Assuming the number holds an unsigned number, the range of numbers for 4 bits is 0-7. 7 is a prime number.
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A decimal digit requires 4 bits of memory space to represent all possible values. So N decimal digits will require 4N bits to store in decimal format. On the other hand, if the same N decimal digits were stored as a binary number, they should require log2(10N) bits, that is, about 3.32N bits. So storing the decimal representation uses about 20% more memory. To put it another way, 4 bits is capable of holding one of 16 different values. By using it to store decimal digits, it is only being used to hold one of 10 different values.
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There are 16 decimal numbers that can be represented by 4-bits.
16 of them.
256x4=1024 bits are stored.128x8=1024 ,yes this chip can be specified as 128 byte
Assuming the number holds an unsigned number, the range of numbers for 4 bits is 0-7. 7 is a prime number.
Using 4 bits the signed range of numbers is -8 to 7. When working with signed numbers one bit is the sign bit, thus with 4 bits this leaves 3 bits for the value. With 3 bits there are 8 possible values, which when using 2s complement have ranges: for non-negative numbers these are 0 to 7; for negative numbers these are -1 to -8. Thus the range for signed 4 bit numbers is -8 to 7.
1 nibble = 4 bits, so 4 nibbles for 16 bits.
If all four bytes are being used for its value (i.e. this is an unsigned integer) then you have 8 * 4 = 32 bits, so your range is from 0 to 2^32 (4,294,967,296) Remember, the size of various data types in C and C++ is architecture dependent. See limits.h (/usr/include/limits.h in Linux)
Each hexidecimal character represents 4 bits, therefore 256 bits takes 256 / 4 = 64 characters.
Floating point numbers are stored in scientific notation using base 2 not base 10.There are a limited number of bits so they are stored to a certain number of significant binary figures.There are various number of bytes (bits) used to store the numbers - the bits being split between the mantissa (the number) and the exponent (the power of 10 (being in the base of the storage - in binary, 10 equals 2 in decimal) by which the mantissa is multiplied to get the binary/decimal point back to where it should be), examples:Single precision (IEEE) uses 4 bytes: 8 bits for the exponent (encoding ±), 1 bit for the sign of the number and 23 bits for the number itself;Double precision (IEEE) uses 8 bytes: 11 bits for the exponent, 1 bit for the sign, 52 bits for the number;The Commodore PET used 5 bytes: 8 bits for the exponent, 1 bit for the sign and 31 bits for the number;The Sinclair QL used 6 bytes: 12 bits for the exponent (stored in 2 bytes, 16 bits, 4 bits of which were unused), 1 bit for the sign and 31 bits for the number.The numbers are stored normalised:In decimal numbers the digit before the decimal point is non-zero, ie one of {1, 2, ..., 9}.In binary numbers, the only non-zero digit is 1, so *every* floating point number in binary (except 0) has a 1 before the binary point; thus the initial 1 (before the binary point) is not stored (it is implicit).The exponent is stored by adding an offset of 2^(bits of exponent - 1), eg with 8 bit exponents it is stored by adding 2^7 = 1000 0000Zero is stored by having an exponent of zero (and mantissa of zero).Example 10 (decimal):10 (decimal) = 1010 in binary → 1.010 × 10^11 (all digits binary) which is stored in single precision as:sign = 0exponent = 1000 0000 + 0000 0011 = 1000 00011mantissa = 010 0000 0000 0000 0000 0000 (the 1 before the binary point is explicit).Example -0.75 (decimal):-0.75 decimal = -0.11 in binary (0.75 = ½ + ¼) → 1.1 × 10^-1 (all digits binary) → single precision:sign = 1exponent = 1000 0000 + (-0000 0001) = 0111 1111mantissa = 100 0000 0000 0000 0000 0000Note 0.1 in decimal is a recurring binary fraction 0.1 (decimal) = 0.0001100110011... in binary which is one reason floating point numbers have rounding issues when dealing with decimal fractions.
Yes, a byte is 8 bits, and a one hexadecimal digit takes up four bits, so two hexadecimal digits can be stored in a byte. The largest hexadecimal digit is F (which is 15 in base ten.) In base two, this converts to 1111, which takes up four bits, which is why it only takes four bits to store a hexadecimal digit. With 8 bits, two hexadecimal digits can be stored (FF would be 11111111, which is 8 bits), and 8 bits make up a byte. Generally, 4 bits are always used to store a hexadecimal digit, using leading zeros where necessary. For example, the hexadecimal digit 5 would be stored as 0101, and the hexadecimal digits 5A would be stored as 01011010.
One nibble, or nybble, is equal to four bits.
32 bits. which is 4 bytes (8 bits in each byte).