0.957 603 280 698 573 587 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 0.957 603 280 698 573 587(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
0.957 603 280 698 573 587(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: 0.957 603 280 698 573 587.

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) 0.957 603 280 698 573 587 × 2 = 1 + 0.915 206 561 397 147 174;
  • 2) 0.915 206 561 397 147 174 × 2 = 1 + 0.830 413 122 794 294 348;
  • 3) 0.830 413 122 794 294 348 × 2 = 1 + 0.660 826 245 588 588 696;
  • 4) 0.660 826 245 588 588 696 × 2 = 1 + 0.321 652 491 177 177 392;
  • 5) 0.321 652 491 177 177 392 × 2 = 0 + 0.643 304 982 354 354 784;
  • 6) 0.643 304 982 354 354 784 × 2 = 1 + 0.286 609 964 708 709 568;
  • 7) 0.286 609 964 708 709 568 × 2 = 0 + 0.573 219 929 417 419 136;
  • 8) 0.573 219 929 417 419 136 × 2 = 1 + 0.146 439 858 834 838 272;
  • 9) 0.146 439 858 834 838 272 × 2 = 0 + 0.292 879 717 669 676 544;
  • 10) 0.292 879 717 669 676 544 × 2 = 0 + 0.585 759 435 339 353 088;
  • 11) 0.585 759 435 339 353 088 × 2 = 1 + 0.171 518 870 678 706 176;
  • 12) 0.171 518 870 678 706 176 × 2 = 0 + 0.343 037 741 357 412 352;
  • 13) 0.343 037 741 357 412 352 × 2 = 0 + 0.686 075 482 714 824 704;
  • 14) 0.686 075 482 714 824 704 × 2 = 1 + 0.372 150 965 429 649 408;
  • 15) 0.372 150 965 429 649 408 × 2 = 0 + 0.744 301 930 859 298 816;
  • 16) 0.744 301 930 859 298 816 × 2 = 1 + 0.488 603 861 718 597 632;
  • 17) 0.488 603 861 718 597 632 × 2 = 0 + 0.977 207 723 437 195 264;
  • 18) 0.977 207 723 437 195 264 × 2 = 1 + 0.954 415 446 874 390 528;
  • 19) 0.954 415 446 874 390 528 × 2 = 1 + 0.908 830 893 748 781 056;
  • 20) 0.908 830 893 748 781 056 × 2 = 1 + 0.817 661 787 497 562 112;
  • 21) 0.817 661 787 497 562 112 × 2 = 1 + 0.635 323 574 995 124 224;
  • 22) 0.635 323 574 995 124 224 × 2 = 1 + 0.270 647 149 990 248 448;
  • 23) 0.270 647 149 990 248 448 × 2 = 0 + 0.541 294 299 980 496 896;
  • 24) 0.541 294 299 980 496 896 × 2 = 1 + 0.082 588 599 960 993 792;
  • 25) 0.082 588 599 960 993 792 × 2 = 0 + 0.165 177 199 921 987 584;
  • 26) 0.165 177 199 921 987 584 × 2 = 0 + 0.330 354 399 843 975 168;
  • 27) 0.330 354 399 843 975 168 × 2 = 0 + 0.660 708 799 687 950 336;
  • 28) 0.660 708 799 687 950 336 × 2 = 1 + 0.321 417 599 375 900 672;
  • 29) 0.321 417 599 375 900 672 × 2 = 0 + 0.642 835 198 751 801 344;
  • 30) 0.642 835 198 751 801 344 × 2 = 1 + 0.285 670 397 503 602 688;
  • 31) 0.285 670 397 503 602 688 × 2 = 0 + 0.571 340 795 007 205 376;
  • 32) 0.571 340 795 007 205 376 × 2 = 1 + 0.142 681 590 014 410 752;
  • 33) 0.142 681 590 014 410 752 × 2 = 0 + 0.285 363 180 028 821 504;
  • 34) 0.285 363 180 028 821 504 × 2 = 0 + 0.570 726 360 057 643 008;
  • 35) 0.570 726 360 057 643 008 × 2 = 1 + 0.141 452 720 115 286 016;
  • 36) 0.141 452 720 115 286 016 × 2 = 0 + 0.282 905 440 230 572 032;
  • 37) 0.282 905 440 230 572 032 × 2 = 0 + 0.565 810 880 461 144 064;
  • 38) 0.565 810 880 461 144 064 × 2 = 1 + 0.131 621 760 922 288 128;
  • 39) 0.131 621 760 922 288 128 × 2 = 0 + 0.263 243 521 844 576 256;
  • 40) 0.263 243 521 844 576 256 × 2 = 0 + 0.526 487 043 689 152 512;
  • 41) 0.526 487 043 689 152 512 × 2 = 1 + 0.052 974 087 378 305 024;
  • 42) 0.052 974 087 378 305 024 × 2 = 0 + 0.105 948 174 756 610 048;
  • 43) 0.105 948 174 756 610 048 × 2 = 0 + 0.211 896 349 513 220 096;
  • 44) 0.211 896 349 513 220 096 × 2 = 0 + 0.423 792 699 026 440 192;
  • 45) 0.423 792 699 026 440 192 × 2 = 0 + 0.847 585 398 052 880 384;
  • 46) 0.847 585 398 052 880 384 × 2 = 1 + 0.695 170 796 105 760 768;
  • 47) 0.695 170 796 105 760 768 × 2 = 1 + 0.390 341 592 211 521 536;
  • 48) 0.390 341 592 211 521 536 × 2 = 0 + 0.780 683 184 423 043 072;
  • 49) 0.780 683 184 423 043 072 × 2 = 1 + 0.561 366 368 846 086 144;
  • 50) 0.561 366 368 846 086 144 × 2 = 1 + 0.122 732 737 692 172 288;
  • 51) 0.122 732 737 692 172 288 × 2 = 0 + 0.245 465 475 384 344 576;
  • 52) 0.245 465 475 384 344 576 × 2 = 0 + 0.490 930 950 768 689 152;
  • 53) 0.490 930 950 768 689 152 × 2 = 0 + 0.981 861 901 537 378 304;

