0.000 700 457 304 2 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 0.000 700 457 304 2(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
0.000 700 457 304 2(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. 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;

2. 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)


3. Convert to binary (base 2) the fractional part: 0.000 700 457 304 2.

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) 0.000 700 457 304 2 × 2 = 0 + 0.001 400 914 608 4;
  • 2) 0.001 400 914 608 4 × 2 = 0 + 0.002 801 829 216 8;
  • 3) 0.002 801 829 216 8 × 2 = 0 + 0.005 603 658 433 6;
  • 4) 0.005 603 658 433 6 × 2 = 0 + 0.011 207 316 867 2;
  • 5) 0.011 207 316 867 2 × 2 = 0 + 0.022 414 633 734 4;
  • 6) 0.022 414 633 734 4 × 2 = 0 + 0.044 829 267 468 8;
  • 7) 0.044 829 267 468 8 × 2 = 0 + 0.089 658 534 937 6;
  • 8) 0.089 658 534 937 6 × 2 = 0 + 0.179 317 069 875 2;
  • 9) 0.179 317 069 875 2 × 2 = 0 + 0.358 634 139 750 4;
  • 10) 0.358 634 139 750 4 × 2 = 0 + 0.717 268 279 500 8;
  • 11) 0.717 268 279 500 8 × 2 = 1 + 0.434 536 559 001 6;
  • 12) 0.434 536 559 001 6 × 2 = 0 + 0.869 073 118 003 2;
  • 13) 0.869 073 118 003 2 × 2 = 1 + 0.738 146 236 006 4;
  • 14) 0.738 146 236 006 4 × 2 = 1 + 0.476 292 472 012 8;
  • 15) 0.476 292 472 012 8 × 2 = 0 + 0.952 584 944 025 6;
  • 16) 0.952 584 944 025 6 × 2 = 1 + 0.905 169 888 051 2;
  • 17) 0.905 169 888 051 2 × 2 = 1 + 0.810 339 776 102 4;
  • 18) 0.810 339 776 102 4 × 2 = 1 + 0.620 679 552 204 8;
  • 19) 0.620 679 552 204 8 × 2 = 1 + 0.241 359 104 409 6;
  • 20) 0.241 359 104 409 6 × 2 = 0 + 0.482 718 208 819 2;
  • 21) 0.482 718 208 819 2 × 2 = 0 + 0.965 436 417 638 4;
  • 22) 0.965 436 417 638 4 × 2 = 1 + 0.930 872 835 276 8;
  • 23) 0.930 872 835 276 8 × 2 = 1 + 0.861 745 670 553 6;
  • 24) 0.861 745 670 553 6 × 2 = 1 + 0.723 491 341 107 2;
  • 25) 0.723 491 341 107 2 × 2 = 1 + 0.446 982 682 214 4;
  • 26) 0.446 982 682 214 4 × 2 = 0 + 0.893 965 364 428 8;
  • 27) 0.893 965 364 428 8 × 2 = 1 + 0.787 930 728 857 6;
  • 28) 0.787 930 728 857 6 × 2 = 1 + 0.575 861 457 715 2;
  • 29) 0.575 861 457 715 2 × 2 = 1 + 0.151 722 915 430 4;
  • 30) 0.151 722 915 430 4 × 2 = 0 + 0.303 445 830 860 8;
  • 31) 0.303 445 830 860 8 × 2 = 0 + 0.606 891 661 721 6;
  • 32) 0.606 891 661 721 6 × 2 = 1 + 0.213 783 323 443 2;
  • 33) 0.213 783 323 443 2 × 2 = 0 + 0.427 566 646 886 4;
  • 34) 0.427 566 646 886 4 × 2 = 0 + 0.855 133 293 772 8;
  • 35) 0.855 133 293 772 8 × 2 = 1 + 0.710 266 587 545 6;
  • 36) 0.710 266 587 545 6 × 2 = 1 + 0.420 533 175 091 2;
  • 37) 0.420 533 175 091 2 × 2 = 0 + 0.841 066 350 182 4;
  • 38) 0.841 066 350 182 4 × 2 = 1 + 0.682 132 700 364 8;
  • 39) 0.682 132 700 364 8 × 2 = 1 + 0.364 265 400 729 6;
  • 40) 0.364 265 400 729 6 × 2 = 0 + 0.728 530 801 459 2;
  • 41) 0.728 530 801 459 2 × 2 = 1 + 0.457 061 602 918 4;
  • 42) 0.457 061 602 918 4 × 2 = 0 + 0.914 123 205 836 8;
  • 43) 0.914 123 205 836 8 × 2 = 1 + 0.828 246 411 673 6;
  • 44) 0.828 246 411 673 6 × 2 = 1 + 0.656 492 823 347 2;
  • 45) 0.656 492 823 347 2 × 2 = 1 + 0.312 985 646 694 4;
  • 46) 0.312 985 646 694 4 × 2 = 0 + 0.625 971 293 388 8;
  • 47) 0.625 971 293 388 8 × 2 = 1 + 0.251 942 586 777 6;
  • 48) 0.251 942 586 777 6 × 2 = 0 + 0.503 885 173 555 2;
  • 49) 0.503 885 173 555 2 × 2 = 1 + 0.007 770 347 110 4;
  • 50) 0.007 770 347 110 4 × 2 = 0 + 0.015 540 694 220 8;
  • 51) 0.015 540 694 220 8 × 2 = 0 + 0.031 081 388 441 6;
  • 52) 0.031 081 388 441 6 × 2 = 0 + 0.062 162 776 883 2;
  • 53) 0.062 162 776 883 2 × 2 = 0 + 0.124 325 553 766 4;
  • 54) 0.124 325 553 766 4 × 2 = 0 + 0.248 651 107 532 8;
  • 55) 0.248 651 107 532 8 × 2 = 0 + 0.497 302 215 065 6;
  • 56) 0.497 302 215 065 6 × 2 = 0 + 0.994 604 430 131 2;
  • 57) 0.994 604 430 131 2 × 2 = 1 + 0.989 208 860 262 4;
  • 58) 0.989 208 860 262 4 × 2 = 1 + 0.978 417 720 524 8;
  • 59) 0.978 417 720 524 8 × 2 = 1 + 0.956 835 441 049 6;
  • 60) 0.956 835 441 049 6 × 2 = 1 + 0.913 670 882 099 2;
  • 61) 0.913 670 882 099 2 × 2 = 1 + 0.827 341 764 198 4;
  • 62) 0.827 341 764 198 4 × 2 = 1 + 0.654 683 528 396 8;
  • 63) 0.654 683 528 396 8 × 2 = 1 + 0.309 367 056 793 6;

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).


4. 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:


0.000 700 457 304 2(10) =


0.0000 0000 0010 1101 1110 0111 1011 1001 0011 0110 1011 1010 1000 0000 1111 111(2)

5. Positive number before normalization:

0.000 700 457 304 2(10) =


0.0000 0000 0010 1101 1110 0111 1011 1001 0011 0110 1011 1010 1000 0000 1111 111(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 11 positions to the right, so that only one non zero digit remains to the left of it:


0.000 700 457 304 2(10) =


0.0000 0000 0010 1101 1110 0111 1011 1001 0011 0110 1011 1010 1000 0000 1111 111(2) =


0.0000 0000 0010 1101 1110 0111 1011 1001 0011 0110 1011 1010 1000 0000 1111 111(2) × 20 =


1.0110 1111 0011 1101 1100 1001 1011 0101 1101 0100 0000 0111 1111(2) × 2-11


7. 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 0 (a positive number)


Exponent (unadjusted): -11


Mantissa (not normalized):
1.0110 1111 0011 1101 1100 1001 1011 0101 1101 0100 0000 0111 1111


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


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


(-11 + 1 023)(10) =


1 012(10)


9. 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;
  • 1 012 ÷ 2 = 506 + 0;
  • 506 ÷ 2 = 253 + 0;
  • 253 ÷ 2 = 126 + 1;
  • 126 ÷ 2 = 63 + 0;
  • 63 ÷ 2 = 31 + 1;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 1 ÷ 2 = 0 + 1;

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

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


Exponent (adjusted) =


1012(10) =


011 1111 0100(2)


11. 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. 0110 1111 0011 1101 1100 1001 1011 0101 1101 0100 0000 0111 1111 =


0110 1111 0011 1101 1100 1001 1011 0101 1101 0100 0000 0111 1111


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

Sign (1 bit) =
0 (a positive number)


Exponent (11 bits) =
011 1111 0100


Mantissa (52 bits) =
0110 1111 0011 1101 1100 1001 1011 0101 1101 0100 0000 0111 1111


Decimal number 0.000 700 457 304 2 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 011 1111 0100 - 0110 1111 0011 1101 1100 1001 1011 0101 1101 0100 0000 0111 1111

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