + 0.894 400 000 008 96;
  • 7) 0.894 400 000 008 96 × 2 = 1 + 0.788 800 000 017 92;
  • 8) 0.788 800 000 017 92 × 2 = 1 + 0.577 600 000 035 84;
  • 9) 0.577 600 000 035 84 × 2 = 1 + 0.155 200 000 071 68;
  • 10) 0.155 200 000 071 68 × 2 = 0 + 0.310 400 000 143 36;
  • 11) 0.310 400 000 143 36 × 2 = 0 + 0.620 800 000 286 72;
  • 12) 0.620 800 000 286 72 × 2 = 1 + 0.241 600 000 573 44;
  • 13) 0.241 600 000 573 44 × 2 = 0 + 0.483 200 001 146 88;
  • 14) 0.483 200 001 146 88 × 2 = 0 + 0.966 400 002 293 76;
  • 15) 0.966 400 002 293 76 × 2 = 1 + 0.932 800 004 587 52;
  • 16) 0.932 800 004 587 52 × 2 = 1 + 0.865 600 009 175 04;
  • 17) 0.865 600 009 175 04 × 2 = 1 + 0.731 200 018 350 08;
  • 18) 0.731 200 018 350 08 × 2 = 1 + 0.462 400 036 700 16;
  • 19) 0.462 400 036 700 16 × 2 = 0 + 0.924 800 073 400 32;
  • 20) 0.924 800 073 400 32 × 2 = 1 + 0.849 600 146 800 64;
  • 21) 0.849 600 146 800 64 × 2 = 1 + 0.699 200 293 601 28;
  • 22) 0.699 200 293 601 28 × 2 = 1 + 0.398 400 587 202 56;
  • 23) 0.398 400 587 202 56 × 2 = 0 + 0.796 801 174 405 12;
  • 24) 0.796 801 174 405 12 × 2 = 1 + 0.593 602 348 810 24;
  • 25) 0.593 602 348 810 24 × 2 = 1 + 0.187 204 697 620 48;
  • 26) 0.187 204 697 620 48 × 2 = 0 + 0.374 409 395 240 96;
  • 27) 0.374 409 395 240 96 × 2 = 0 + 0.748 818 790 481 92;
  • 28) 0.748 818 790 481 92 × 2 = 1 + 0.497 637 580 963 84;
  • 29) 0.497 637 580 963 84 × 2 = 0 + 0.995 275 161 927 68;
  • 30) 0.995 275 161 927 68 × 2 = 1 + 0.990 550 323 855 36;
  • 31) 0.990 550 323 855 36 × 2 = 1 + 0.981 100 647 710 72;
  • 32) 0.981 100 647 710 72 × 2 = 1 + 0.962 201 295 421 44;
  • 33) 0.962 201 295 421 44 × 2 = 1 + 0.924 402 590 842 88;
  • 34) 0.924 402 590 842 88 × 2 = 1 + 0.848 805 181 685 76;
  • 35) 0.848 805 181 685 76 × 2 = 1 + 0.697 610 363 371 52;
  • 36) 0.697 610 363 371 52 × 2 = 1 + 0.395 220 726 743 04;
  • 37) 0.395 220 726 743 04 × 2 = 0 + 0.790 441 453 486 08;
  • 38) 0.790 441 453 486 08 × 2 = 1 + 0.580 882 906 972 16;
  • 39) 0.580 882 906 972 16 × 2 = 1 + 0.161 765 813 944 32;
  • 40) 0.161 765 813 944 32 × 2 = 0 + 0.323 531 627 888 64;
  • 41) 0.323 531 627 888 64 × 2 = 0 + 0.647 063 255 777 28;
  • 42) 0.647 063 255 777 28 × 2 = 1 + 0.294 126 511 554 56;
  • 43) 0.294 126 511 554 56 × 2 = 0 + 0.588 253 023 109 12;
  • 44) 0.588 253 023 109 12 × 2 = 1 + 0.176 506 046 218 24;
  • 45) 0.176 506 046 218 24 × 2 = 0 + 0.353 012 092 436 48;
  • 46) 0.353 012 092 436 48 × 2 = 0 + 0.706 024 184 872 96;
  • 47) 0.706 024 184 872 96 × 2 = 1 + 0.412 048 369 745 92;
  • 48) 0.412 048 369 745 92 × 2 = 0 + 0.824 096 739 491 84;
  • 49) 0.824 096 739 491 84 × 2 = 1 + 0.648 193 478 983 68;
  • 50) 0.648 193 478 983 68 × 2 = 1 + 0.296 386 957 967 36;
  • 51) 0.296 386 957 967 36 × 2 = 0 + 0.592 773 915 934 72;
  • 52) 0.592 773 915 934 72 × 2 = 1 + 0.185 547 831 869 44;
  • 53) 0.185 547 831 869 44 × 2 = 0 + 0.371 095 663 738 88;

