-0.000 282 006 264 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 006 264(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
-0.000 282 006 264(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. Start with the positive version of the number:

|-0.000 282 006 264| = 0.000 282 006 264


2. 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;

3. 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)


4. Convert to binary (base 2) the fractional part: 0.000 282 006 264.

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) 0.000 282 006 264 × 2 = 0 + 0.000 564 012 528;
  • 2) 0.000 564 012 528 × 2 = 0 + 0.001 128 025 056;
  • 3) 0.001 128 025 056 × 2 = 0 + 0.002 256 050 112;
  • 4) 0.002 256 050 112 × 2 = 0 + 0.004 512 100 224;
  • 5) 0.004 512 100 224 × 2 = 0 + 0.009 024 200 448;
  • 6) 0.009 024 200 448 × 2 = 0 + 0.018 048 400 896;
  • 7) 0.018 048 400 896 × 2 = 0 + 0.036 096 801 792;
  • 8) 0.036 096 801 792 × 2 = 0 + 0.072 193 603 584;
  • 9) 0.072 193 603 584 × 2 = 0 + 0.144 387 207 168;
  • 10) 0.144 387 207 168 × 2 = 0 + 0.288 774 414 336;
  • 11) 0.288 774 414 336 × 2 = 0 + 0.577 548 828 672;
  • 12) 0.577 548 828 672 × 2 = 1 + 0.155 097 657 344;
  • 13) 0.155 097 657 344 × 2 = 0 + 0.310 195 314 688;
  • 14) 0.310 195 314 688 × 2 = 0 + 0.620 390 629 376;
  • 15) 0.620 390 629 376 × 2 = 1 + 0.240 781 258 752;
  • 16) 0.240 781 258 752 × 2 = 0 + 0.481 562 517 504;
  • 17) 0.481 562 517 504 × 2 = 0 + 0.963 125 035 008;
  • 18) 0.963 125 035 008 × 2 = 1 + 0.926 250 070 016;
  • 19) 0.926 250 070 016 × 2 = 1 + 0.852 500 140 032;
  • 20) 0.852 500 140 032 × 2 = 1 + 0.705 000 280 064;
  • 21) 0.705 000 280 064 × 2 = 1 + 0.410 000 560 128;
  • 22) 0.410 000 560 128 × 2 = 0 + 0.820 001 120 256;
  • 23) 0.820 001 120 256 × 2 = 1 + 0.640 002 240 512;
  • 24) 0.640 002 240 512 × 2 = 1 + 0.280 004 481 024;
  • 25) 0.280 004 481 024 × 2 = 0 + 0.560 008 962 048;
  • 26) 0.560 008 962 048 × 2 = 1 + 0.120 017 924 096;
  • 27) 0.120 017 924 096 × 2 = 0 + 0.240 035 848 192;
  • 28) 0.240 035 848 192 × 2 = 0 + 0.480 071 696 384;
  • 29) 0.480 071 696 384 × 2 = 0 + 0.960 143 392 768;
  • 30) 0.960 143 392 768 × 2 = 1 + 0.920 286 785 536;
  • 31) 0.920 286 785 536 × 2 = 1 + 0.840 573 571 072;
  • 32) 0.840 573 571 072 × 2 = 1 + 0.681 147 142 144;
  • 33) 0.681 147 142 144 × 2 = 1 + 0.362 294 284 288;
  • 34) 0.362 294 284 288 × 2 = 0 + 0.724 588 568 576;
  • 35) 0.724 588 568 576 × 2 = 1 + 0.449 177 137 152;
  • 36) 0.449 177 137 152 × 2 = 0 + 0.898 354 274 304;
  • 37) 0.898 354 274 304 × 2 = 1 + 0.796 708 548 608;
  • 38) 0.796 708 548 608 × 2 = 1 + 0.593 417 097 216;
  • 39) 0.593 417 097 216 × 2 = 1 + 0.186 834 194 432;
  • 40) 0.186 834 194 432 × 2 = 0 + 0.373 668 388 864;
  • 41) 0.373 668 388 864 × 2 = 0 + 0.747 336 777 728;
  • 42) 0.747 336 777 728 × 2 = 1 + 0.494 673 555 456;
  • 43) 0.494 673 555 456 × 2 = 0 + 0.989 347 110 912;
  • 44) 0.989 347 110 912 × 2 = 1 + 0.978 694 221 824;
  • 45) 0.978 694 221 824 × 2 = 1 + 0.957 388 443 648;
  • 46) 0.957 388 443 648 × 2 = 1 + 0.914 776 887 296;
  • 47) 0.914 776 887 296 × 2 = 1 + 0.829 553 774 592;
  • 48) 0.829 553 774 592 × 2 = 1 + 0.659 107 549 184;
  • 49) 0.659 107 549 184 × 2 = 1 + 0.318 215 098 368;
  • 50) 0.318 215 098 368 × 2 = 0 + 0.636 430 196 736;
  • 51) 0.636 430 196 736 × 2 = 1 + 0.272 860 393 472;
  • 52) 0.272 860 393 472 × 2 = 0 + 0.545 720 786 944;
  • 53) 0.545 720 786 944 × 2 = 1 + 0.091 441 573 888;
  • 54) 0.091 441 573 888 × 2 = 0 + 0.182 883 147 776;
  • 55) 0.182 883 147 776 × 2 = 0 + 0.365 766 295 552;
  • 56) 0.365 766 295 552 × 2 = 0 + 0.731 532 591 104;
  • 57) 0.731 532 591 104 × 2 = 1 + 0.463 065 182 208;
  • 58) 0.463 065 182 208 × 2 = 0 + 0.926 130 364 416;
  • 59) 0.926 130 364 416 × 2 = 1 + 0.852 260 728 832;
  • 60) 0.852 260 728 832 × 2 = 1 + 0.704 521 457 664;
  • 61) 0.704 521 457 664 × 2 = 1 + 0.409 042 915 328;
  • 62) 0.409 042 915 328 × 2 = 0 + 0.818 085 830 656;
  • 63) 0.818 085 830 656 × 2 = 1 + 0.636 171 661 312;
  • 64) 0.636 171 661 312 × 2 = 1 + 0.272 343 322 624;

