1.745 459 324 169 999 823 55 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 1.745 459 324 169 999 823 55(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
1.745 459 324 169 999 823 55(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: 0.745 459 324 169 999 823 55.

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) 0.745 459 324 169 999 823 55 × 2 = 1 + 0.490 918 648 339 999 647 1;
  • 2) 0.490 918 648 339 999 647 1 × 2 = 0 + 0.981 837 296 679 999 294 2;
  • 3) 0.981 837 296 679 999 294 2 × 2 = 1 + 0.963 674 593 359 998 588 4;
  • 4) 0.963 674 593 359 998 588 4 × 2 = 1 + 0.927 349 186 719 997 176 8;
  • 5) 0.927 349 186 719 997 176 8 × 2 = 1 + 0.854 698 373 439 994 353 6;
  • 6) 0.854 698 373 439 994 353 6 × 2 = 1 + 0.709 396 746 879 988 707 2;
  • 7) 0.709 396 746 879 988 707 2 × 2 = 1 + 0.418 793 493 759 977 414 4;
  • 8) 0.418 793 493 759 977 414 4 × 2 = 0 + 0.837 586 987 519 954 828 8;
  • 9) 0.837 586 987 519 954 828 8 × 2 = 1 + 0.675 173 975 039 909 657 6;
  • 10) 0.675 173 975 039 909 657 6 × 2 = 1 + 0.350 347 950 079 819 315 2;
  • 11) 0.350 347 950 079 819 315 2 × 2 = 0 + 0.700 695 900 159 638 630 4;
  • 12) 0.700 695 900 159 638 630 4 × 2 = 1 + 0.401 391 800 319 277 260 8;
  • 13) 0.401 391 800 319 277 260 8 × 2 = 0 + 0.802 783 600 638 554 521 6;
  • 14) 0.802 783 600 638 554 521 6 × 2 = 1 + 0.605 567 201 277 109 043 2;
  • 15) 0.605 567 201 277 109 043 2 × 2 = 1 + 0.211 134 402 554 218 086 4;
  • 16) 0.211 134 402 554 218 086 4 × 2 = 0 + 0.422 268 805 108 436 172 8;
  • 17) 0.422 268 805 108 436 172 8 × 2 = 0 + 0.844 537 610 216 872 345 6;
  • 18) 0.844 537 610 216 872 345 6 × 2 = 1 + 0.689 075 220 433 744 691 2;
  • 19) 0.689 075 220 433 744 691 2 × 2 = 1 + 0.378 150 440 867 489 382 4;
  • 20) 0.378 150 440 867 489 382 4 × 2 = 0 + 0.756 300 881 734 978 764 8;
  • 21) 0.756 300 881 734 978 764 8 × 2 = 1 + 0.512 601 763 469 957 529 6;
  • 22) 0.512 601 763 469 957 529 6 × 2 = 1 + 0.025 203 526 939 915 059 2;
  • 23) 0.025 203 526 939 915 059 2 × 2 = 0 + 0.050 407 053 879 830 118 4;
  • 24) 0.050 407 053 879 830 118 4 × 2 = 0 + 0.100 814 107 759 660 236 8;
  • 25) 0.100 814 107 759 660 236 8 × 2 = 0 + 0.201 628 215 519 320 473 6;
  • 26) 0.201 628 215 519 320 473 6 × 2 = 0 + 0.403 256 431 038 640 947 2;
  • 27) 0.403 256 431 038 640 947 2 × 2 = 0 + 0.806 512 862 077 281 894 4;
  • 28) 0.806 512 862 077 281 894 4 × 2 = 1 + 0.613 025 724 154 563 788 8;
  • 29) 0.613 025 724 154 563 788 8 × 2 = 1 + 0.226 051 448 309 127 577 6;
  • 30) 0.226 051 448 309 127 577 6 × 2 = 0 + 0.452 102 896 618 255 155 2;
  • 31) 0.452 102 896 618 255 155 2 × 2 = 0 + 0.904 205 793 236 510 310 4;
  • 32) 0.904 205 793 236 510 310 4 × 2 = 1 + 0.808 411 586 473 020 620 8;
  • 33) 0.808 411 586 473 020 620 8 × 2 = 1 + 0.616 823 172 946 041 241 6;
  • 34) 0.616 823 172 946 041 241 6 × 2 = 1 + 0.233 646 345 892 082 483 2;
  • 35) 0.233 646 345 892 082 483 2 × 2 = 0 + 0.467 292 691 784 164 966 4;
  • 36) 0.467 292 691 784 164 966 4 × 2 = 0 + 0.934 585 383 568 329 932 8;
  • 37) 0.934 585 383 568 329 932 8 × 2 = 1 + 0.869 170 767 136 659 865 6;
  • 38) 0.869 170 767 136 659 865 6 × 2 = 1 + 0.738 341 534 273 319 731 2;
  • 39) 0.738 341 534 273 319 731 2 × 2 = 1 + 0.476 683 068 546 639 462 4;
  • 40) 0.476 683 068 546 639 462 4 × 2 = 0 + 0.953 366 137 093 278 924 8;
  • 41) 0.953 366 137 093 278 924 8 × 2 = 1 + 0.906 732 274 186 557 849 6;
  • 42) 0.906 732 274 186 557 849 6 × 2 = 1 + 0.813 464 548 373 115 699 2;
  • 43) 0.813 464 548 373 115 699 2 × 2 = 1 + 0.626 929 096 746 231 398 4;
  • 44) 0.626 929 096 746 231 398 4 × 2 = 1 + 0.253 858 193 492 462 796 8;
  • 45) 0.253 858 193 492 462 796 8 × 2 = 0 + 0.507 716 386 984 925 593 6;
  • 46) 0.507 716 386 984 925 593 6 × 2 = 1 + 0.015 432 773 969 851 187 2;
  • 47) 0.015 432 773 969 851 187 2 × 2 = 0 + 0.030 865 547 939 702 374 4;
  • 48) 0.030 865 547 939 702 374 4 × 2 = 0 + 0.061 731 095 879 404 748 8;
  • 49) 0.061 731 095 879 404 748 8 × 2 = 0 + 0.123 462 191 758 809 497 6;
  • 50) 0.123 462 191 758 809 497 6 × 2 = 0 + 0.246 924 383 517 618 995 2;
  • 51) 0.246 924 383 517 618 995 2 × 2 = 0 + 0.493 848 767 035 237 990 4;
  • 52) 0.493 848 767 035 237 990 4 × 2 = 0 + 0.987 697 534 070 475 980 8;
  • 53) 0.987 697 534 070 475 980 8 × 2 = 1 + 0.975 395 068 140 951 961 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:


0.745 459 324 169 999 823 55(10) =


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

5. Positive number before normalization:

1.745 459 324 169 999 823 55(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:


1.745 459 324 169 999 823 55(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 1.745 459 324 169 999 823 55 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