We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit) and at least one integer that was different from zero => FULL STOP (Losing precision - the converted number we get in the end will be just a very good approximation of the initial one).


5. Construct the base 2 representation of the fractional part of the number.

Take all the integer parts of the multiplying operations, starting from the top of the constructed list above:


0.529 600 000 000 14(10) =


0.1000 0111 1001 0011 1101 1101 1001 0111 1111 0110 0101 0010 1101 0(2)

6. Positive number before normalization:

480.529 600 000 000 14(10) =


1 1110 0000.1000 0111 1001 0011 1101 1101 1001 0111 1111 0110 0101 0010 1101 0(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 8 positions to the left, so that only one non zero digit remains to the left of it:


480.529 600 000 000 14(10) =


1 1110 0000.1000 0111 1001 0011 1101 1101 1001 0111 1111 0110 0101 0010 1101 0(2) =


1 1110 0000.1000 0111 1001 0011 1101 1101 1001 0111 1111 0110 0101 0010 1101 0(2) × 20 =


1.1110 0000 1000 0111 1001 0011 1101 1101 1001 0111 1111 0110 0101 0010 1101 0(2) × 28


8. Up to this moment, there are the following elements that would feed into the 64 bit double precision IEEE 754 binary floating point representation:

Sign 1 (a negative number)


Exponent (unadjusted): 8


Mantissa (not normalized):
1.1110 0000 1000 0111 1001 0011 1101 1101 1001 0111 1111 0110 0101 0010 1101 0


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


Exponent (unadjusted) + 2(11-1) - 1 =


8 + 2(11-1) - 1 =


(8 + 1 023)(10) =


1 031(10)


10. Convert the adjusted exponent from the decimal (base 10) to 11 bit binary.

Use the same technique of repeatedly dividing by 2:


  • division = quotient + remainder;
  • 1 031 ÷ 2 = 515 + 1;
  • 515 ÷ 2 = 257 + 1;
  • 257 ÷ 2 = 128 + 1;
  • 128 ÷ 2 = 64 + 0;
  • 64 ÷ 2 = 32 + 0;
  • 32 ÷ 2 = 16 + 0;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

11. Construct the base 2 representation of the adjusted exponent.

Take all the remainders starting from the bottom of the list constructed above.


Exponent (adjusted) =


1031(10) =


100 0000 0111(2)


12. Normalize the mantissa.

a) Remove the leading (the leftmost) bit, since it's allways 1, and the decimal point, if the case.


b) Adjust its length to 52 bits, by removing the excess bits, from the right (if any of the excess bits is set on 1, we are losing precision...).


Mantissa (normalized) =


1. 1110 0000 1000 0111 1001 0011 1101 1101 1001 0111 1111 0110 0101 0 0101 1010 =


1110 0000 1000 0111 1001 0011 1101 1101 1001 0111 1111 0110 0101


13. The three elements that make up the number's 64 bit double precision IEEE 754 binary floating point representation:

Sign (1 bit) =
1 (a negative number)


Exponent (11 bits) =
100 0000 0111


Mantissa (52 bits) =
1110 0000 1000 0111 1001 0011 1101 1101 1001 0111 1111 0110 0101


Decimal number -480.529 600 000 000 14 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 100 0000 0111 - 1110 0000 1000 0111 1001 0011 1101 1101 1001 0111 1111 0110 0101


How to convert numbers from the decimal system (base ten) to 64 bit double precision IEEE 754 binary floating point standard

Follow the steps below to convert a base 10 decimal number to 64 bit double precision IEEE 754 binary floating point:

