Floating point normalization has a great usage for computing anything very near to accuracy. A floating point number is consists of: Mantissa or significand. Exponent. Say, I've a number 123.75. Its a floating point number. It has integer significand, 12375 and exponent -2. So arithmatic representation is 12375 x 10 -2 . How to normalize a floating point number? - By shifting the mantissa to left until a 1 appears in most significant bits(HO). Hence, the normalized representation will be 1.2375 x 10 +2 . Most of the time for normalized number this bit is hidden as it happens to be 1. This is hidden bit. Now the question when we can't normalize a floating point number? - There are two such situations: We can't normalize zero(0). The floating point representation of Zero doesn't contain any 1 bit. However, IEEE representation for +0 and -0 has different significance. We also can't normalize a floating point number whose most significant bits in mant