This set of Digital Signal Processing Multiple Choice Questions & Answers (MCQs) focuses on “Representation of Numbers-1”.

1. If (101.01)_{2}=(x)_{10}, then what is the value of x?

a) 505.05

b) 10.101

c) 101.01

d) 5.25

View Answer

Explanation: (101.01)

_{2}=1*2

^{2}+0*2

^{1}+1*2

^{0}+0*2

^{-1}+1*2

^{-2}=(5.25)

_{10}

=>x=5.25

2. If X is a real number with ‘r’ as the radix, A is the number of integer digits and B is the number of fraction digits, then

a) True

b) False

View Answer

Explanation: A real number X can be represented as where b

_{i}represents the digit, ‘r’ is the radix or base, A is the number of integer digits, and B is the number of fractional digits.

3. The binary point between the digits b0 and b1 exist physically in the computer.

a) True

b) False

View Answer

Explanation: The binary point between the digits b0 and b1 does not exist physically in the computer. Simply, the logic circuits of the computer are designed such that the computations result in numbers that correspond to the assumed location of this point.

a) (xmax+xmin)/(2

^{b}-1)

b) (xmax+xmin)/(2

^{b}+1)

c) (xmax-xmin)/(2

^{b}-1)

d) (xmax-xmin)/(2

^{b}+1)

View Answer

Explanation: A fixed point representation of numbers allows us to cover a range of numbers, say,xmax-xmin with a resolution

Δ=(xmax-xmin)/(m-1)

where m=2

^{b}is the number of levels and ‘b’ is the number of bits.

5. What are the mantissa and exponent required respectively to represent ‘5’ in binary floating point representation?

a) 011,0.110000

b) 0.110000,011

c) 011,0.101000

d) 0.101000,011

View Answer

Explanation: We can represent 5 as

5=0.625*8=0.625*2

^{3}

The above number can be represented in binary float point representation as 0.101000*2

^{011}

Thus Mantissa=0.101000, Exponent=011.

6. If the two numbers are to be multiplied, the mantissas are multiplied and the exponents are added.

a) True

b) False

View Answer

Explanation: Let us consider two numbers X=M.2

^{E}and Y=N.2

^{F}

If we multiply both X and Y, we get X.Y=(M.N).2

^{E+F}

Thus if we multiply two numbers, the mantissas are multiplied and the exponents are added.

7. What is the smallest floating point number that can be represented using a 32-bit word?

a) 3*10^{-38}

b) 2*10^{-38}

c) 0.2*10^{-38}

d) 0.3*10^{-38}

View Answer

Explanation: Let the mantissa be represented by 23 bits plus a sign bit and let the exponent be represented by 7 bits plus a sign bit.

Thus, the smallest floating point number that can be represented using the 32 bit number is

(1/2)*2

^{-127}=0.3*10

^{-38}

Thus, the smallest floating point number that can be represented using the 32 bit number is

(1-2

^{-23})*2

^{127/sup>=1.7*1038}

a) Fractional number

b) Infinity

c) Mixed number

d) Zero

View Answer

Explanation: According to the IEEE 754 standard, for a 32-bit machine, single precision floating point number is represented as X=(-1)c(M).

From the above equation we can interpret that,

If 0<E<255, then X=(-1)

^{s}.2

^{E-127}(1.M)=>X is a mixed number.

9. For a twos complement representation, the truncation error is:

a) Always positive

b) Always negative

c) Zero

d) None of the mentioned

View Answer

Explanation: For a two’s complement representation, the truncation error is always negative and falls in the range

-(2

^{-b}-2

^{-bm}) ≤ E

_{t ≤ 0.}

10. Due to non-uniform resolution, the corresponding error in a floating point representation is proportional to the number being quantized.

a) True

b) False

View Answer

Explanation: In floating point representation, the mantissa is either rounded or truncated. Due to non-uniform resolution, the corresponding error in a floating point representation is proportional to the number being quantized.

**Sanfoundry Global Education & Learning Series – Digital Signal Processing.**

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