1.703 864 206 57 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 1.703 864 206 57(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
1.703 864 206 57(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: 0.703 864 206 57.

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) 0.703 864 206 57 × 2 = 1 + 0.407 728 413 14;
  • 2) 0.407 728 413 14 × 2 = 0 + 0.815 456 826 28;
  • 3) 0.815 456 826 28 × 2 = 1 + 0.630 913 652 56;
  • 4) 0.630 913 652 56 × 2 = 1 + 0.261 827 305 12;
  • 5) 0.261 827 305 12 × 2 = 0 + 0.523 654 610 24;
  • 6) 0.523 654 610 24 × 2 = 1 + 0.047 309 220 48;
  • 7) 0.047 309 220 48 × 2 = 0 + 0.094 618 440 96;
  • 8) 0.094 618 440 96 × 2 = 0 + 0.189 236 881 92;
  • 9) 0.189 236 881 92 × 2 = 0 + 0.378 473 763 84;
  • 10) 0.378 473 763 84 × 2 = 0 + 0.756 947 527 68;
  • 11) 0.756 947 527 68 × 2 = 1 + 0.513 895 055 36;
  • 12) 0.513 895 055 36 × 2 = 1 + 0.027 790 110 72;
  • 13) 0.027 790 110 72 × 2 = 0 + 0.055 580 221 44;
  • 14) 0.055 580 221 44 × 2 = 0 + 0.111 160 442 88;
  • 15) 0.111 160 442 88 × 2 = 0 + 0.222 320 885 76;
  • 16) 0.222 320 885 76 × 2 = 0 + 0.444 641 771 52;
  • 17) 0.444 641 771 52 × 2 = 0 + 0.889 283 543 04;
  • 18) 0.889 283 543 04 × 2 = 1 + 0.778 567 086 08;
  • 19) 0.778 567 086 08 × 2 = 1 + 0.557 134 172 16;
  • 20) 0.557 134 172 16 × 2 = 1 + 0.114 268 344 32;
  • 21) 0.114 268 344 32 × 2 = 0 + 0.228 536 688 64;
  • 22) 0.228 536 688 64 × 2 = 0 + 0.457 073 377 28;
  • 23) 0.457 073 377 28 × 2 = 0 + 0.914 146 754 56;
  • 24) 0.914 146 754 56 × 2 = 1 + 0.828 293 509 12;
  • 25) 0.828 293 509 12 × 2 = 1 + 0.656 587 018 24;
  • 26) 0.656 587 018 24 × 2 = 1 + 0.313 174 036 48;
  • 27) 0.313 174 036 48 × 2 = 0 + 0.626 348 072 96;
  • 28) 0.626 348 072 96 × 2 = 1 + 0.252 696 145 92;
  • 29) 0.252 696 145 92 × 2 = 0 + 0.505 392 291 84;
  • 30) 0.505 392 291 84 × 2 = 1 + 0.010 784 583 68;
  • 31) 0.010 784 583 68 × 2 = 0 + 0.021 569 167 36;
  • 32) 0.021 569 167 36 × 2 = 0 + 0.043 138 334 72;
  • 33) 0.043 138 334 72 × 2 = 0 + 0.086 276 669 44;
  • 34) 0.086 276 669 44 × 2 = 0 + 0.172 553 338 88;
  • 35) 0.172 553 338 88 × 2 = 0 + 0.345 106 677 76;
  • 36) 0.345 106 677 76 × 2 = 0 + 0.690 213 355 52;
  • 37) 0.690 213 355 52 × 2 = 1 + 0.380 426 711 04;
  • 38) 0.380 426 711 04 × 2 = 0 + 0.760 853 422 08;
  • 39) 0.760 853 422 08 × 2 = 1 + 0.521 706 844 16;
  • 40) 0.521 706 844 16 × 2 = 1 + 0.043 413 688 32;
  • 41) 0.043 413 688 32 × 2 = 0 + 0.086 827 376 64;
  • 42) 0.086 827 376 64 × 2 = 0 + 0.173 654 753 28;
  • 43) 0.173 654 753 28 × 2 = 0 + 0.347 309 506 56;
  • 44) 0.347 309 506 56 × 2 = 0 + 0.694 619 013 12;
  • 45) 0.694 619 013 12 × 2 = 1 + 0.389 238 026 24;
  • 46) 0.389 238 026 24 × 2 = 0 + 0.778 476 052 48;
  • 47) 0.778 476 052 48 × 2 = 1 + 0.556 952 104 96;
  • 48) 0.556 952 104 96 × 2 = 1 + 0.113 904 209 92;
  • 49) 0.113 904 209 92 × 2 = 0 + 0.227 808 419 84;
  • 50) 0.227 808 419 84 × 2 = 0 + 0.455 616 839 68;
  • 51) 0.455 616 839 68 × 2 = 0 + 0.911 233 679 36;
  • 52) 0.911 233 679 36 × 2 = 1 + 0.822 467 358 72;
  • 53) 0.822 467 358 72 × 2 = 1 + 0.644 934 717 44;

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:


0.703 864 206 57(10) =


0.1011 0100 0011 0000 0111 0001 1101 0100 0000 1011 0000 1011 0001 1(2)

5. Positive number before normalization:

1.703 864 206 57(10) =


1.1011 0100 0011 0000 0111 0001 1101 0100 0000 1011 0000 1011 0001 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:


1.703 864 206 57(10) =


1.1011 0100 0011 0000 0111 0001 1101 0100 0000 1011 0000 1011 0001 1(2) =


1.1011 0100 0011 0000 0111 0001 1101 0100 0000 1011 0000 1011 0001 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 0100 0011 0000 0111 0001 1101 0100 0000 1011 0000 1011 0001 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 0100 0011 0000 0111 0001 1101 0100 0000 1011 0000 1011 0001 1 =


1011 0100 0011 0000 0111 0001 1101 0100 0000 1011 0000 1011 0001


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 0100 0011 0000 0111 0001 1101 0100 0000 1011 0000 1011 0001


Decimal number 1.703 864 206 57 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 011 1111 1111 - 1011 0100 0011 0000 0111 0001 1101 0100 0000 1011 0000 1011 0001

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