-0.057 037 4 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.057 037 4(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
-0.057 037 4(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:

|-0.057 037 4| = 0.057 037 4


2. First, convert to binary (in base 2) the integer part: 0.
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;
  • 0 ÷ 2 = 0 + 0;

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.

0(10) =

0(2)


4. Convert to binary (base 2) the fractional part: 0.057 037 4.

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) 0.057 037 4 × 2 = 0 + 0.114 074 8;
  • 2) 0.114 074 8 × 2 = 0 + 0.228 149 6;
  • 3) 0.228 149 6 × 2 = 0 + 0.456 299 2;
  • 4) 0.456 299 2 × 2 = 0 + 0.912 598 4;
  • 5) 0.912 598 4 × 2 = 1 + 0.825 196 8;
  • 6) 0.825 196 8 × 2 = 1 + 0.650 393 6;
  • 7) 0.650 393 6 × 2 = 1 + 0.300 787 2;
  • 8) 0.300 787 2 × 2 = 0 + 0.601 574 4;
  • 9) 0.601 574 4 × 2 = 1 + 0.203 148 8;
  • 10) 0.203 148 8 × 2 = 0 + 0.406 297 6;
  • 11) 0.406 297 6 × 2 = 0 + 0.812 595 2;
  • 12) 0.812 595 2 × 2 = 1 + 0.625 190 4;
  • 13) 0.625 190 4 × 2 = 1 + 0.250 380 8;
  • 14) 0.250 380 8 × 2 = 0 + 0.500 761 6;
  • 15) 0.500 761 6 × 2 = 1 + 0.001 523 2;
  • 16) 0.001 523 2 × 2 = 0 + 0.003 046 4;
  • 17) 0.003 046 4 × 2 = 0 + 0.006 092 8;
  • 18) 0.006 092 8 × 2 = 0 + 0.012 185 6;
  • 19) 0.012 185 6 × 2 = 0 + 0.024 371 2;
  • 20) 0.024 371 2 × 2 = 0 + 0.048 742 4;
  • 21) 0.048 742 4 × 2 = 0 + 0.097 484 8;
  • 22) 0.097 484 8 × 2 = 0 + 0.194 969 6;
  • 23) 0.194 969 6 × 2 = 0 + 0.389 939 2;
  • 24) 0.389 939 2 × 2 = 0 + 0.779 878 4;
  • 25) 0.779 878 4 × 2 = 1 + 0.559 756 8;
  • 26) 0.559 756 8 × 2 = 1 + 0.119 513 6;
  • 27) 0.119 513 6 × 2 = 0 + 0.239 027 2;
  • 28) 0.239 027 2 × 2 = 0 + 0.478 054 4;
  • 29) 0.478 054 4 × 2 = 0 + 0.956 108 8;
  • 30) 0.956 108 8 × 2 = 1 + 0.912 217 6;
  • 31) 0.912 217 6 × 2 = 1 + 0.824 435 2;
  • 32) 0.824 435 2 × 2 = 1 + 0.648 870 4;
  • 33) 0.648 870 4 × 2 = 1 + 0.297 740 8;
  • 34) 0.297 740 8 × 2 = 0 + 0.595 481 6;
  • 35) 0.595 481 6 × 2 = 1 + 0.190 963 2;
  • 36) 0.190 963 2 × 2 = 0 + 0.381 926 4;
  • 37) 0.381 926 4 × 2 = 0 + 0.763 852 8;
  • 38) 0.763 852 8 × 2 = 1 + 0.527 705 6;
  • 39) 0.527 705 6 × 2 = 1 + 0.055 411 2;
  • 40) 0.055 411 2 × 2 = 0 + 0.110 822 4;
  • 41) 0.110 822 4 × 2 = 0 + 0.221 644 8;
  • 42) 0.221 644 8 × 2 = 0 + 0.443 289 6;
  • 43) 0.443 289 6 × 2 = 0 + 0.886 579 2;
  • 44) 0.886 579 2 × 2 = 1 + 0.773 158 4;
  • 45) 0.773 158 4 × 2 = 1 + 0.546 316 8;
  • 46) 0.546 316 8 × 2 = 1 + 0.092 633 6;
  • 47) 0.092 633 6 × 2 = 0 + 0.185 267 2;
  • 48) 0.185 267 2 × 2 = 0 + 0.370 534 4;
  • 49) 0.370 534 4 × 2 = 0 + 0.741 068 8;
  • 50) 0.741 068 8 × 2 = 1 + 0.482 137 6;
  • 51) 0.482 137 6 × 2 = 0 + 0.964 275 2;
  • 52) 0.964 275 2 × 2 = 1 + 0.928 550 4;
  • 53) 0.928 550 4 × 2 = 1 + 0.857 100 8;
  • 54) 0.857 100 8 × 2 = 1 + 0.714 201 6;
  • 55) 0.714 201 6 × 2 = 1 + 0.428 403 2;
  • 56) 0.428 403 2 × 2 = 0 + 0.856 806 4;
  • 57) 0.856 806 4 × 2 = 1 + 0.713 612 8;

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:


0.057 037 4(10) =

0.0000 1110 1001 1010 0000 0000 1100 0111 1010 0110 0001 1100 0101 1110 1(2)

6. Positive number before normalization:

0.057 037 4(10) =

0.0000 1110 1001 1010 0000 0000 1100 0111 1010 0110 0001 1100 0101 1110 1(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 5 positions to the right, so that only one non zero digit remains to the left of it:


0.057 037 4(10) =

0.0000 1110 1001 1010 0000 0000 1100 0111 1010 0110 0001 1100 0101 1110 1(2) =

0.0000 1110 1001 1010 0000 0000 1100 0111 1010 0110 0001 1100 0101 1110 1(2) × 20 =

1.1101 0011 0100 0000 0001 1000 1111 0100 1100 0011 1000 1011 1101(2) × 2-5


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): -5

Mantissa (not normalized):
1.1101 0011 0100 0000 0001 1000 1111 0100 1100 0011 1000 1011 1101


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =

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

-5 + 2(11-1) - 1 =

(-5 + 1 023)(10) =

1 018(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;
  • 1 018 ÷ 2 = 509 + 0;
  • 509 ÷ 2 = 254 + 1;
  • 254 ÷ 2 = 127 + 0;
  • 127 ÷ 2 = 63 + 1;
  • 63 ÷ 2 = 31 + 1;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 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) =

1018(10) =

011 1111 1010(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, only if necessary (not the case here).


Mantissa (normalized) =

1. 1101 0011 0100 0000 0001 1000 1111 0100 1100 0011 1000 1011 1101 =

1101 0011 0100 0000 0001 1000 1111 0100 1100 0011 1000 1011 1101


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) =
011 1111 1010

Mantissa (52 bits) =
1101 0011 0100 0000 0001 1000 1111 0100 1100 0011 1000 1011 1101


Decimal number -0.057 037 4 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 1010 - 1101 0011 0100 0000 0001 1000 1111 0100 1100 0011 1000 1011 1101

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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