# Sampling Theorem Viva Questions And Answers

**Sampling Theorem Viva Questions And Answers**

**1. Discuss in detail about Formatting?**

In digital communication, the first and most important
signal processing step is formatting. Formatting converts source data into
bits, ensuring that the data and signal processing processes of a digital
communication system are compatible.

i. Data that has already been converted to a digital
format would be bypassed by the formatting procedure.

ii. A coder converts textual data into binary digits.

iii. Analog data is structured in three steps:
sampling, quantification, and coding.

**2. What do you know about the sampling theorem.**

The sampling theorem may be categorised into two
parts:

(i) Sample values at uniform intervals less than or
equal to 1/2fm fully represented by a band-limited signal of finite energy
with no frequency components higher than fm Hertz.

(ii) A finite-energy band-limited signal with no
frequency components greater than fm Hertz may be fully recovered using just
the knowledge of its samples obtained at a rate of 2fm samples per second.

**3. Discuss in detail about Nyquist Theorem.**

The Nyquist theorem can be stated as follows. "To recover the signal exactly from its samples, the
sampling frequency (f_{s}) must be at the rate equal to or greater than
twice the highest frequency (maximum frequency) component (f_{m})
present in the signal".

Mathematically, it can be written as** f _{s}**

**≥2f**.

_{m}**4. What does sampling mean? Name the various sampling
techniques.**

Sampling is the process of converting a
continuous-time signal into a discrete-time signal. There are mainly three
basic types of sampling techniques.

1. Impulse sampling or Ideal sampling.

2. Natural sampling

3. Sample and hold operation or (flat top sampling).

**5. What do you know about impulse sampling? Mention its disadvantage?**

The method is known as the impulse or ideal sampling
if the sample function is a train of impulses. As a result of this procedure,
the breadth of the samples approaches zero. The power content of the
immediately sampled pulse is insignificant as a result of this. As a result,
this approach is unsuitable for transmission purposes.

**6. Explain in detail natural sampling? Discuss its
disadvantages?**

Natural sampling is the method used when the sampling
function is a pulse train or switching waveform. