-0.016 738 891 601 562 496 530 553 073 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.016 738 891 601 562 496 530 553 073(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
-0.016 738 891 601 562 496 530 553 073(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:

|-0.016 738 891 601 562 496 530 553 073| = 0.016 738 891 601 562 496 530 553 073


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: 0.016 738 891 601 562 496 530 553 073.

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) 0.016 738 891 601 562 496 530 553 073 × 2 = 0 + 0.033 477 783 203 124 993 061 106 146;
  • 2) 0.033 477 783 203 124 993 061 106 146 × 2 = 0 + 0.066 955 566 406 249 986 122 212 292;
  • 3) 0.066 955 566 406 249 986 122 212 292 × 2 = 0 + 0.133 911 132 812 499 972 244 424 584;
  • 4) 0.133 911 132 812 499 972 244 424 584 × 2 = 0 + 0.267 822 265 624 999 944 488 849 168;
  • 5) 0.267 822 265 624 999 944 488 849 168 × 2 = 0 + 0.535 644 531 249 999 888 977 698 336;
  • 6) 0.535 644 531 249 999 888 977 698 336 × 2 = 1 + 0.071 289 062 499 999 777 955 396 672;
  • 7) 0.071 289 062 499 999 777 955 396 672 × 2 = 0 + 0.142 578 124 999 999 555 910 793 344;
  • 8) 0.142 578 124 999 999 555 910 793 344 × 2 = 0 + 0.285 156 249 999 999 111 821 586 688;
  • 9) 0.285 156 249 999 999 111 821 586 688 × 2 = 0 + 0.570 312 499 999 998 223 643 173 376;
  • 10) 0.570 312 499 999 998 223 643 173 376 × 2 = 1 + 0.140 624 999 999 996 447 286 346 752;
  • 11) 0.140 624 999 999 996 447 286 346 752 × 2 = 0 + 0.281 249 999 999 992 894 572 693 504;
  • 12) 0.281 249 999 999 992 894 572 693 504 × 2 = 0 + 0.562 499 999 999 985 789 145 387 008;
  • 13) 0.562 499 999 999 985 789 145 387 008 × 2 = 1 + 0.124 999 999 999 971 578 290 774 016;
  • 14) 0.124 999 999 999 971 578 290 774 016 × 2 = 0 + 0.249 999 999 999 943 156 581 548 032;
  • 15) 0.249 999 999 999 943 156 581 548 032 × 2 = 0 + 0.499 999 999 999 886 313 163 096 064;
  • 16) 0.499 999 999 999 886 313 163 096 064 × 2 = 0 + 0.999 999 999 999 772 626 326 192 128;
  • 17) 0.999 999 999 999 772 626 326 192 128 × 2 = 1 + 0.999 999 999 999 545 252 652 384 256;
  • 18) 0.999 999 999 999 545 252 652 384 256 × 2 = 1 + 0.999 999 999 999 090 505 304 768 512;
  • 19) 0.999 999 999 999 090 505 304 768 512 × 2 = 1 + 0.999 999 999 998 181 010 609 537 024;
  • 20) 0.999 999 999 998 181 010 609 537 024 × 2 = 1 + 0.999 999 999 996 362 021 219 074 048;
  • 21) 0.999 999 999 996 362 021 219 074 048 × 2 = 1 + 0.999 999 999 992 724 042 438 148 096;
  • 22) 0.999 999 999 992 724 042 438 148 096 × 2 = 1 + 0.999 999 999 985 448 084 876 296 192;
  • 23) 0.999 999 999 985 448 084 876 296 192 × 2 = 1 + 0.999 999 999 970 896 169 752 592 384;
  • 24) 0.999 999 999 970 896 169 752 592 384 × 2 = 1 + 0.999 999 999 941 792 339 505 184 768;
  • 25) 0.999 999 999 941 792 339 505 184 768 × 2 = 1 + 0.999 999 999 883 584 679 010 369 536;
  • 26) 0.999 999 999 883 584 679 010 369 536 × 2 = 1 + 0.999 999 999 767 169 358 020 739 072;
  • 27) 0.999 999 999 767 169 358 020 739 072 × 2 = 1 + 0.999 999 999 534 338 716 041 478 144;
  • 28) 0.999 999 999 534 338 716 041 478 144 × 2 = 1 + 0.999 999 999 068 677 432 082 956 288;
  • 29) 0.999 999 999 068 677 432 082 956 288 × 2 = 1 + 0.999 999 998 137 354 864 165 912 576;
  • 30) 0.999 999 998 137 354 864 165 912 576 × 2 = 1 + 0.999 999 996 274 709 728 331 825 152;
  • 31) 0.999 999 996 274 709 728 331 825 152 × 2 = 1 + 0.999 999 992 549 419 456 663 650 304;
  • 32) 0.999 999 992 549 419 456 663 650 304 × 2 = 1 + 0.999 999 985 098 838 913 327 300 608;
  • 33) 0.999 999 985 098 838 913 327 300 608 × 2 = 1 + 0.999 999 970 197 677 826 654 601 216;
  • 34) 0.999 999 970 197 677 826 654 601 216 × 2 = 1 + 0.999 999 940 395 355 653 309 202 432;
  • 35) 0.999 999 940 395 355 653 309 202 432 × 2 = 1 + 0.999 999 880 790 711 306 618 404 864;
  • 36) 0.999 999 880 790 711 306 618 404 864 × 2 = 1 + 0.999 999 761 581 422 613 236 809 728;
  • 37) 0.999 999 761 581 422 613 236 809 728 × 2 = 1 + 0.999 999 523 162 845 226 473 619 456;
  • 38) 0.999 999 523 162 845 226 473 619 456 × 2 = 1 + 0.999 999 046 325 690 452 947 238 912;
  • 39) 0.999 999 046 325 690 452 947 238 912 × 2 = 1 + 0.999 998 092 651 380 905 894 477 824;
  • 40) 0.999 998 092 651 380 905 894 477 824 × 2 = 1 + 0.999 996 185 302 761 811 788 955 648;
  • 41) 0.999 996 185 302 761 811 788 955 648 × 2 = 1 + 0.999 992 370 605 523 623 577 911 296;
  • 42) 0.999 992 370 605 523 623 577 911 296 × 2 = 1 + 0.999 984 741 211 047 247 155 822 592;
  • 43) 0.999 984 741 211 047 247 155 822 592 × 2 = 1 + 0.999 969 482 422 094 494 311 645 184;
  • 44) 0.999 969 482 422 094 494 311 645 184 × 2 = 1 + 0.999 938 964 844 188 988 623 290 368;
  • 45) 0.999 938 964 844 188 988 623 290 368 × 2 = 1 + 0.999 877 929 688 377 977 246 580 736;
  • 46) 0.999 877 929 688 377 977 246 580 736 × 2 = 1 + 0.999 755 859 376 755 954 493 161 472;
  • 47) 0.999 755 859 376 755 954 493 161 472 × 2 = 1 + 0.999 511 718 753 511 908 986 322 944;
  • 48) 0.999 511 718 753 511 908 986 322 944 × 2 = 1 + 0.999 023 437 507 023 817 972 645 888;
  • 49) 0.999 023 437 507 023 817 972 645 888 × 2 = 1 + 0.998 046 875 014 047 635 945 291 776;
  • 50) 0.998 046 875 014 047 635 945 291 776 × 2 = 1 + 0.996 093 750 028 095 271 890 583 552;
  • 51) 0.996 093 750 028 095 271 890 583 552 × 2 = 1 + 0.992 187 500 056 190 543 781 167 104;
  • 52) 0.992 187 500 056 190 543 781 167 104 × 2 = 1 + 0.984 375 000 112 381 087 562 334 208;
  • 53) 0.984 375 000 112 381 087 562 334 208 × 2 = 1 + 0.968 750 000 224 762 175 124 668 416;
  • 54) 0.968 750 000 224 762 175 124 668 416 × 2 = 1 + 0.937 500 000 449 524 350 249 336 832;
  • 55) 0.937 500 000 449 524 350 249 336 832 × 2 = 1 + 0.875 000 000 899 048 700 498 673 664;
  • 56) 0.875 000 000 899 048 700 498 673 664 × 2 = 1 + 0.750 000 001 798 097 400 997 347 328;
  • 57) 0.750 000 001 798 097 400 997 347 328 × 2 = 1 + 0.500 000 003 596 194 801 994 694 656;
  • 58) 0.500 000 003 596 194 801 994 694 656 × 2 = 1 + 0.000 000 007 192 389 603 989 389 312;

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:


0.016 738 891 601 562 496 530 553 073(10) =

0.0000 0100 0100 1000 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 11(2)

6. Positive number before normalization:

0.016 738 891 601 562 496 530 553 073(10) =

0.0000 0100 0100 1000 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 11(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 6 positions to the right, so that only one non zero digit remains to the left of it:


0.016 738 891 601 562 496 530 553 073(10) =

0.0000 0100 0100 1000 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 11(2) =

0.0000 0100 0100 1000 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 11(2) × 20 =

1.0001 0010 0011 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111(2) × 2-6


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): -6

Mantissa (not normalized):
1.0001 0010 0011 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =

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

-6 + 2(11-1) - 1 =

(-6 + 1 023)(10) =

1 017(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;
  • 1 017 ÷ 2 = 508 + 1;
  • 508 ÷ 2 = 254 + 0;
  • 254 ÷ 2 = 127 + 0;
  • 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;

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) =

1017(10) =

011 1111 1001(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. 0001 0010 0011 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 =

0001 0010 0011 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111


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 1001

Mantissa (52 bits) =
0001 0010 0011 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111


Decimal number -0.016 738 891 601 562 496 530 553 073 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 1001 - 0001 0010 0011 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111

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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