  • 1. If the number to be converted is negative, start with its the positive version.
  • 2. First convert the integer part. Divide repeatedly by 2 the positive representation of the integer number that is to be converted to binary, until we get a quotient that is equal to zero, keeping track of each remainder.
  • 3. Construct the base 2 representation of the positive integer part of the number, by taking all the remainders from the previous operations, starting from the bottom of the list constructed above. Thus, the last remainder of the divisions becomes the first symbol (the leftmost) of the base two number, while the first remainder becomes the last symbol (the rightmost).
  • 4. Then convert the fractional part. Multiply the number repeatedly by 2, until we get a fractional part that is equal to zero, keeping track of each integer part of the results.
  • 5. Construct the base 2 representation of the fractional part of the number, by taking all the integer parts of the multiplying operations, starting from the top of the list constructed above (they should appear in the binary representation, from left to right, in the order they have been calculated).
  • 6. Normalize the binary representation of the number, shifting the decimal mark (the decimal point) "n" positions either to the left, or to the right, so that only one non zero digit remains to the left of the decimal mark.
  • 7. Adjust the exponent in 11 bit excess/bias notation and then convert it from decimal (base 10) to 11 bit binary, by using the same technique of repeatedly dividing by 2, as shown above:
    Exponent (adjusted) = Exponent (unadjusted) + 2(11-1) - 1
  • 8. Normalize mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal mark, if the case) and adjust its length to 52 bits, either by removing the excess bits from the right (losing precision...) or by adding extra bits set on '0' to the right.
  • 9. Sign (it takes 1 bit) is either 1 for a negative or 0 for a positive number.

Example: convert the negative number -31.640 215 from the decimal system (base ten) to 64 bit double precision IEEE 754 binary floating point:

  • 1. Start with the positive version of the number:

    |-31.640 215| = 31.640 215

  • 2. First convert the integer part, 31. Divide it repeatedly by 2, keeping track of each remainder, until we get a quotient that is equal to zero:
    • division = quotient + remainder;
    • 31 ÷ 2 = 15 + 1;
    • 15 ÷ 2 = 7 + 1;
    • 7 ÷ 2 = 3 + 1;
    • 3 ÷ 2 = 1 + 1;
    • 1 ÷ 2 = 0 + 1;
    • We have encountered a quotient that is ZERO => FULL STOP
  • 3. Construct the base 2 representation of the integer part of the number by taking all the remainders of the previous dividing operations, starting from the bottom of the list constructed above:

    31(10) = 1 1111(2)

