1.745 459 324 169 999 826 2 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 1.745 459 324 169 999 826 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
1.745 459 324 169 999 826 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: 1.
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;
  • 1 ÷ 2 = 0 + 1;

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.

1(10) =


1(2)


3. Convert to binary (base 2) the fractional part: 0.745 459 324 169 999 826 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) 0.745 459 324 169 999 826 2 × 2 = 1 + 0.490 918 648 339 999 652 4;
  • 2) 0.490 918 648 339 999 652 4 × 2 = 0 + 0.981 837 296 679 999 304 8;
  • 3) 0.981 837 296 679 999 304 8 × 2 = 1 + 0.963 674 593 359 998 609 6;
  • 4) 0.963 674 593 359 998 609 6 × 2 = 1 + 0.927 349 186 719 997 219 2;
  • 5) 0.927 349 186 719 997 219 2 × 2 = 1 + 0.854 698 373 439 994 438 4;
  • 6) 0.854 698 373 439 994 438 4 × 2 = 1 + 0.709 396 746 879 988 876 8;
  • 7) 0.709 396 746 879 988 876 8 × 2 = 1 + 0.418 793 493 759 977 753 6;
  • 8) 0.418 793 493 759 977 753 6 × 2 = 0 + 0.837 586 987 519 955 507 2;
  • 9) 0.837 586 987 519 955 507 2 × 2 = 1 + 0.675 173 975 039 911 014 4;
  • 10) 0.675 173 975 039 911 014 4 × 2 = 1 + 0.350 347 950 079 822 028 8;
  • 11) 0.350 347 950 079 822 028 8 × 2 = 0 + 0.700 695 900 159 644 057 6;
  • 12) 0.700 695 900 159 644 057 6 × 2 = 1 + 0.401 391 800 319 288 115 2;
  • 13) 0.401 391 800 319 288 115 2 × 2 = 0 + 0.802 783 600 638 576 230 4;
  • 14) 0.802 783 600 638 576 230 4 × 2 = 1 + 0.605 567 201 277 152 460 8;
  • 15) 0.605 567 201 277 152 460 8 × 2 = 1 + 0.211 134 402 554 304 921 6;
  • 16) 0.211 134 402 554 304 921 6 × 2 = 0 + 0.422 268 805 108 609 843 2;
  • 17) 0.422 268 805 108 609 843 2 × 2 = 0 + 0.844 537 610 217 219 686 4;
  • 18) 0.844 537 610 217 219 686 4 × 2 = 1 + 0.689 075 220 434 439 372 8;
  • 19) 0.689 075 220 434 439 372 8 × 2 = 1 + 0.378 150 440 868 878 745 6;
  • 20) 0.378 150 440 868 878 745 6 × 2 = 0 + 0.756 300 881 737 757 491 2;
  • 21) 0.756 300 881 737 757 491 2 × 2 = 1 + 0.512 601 763 475 514 982 4;
  • 22) 0.512 601 763 475 514 982 4 × 2 = 1 + 0.025 203 526 951 029 964 8;
  • 23) 0.025 203 526 951 029 964 8 × 2 = 0 + 0.050 407 053 902 059 929 6;
  • 24) 0.050 407 053 902 059 929 6 × 2 = 0 + 0.100 814 107 804 119 859 2;
  • 25) 0.100 814 107 804 119 859 2 × 2 = 0 + 0.201 628 215 608 239 718 4;
  • 26) 0.201 628 215 608 239 718 4 × 2 = 0 + 0.403 256 431 216 479 436 8;
  • 27) 0.403 256 431 216 479 436 8 × 2 = 0 + 0.806 512 862 432 958 873 6;
  • 28) 0.806 512 862 432 958 873 6 × 2 = 1 + 0.613 025 724 865 917 747 2;
  • 29) 0.613 025 724 865 917 747 2 × 2 = 1 + 0.226 051 449 731 835 494 4;
  • 30) 0.226 051 449 731 835 494 4 × 2 = 0 + 0.452 102 899 463 670 988 8;
  • 31) 0.452 102 899 463 670 988 8 × 2 = 0 + 0.904 205 798 927 341 977 6;
  • 32) 0.904 205 798 927 341 977 6 × 2 = 1 + 0.808 411 597 854 683 955 2;
  • 33) 0.808 411 597 854 683 955 2 × 2 = 1 + 0.616 823 195 709 367 910 4;
  • 34) 0.616 823 195 709 367 910 4 × 2 = 1 + 0.233 646 391 418 735 820 8;
  • 35) 0.233 646 391 418 735 820 8 × 2 = 0 + 0.467 292 782 837 471 641 6;
  • 36) 0.467 292 782 837 471 641 6 × 2 = 0 + 0.934 585 565 674 943 283 2;
  • 37) 0.934 585 565 674 943 283 2 × 2 = 1 + 0.869 171 131 349 886 566 4;
  • 38) 0.869 171 131 349 886 566 4 × 2 = 1 + 0.738 342 262 699 773 132 8;
  • 39) 0.738 342 262 699 773 132 8 × 2 = 1 + 0.476 684 525 399 546 265 6;
  • 40) 0.476 684 525 399 546 265 6 × 2 = 0 + 0.953 369 050 799 092 531 2;
  • 41) 0.953 369 050 799 092 531 2 × 2 = 1 + 0.906 738 101 598 185 062 4;
  • 42) 0.906 738 101 598 185 062 4 × 2 = 1 + 0.813 476 203 196 370 124 8;
  • 43) 0.813 476 203 196 370 124 8 × 2 = 1 + 0.626 952 406 392 740 249 6;
  • 44) 0.626 952 406 392 740 249 6 × 2 = 1 + 0.253 904 812 785 480 499 2;
  • 45) 0.253 904 812 785 480 499 2 × 2 = 0 + 0.507 809 625 570 960 998 4;
  • 46) 0.507 809 625 570 960 998 4 × 2 = 1 + 0.015 619 251 141 921 996 8;
  • 47) 0.015 619 251 141 921 996 8 × 2 = 0 + 0.031 238 502 283 843 993 6;
  • 48) 0.031 238 502 283 843 993 6 × 2 = 0 + 0.062 477 004 567 687 987 2;
  • 49) 0.062 477 004 567 687 987 2 × 2 = 0 + 0.124 954 009 135 375 974 4;
  • 50) 0.124 954 009 135 375 974 4 × 2 = 0 + 0.249 908 018 270 751 948 8;
  • 51) 0.249 908 018 270 751 948 8 × 2 = 0 + 0.499 816 036 541 503 897 6;
  • 52) 0.499 816 036 541 503 897 6 × 2 = 0 + 0.999 632 073 083 007 795 2;
  • 53) 0.999 632 073 083 007 795 2 × 2 = 1 + 0.999 264 146 166 015 590 4;

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:


0.745 459 324 169 999 826 2(10) =


0.1011 1110 1101 0110 0110 1100 0001 1001 1100 1110 1111 0100 0000 1(2)

5. Positive number before normalization:

1.745 459 324 169 999 826 2(10) =


1.1011 1110 1101 0110 0110 1100 0001 1001 1100 1110 1111 0100 0000 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 0 positions to the left, so that only one non zero digit remains to the left of it:


1.745 459 324 169 999 826 2(10) =


1.1011 1110 1101 0110 0110 1100 0001 1001 1100 1110 1111 0100 0000 1(2) =


1.1011 1110 1101 0110 0110 1100 0001 1001 1100 1110 1111 0100 0000 1(2) × 20


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): 0


Mantissa (not normalized):
1.1011 1110 1101 0110 0110 1100 0001 1001 1100 1110 1111 0100 0000 1


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


0 + 2(11-1) - 1 =


(0 + 1 023)(10) =


1 023(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;
  • 1 023 ÷ 2 = 511 + 1;
  • 511 ÷ 2 = 255 + 1;
  • 255 ÷ 2 = 127 + 1;
  • 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;

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) =


1023(10) =


011 1111 1111(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, 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. 1011 1110 1101 0110 0110 1100 0001 1001 1100 1110 1111 0100 0000 1 =


1011 1110 1101 0110 0110 1100 0001 1001 1100 1110 1111 0100 0000


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 1111


Mantissa (52 bits) =
1011 1110 1101 0110 0110 1100 0001 1001 1100 1110 1111 0100 0000


Decimal number 1.745 459 324 169 999 826 2 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 011 1111 1111 - 1011 1110 1101 0110 0110 1100 0001 1001 1100 1110 1111 0100 0000


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