I'm preparing for some exams and one of the questions given in the past is to find the closest number to 1.7 given an imaginary floating point format that has a total of 8 bits (1 for sign, 3 for exponent, 4 for significand).
Anyway I put down 1.1011 since I can play with four significand digits and the 1 is implied by the IEEE standard. However, setting the exponent to 000 would make it a denormalised number. Does this mean the value 1.7 would be 1.1100 in floating point?
thx
A Floating Point number usually has a decimal point. This means that 0, 3.14, 6.5, and -125.5 are Floating Point numbers.
Like scientific notation, floating-point numbers have a sign, mantissa (M), base (B), and exponent (E), as shown in Figure 5.27. For example, the number 4.1 × 103 is the decimal scientific notation for 4100. It has a mantissa of 4.1, a base of 10, and an exponent of 3.
A single-precision, floating-point number is a 32-bit approximation of a real number. The number can be zero or can range from -3.40282347E+38 to -1.17549435E-38, or from 1.17549435E-38 to 3.40282347E+38.
So how many “normal” non-zero numbers are there between 0 and 1? The negative exponents range from -1 all the way to -126. In each case, we have 223 distinct floating-point numbers because the mantissa is made of 23 bits. So we have 126 x 223 normal floating-point numbers in [0,1).
The questioner posted an answer that was deleted by a moderator. I've flagged it for attention, but I'll add a few notes here as well.
The key is that IEEE-754-style floating-point formats store the exponent in a "biased" (also called "excess-n") integer format. With 3 exponent bits, the bias is 3, so the set of encodeable exponents is:
encoding meaning
000 exponent for zeros and denormals
001 2^-2
010 2^-1
011 2^0
100 2^1
101 2^2
110 2^3
111 exponent for infinities and NaNs
Thus, the questioners value 1.7 would have an exponent field of 3 (b011
), and a significand field of b1011
as he stated, which makes the full value b00111011
.
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