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:


0.957 603 280 698 573 587(10) =


0.1111 0101 0010 0101 0111 1101 0001 0101 0010 0100 1000 0110 1100 0(2)

5. Positive number before normalization:

0.957 603 280 698 573 587(10) =


0.1111 0101 0010 0101 0111 1101 0001 0101 0010 0100 1000 0110 1100 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 1 positions to the right, so that only one non zero digit remains to the left of it:


0.957 603 280 698 573 587(10) =


0.1111 0101 0010 0101 0111 1101 0001 0101 0010 0100 1000 0110 1100 0(2) =


0.1111 0101 0010 0101 0111 1101 0001 0101 0010 0100 1000 0110 1100 0(2) × 20 =


1.1110 1010 0100 1010 1111 1010 0010 1010 0100 1001 0000 1101 1000(2) × 2-1


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): -1


Mantissa (not normalized):
1.1110 1010 0100 1010 1111 1010 0010 1010 0100 1001 0000 1101 1000


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


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


(-1 + 1 023)(10) =


1 022(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;
  • 1 022 ÷ 2 = 511 + 0;
  • 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) =


1022(10) =


011 1111 1110(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. 1110 1010 0100 1010 1111 1010 0010 1010 0100 1001 0000 1101 1000 =


1110 1010 0100 1010 1111 1010 0010 1010 0100 1001 0000 1101 1000


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 1110


Mantissa (52 bits) =
1110 1010 0100 1010 1111 1010 0010 1010 0100 1001 0000 1101 1000


Decimal number 0.957 603 280 698 573 587 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 011 1111 1110 - 1110 1010 0100 1010 1111 1010 0010 1010 0100 1001 0000 1101 1000


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