  • 4. Then, convert the fractional part, 0.640 215. Multiply repeatedly by 2, keeping track of each integer part of the results, until we get a fractional part that is equal to zero:
    • #) multiplying = integer + fractional part;
    • 1) 0.640 215 × 2 = 1 + 0.280 43;
    • 2) 0.280 43 × 2 = 0 + 0.560 86;
    • 3) 0.560 86 × 2 = 1 + 0.121 72;
    • 4) 0.121 72 × 2 = 0 + 0.243 44;
    • 5) 0.243 44 × 2 = 0 + 0.486 88;
    • 6) 0.486 88 × 2 = 0 + 0.973 76;
    • 7) 0.973 76 × 2 = 1 + 0.947 52;
    • 8) 0.947 52 × 2 = 1 + 0.895 04;
    • 9) 0.895 04 × 2 = 1 + 0.790 08;
    • 10) 0.790 08 × 2 = 1 + 0.580 16;
    • 11) 0.580 16 × 2 = 1 + 0.160 32;
    • 12) 0.160 32 × 2 = 0 + 0.320 64;
    • 13) 0.320 64 × 2 = 0 + 0.641 28;
    • 14) 0.641 28 × 2 = 1 + 0.282 56;
    • 15) 0.282 56 × 2 = 0 + 0.565 12;
    • 16) 0.565 12 × 2 = 1 + 0.130 24;
    • 17) 0.130 24 × 2 = 0 + 0.260 48;
    • 18) 0.260 48 × 2 = 0 + 0.520 96;
    • 19) 0.520 96 × 2 = 1 + 0.041 92;
    • 20) 0.041 92 × 2 = 0 + 0.083 84;
    • 21) 0.083 84 × 2 = 0 + 0.167 68;
    • 22) 0.167 68 × 2 = 0 + 0.335 36;
    • 23) 0.335 36 × 2 = 0 + 0.670 72;
    • 24) 0.670 72 × 2 = 1 + 0.341 44;
    • 25) 0.341 44 × 2 = 0 + 0.682 88;
    • 26) 0.682 88 × 2 = 1 + 0.365 76;
    • 27) 0.365 76 × 2 = 0 + 0.731 52;
    • 28) 0.731 52 × 2 = 1 + 0.463 04;
    • 29) 0.463 04 × 2 = 0 + 0.926 08;
    • 30) 0.926 08 × 2 = 1 + 0.852 16;
    • 31) 0.852 16 × 2 = 1 + 0.704 32;
    • 32) 0.704 32 × 2 = 1 + 0.408 64;
    • 33) 0.408 64 × 2 = 0 + 0.817 28;
    • 34) 0.817 28 × 2 = 1 + 0.634 56;
    • 35) 0.634 56 × 2 = 1 + 0.269 12;
    • 36) 0.269 12 × 2 = 0 + 0.538 24;
    • 37) 0.538 24 × 2 = 1 + 0.076 48;
    • 38) 0.076 48 × 2 = 0 + 0.152 96;
    • 39) 0.152 96 × 2 = 0 + 0.305 92;
    • 40) 0.305 92 × 2 = 0 + 0.611 84;
    • 41) 0.611 84 × 2 = 1 + 0.223 68;
    • 42) 0.223 68 × 2 = 0 + 0.447 36;
    • 43) 0.447 36 × 2 = 0 + 0.894 72;
    • 44) 0.894 72 × 2 = 1 + 0.789 44;
    • 45) 0.789 44 × 2 = 1 + 0.578 88;
    • 46) 0.578 88 × 2 = 1 + 0.157 76;
    • 47) 0.157 76 × 2 = 0 + 0.315 52;
    • 48) 0.315 52 × 2 = 0 + 0.631 04;
    • 49) 0.631 04 × 2 = 1 + 0.262 08;
    • 50) 0.262 08 × 2 = 0 + 0.524 16;
    • 51) 0.524 16 × 2 = 1 + 0.048 32;
    • 52) 0.048 32 × 2 = 0 + 0.096 64;
    • 53) 0.096 64 × 2 = 0 + 0.193 28;
    • We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit = 52) and at least one integer part that was different from zero => FULL STOP (losing precision...).
  • 5. Construct the base 2 representation of the fractional part of the number, by taking all the integer parts of the previous multiplying operations, starting from the top of the constructed list above:

    0.640 215(10) = 0.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2)

  • 6. Summarizing - the positive number before normalization:

    31.640 215(10) = 1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2)

  • 7. Normalize the binary representation of the number, shifting the decimal mark 4 positions to the left so that only one non-zero digit stays to the left of the decimal mark:

    31.640 215(10) =
    1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) =
    1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) × 20 =
    1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) × 24

  • 8. Up to this moment, there are the following elements that would feed into the 64 bit double precision IEEE 754 binary floating point representation:

    Sign: 1 (a negative number)

    Exponent (unadjusted): 4

    Mantissa (not-normalized): 1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0

  • 9. Adjust the exponent in 11 bit excess/bias notation and then convert it from decimal (base 10) to 11 bit binary (base 2), by using the same technique of repeatedly dividing it by 2, as shown above:

    Exponent (adjusted) = Exponent (unadjusted) + 2(11-1) - 1 = (4 + 1023)(10) = 1027(10) =
    100 0000 0011(2)

  • 10. Normalize mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal sign) and adjust its length to 52 bits, by removing the excess bits, from the right (losing precision...):

    Mantissa (not-normalized): 1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0

    Mantissa (normalized): 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100

  • Conclusion:

    Sign (1 bit) = 1 (a negative number)

    Exponent (8 bits) = 100 0000 0011

    Mantissa (52 bits) = 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100

  • Number -31.640 215, converted from decimal system (base 10) to 64 bit double precision IEEE 754 binary floating point =
    1 - 100 0000 0011 - 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100