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).


5. 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:


0.000 282 006 264(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1010 1110 0101 1111 1010 1000 1011 1011(2)

6. Positive number before normalization:

0.000 282 006 264(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1010 1110 0101 1111 1010 1000 1011 1011(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 12 positions to the right, so that only one non zero digit remains to the left of it:


0.000 282 006 264(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1010 1110 0101 1111 1010 1000 1011 1011(2) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1010 1110 0101 1111 1010 1000 1011 1011(2) × 20 =


1.0010 0111 1011 0100 0111 1010 1110 0101 1111 1010 1000 1011 1011(2) × 2-12


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): -12


Mantissa (not normalized):
1.0010 0111 1011 0100 0111 1010 1110 0101 1111 1010 1000 1011 1011


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


-12 + 2(11-1) - 1 =


(-12 + 1 023)(10) =


1 011(10)


10. 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;
  • 1 011 ÷ 2 = 505 + 1;
  • 505 ÷ 2 = 252 + 1;
  • 252 ÷ 2 = 126 + 0;
  • 126 ÷ 2 = 63 + 0;
  • 63 ÷ 2 = 31 + 1;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 1 ÷ 2 = 0 + 1;

11. Construct the base 2 representation of the adjusted exponent.

Take all the remainders starting from the bottom of the list constructed above.


Exponent (adjusted) =


1011(10) =


011 1111 0011(2)


12. 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. 0010 0111 1011 0100 0111 1010 1110 0101 1111 1010 1000 1011 1011 =


0010 0111 1011 0100 0111 1010 1110 0101 1111 1010 1000 1011 1011


13. The three elements that make up the number's 64 bit double precision IEEE 754 binary floating point representation:

Sign (1 bit) =
1 (a negative number)


Exponent (11 bits) =
011 1111 0011


Mantissa (52 bits) =
0010 0111 1011 0100 0111 1010 1110 0101 1111 1010 1000 1011 1011


Decimal number -0.000 282 006 264 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0111 1010 1110 0101 1111 1010 1000 1011 1011


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