0.974 013 318 541 726 4 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 0.974 013 318 541 726 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
0.974 013 318 541 726 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. 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: 0.974 013 318 541 726 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) 0.974 013 318 541 726 4 × 2 = 1 + 0.948 026 637 083 452 8;
  • 2) 0.948 026 637 083 452 8 × 2 = 1 + 0.896 053 274 166 905 6;
  • 3) 0.896 053 274 166 905 6 × 2 = 1 + 0.792 106 548 333 811 2;
  • 4) 0.792 106 548 333 811 2 × 2 = 1 + 0.584 213 096 667 622 4;
  • 5) 0.584 213 096 667 622 4 × 2 = 1 + 0.168 426 193 335 244 8;
  • 6) 0.168 426 193 335 244 8 × 2 = 0 + 0.336 852 386 670 489 6;
  • 7) 0.336 852 386 670 489 6 × 2 = 0 + 0.673 704 773 340 979 2;
  • 8) 0.673 704 773 340 979 2 × 2 = 1 + 0.347 409 546 681 958 4;
  • 9) 0.347 409 546 681 958 4 × 2 = 0 + 0.694 819 093 363 916 8;
  • 10) 0.694 819 093 363 916 8 × 2 = 1 + 0.389 638 186 727 833 6;
  • 11) 0.389 638 186 727 833 6 × 2 = 0 + 0.779 276 373 455 667 2;
  • 12) 0.779 276 373 455 667 2 × 2 = 1 + 0.558 552 746 911 334 4;
  • 13) 0.558 552 746 911 334 4 × 2 = 1 + 0.117 105 493 822 668 8;
  • 14) 0.117 105 493 822 668 8 × 2 = 0 + 0.234 210 987 645 337 6;
  • 15) 0.234 210 987 645 337 6 × 2 = 0 + 0.468 421 975 290 675 2;
  • 16) 0.468 421 975 290 675 2 × 2 = 0 + 0.936 843 950 581 350 4;
  • 17) 0.936 843 950 581 350 4 × 2 = 1 + 0.873 687 901 162 700 8;
  • 18) 0.873 687 901 162 700 8 × 2 = 1 + 0.747 375 802 325 401 6;
  • 19) 0.747 375 802 325 401 6 × 2 = 1 + 0.494 751 604 650 803 2;
  • 20) 0.494 751 604 650 803 2 × 2 = 0 + 0.989 503 209 301 606 4;
  • 21) 0.989 503 209 301 606 4 × 2 = 1 + 0.979 006 418 603 212 8;
  • 22) 0.979 006 418 603 212 8 × 2 = 1 + 0.958 012 837 206 425 6;
  • 23) 0.958 012 837 206 425 6 × 2 = 1 + 0.916 025 674 412 851 2;
  • 24) 0.916 025 674 412 851 2 × 2 = 1 + 0.832 051 348 825 702 4;
  • 25) 0.832 051 348 825 702 4 × 2 = 1 + 0.664 102 697 651 404 8;
  • 26) 0.664 102 697 651 404 8 × 2 = 1 + 0.328 205 395 302 809 6;
  • 27) 0.328 205 395 302 809 6 × 2 = 0 + 0.656 410 790 605 619 2;
  • 28) 0.656 410 790 605 619 2 × 2 = 1 + 0.312 821 581 211 238 4;
  • 29) 0.312 821 581 211 238 4 × 2 = 0 + 0.625 643 162 422 476 8;
  • 30) 0.625 643 162 422 476 8 × 2 = 1 + 0.251 286 324 844 953 6;
  • 31) 0.251 286 324 844 953 6 × 2 = 0 + 0.502 572 649 689 907 2;
  • 32) 0.502 572 649 689 907 2 × 2 = 1 + 0.005 145 299 379 814 4;
  • 33) 0.005 145 299 379 814 4 × 2 = 0 + 0.010 290 598 759 628 8;
  • 34) 0.010 290 598 759 628 8 × 2 = 0 + 0.020 581 197 519 257 6;
  • 35) 0.020 581 197 519 257 6 × 2 = 0 + 0.041 162 395 038 515 2;
  • 36) 0.041 162 395 038 515 2 × 2 = 0 + 0.082 324 790 077 030 4;
  • 37) 0.082 324 790 077 030 4 × 2 = 0 + 0.164 649 580 154 060 8;
  • 38) 0.164 649 580 154 060 8 × 2 = 0 + 0.329 299 160 308 121 6;
  • 39) 0.329 299 160 308 121 6 × 2 = 0 + 0.658 598 320 616 243 2;
  • 40) 0.658 598 320 616 243 2 × 2 = 1 + 0.317 196 641 232 486 4;
  • 41) 0.317 196 641 232 486 4 × 2 = 0 + 0.634 393 282 464 972 8;
  • 42) 0.634 393 282 464 972 8 × 2 = 1 + 0.268 786 564 929 945 6;
  • 43) 0.268 786 564 929 945 6 × 2 = 0 + 0.537 573 129 859 891 2;
  • 44) 0.537 573 129 859 891 2 × 2 = 1 + 0.075 146 259 719 782 4;
  • 45) 0.075 146 259 719 782 4 × 2 = 0 + 0.150 292 519 439 564 8;
  • 46) 0.150 292 519 439 564 8 × 2 = 0 + 0.300 585 038 879 129 6;
  • 47) 0.300 585 038 879 129 6 × 2 = 0 + 0.601 170 077 758 259 2;
  • 48) 0.601 170 077 758 259 2 × 2 = 1 + 0.202 340 155 516 518 4;
  • 49) 0.202 340 155 516 518 4 × 2 = 0 + 0.404 680 311 033 036 8;
  • 50) 0.404 680 311 033 036 8 × 2 = 0 + 0.809 360 622 066 073 6;
  • 51) 0.809 360 622 066 073 6 × 2 = 1 + 0.618 721 244 132 147 2;
  • 52) 0.618 721 244 132 147 2 × 2 = 1 + 0.237 442 488 264 294 4;
  • 53) 0.237 442 488 264 294 4 × 2 = 0 + 0.474 884 976 528 588 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).


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:


0.974 013 318 541 726 4(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0101 0001 0011 0(2)

5. Positive number before normalization:

0.974 013 318 541 726 4(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0101 0001 0011 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:


0.974 013 318 541 726 4(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0101 0001 0011 0(2) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0101 0001 0011 0(2) × 20 =


1.1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 1010 0010 0110(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):
1.1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 1010 0010 0110


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. 1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 1010 0010 0110 =


1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 1010 0010 0110


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) =
1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 1010 0010 0110


Decimal number 0.974 013 318 541 726 4 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 011 1111 1110 - 1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 1010 0010 0110


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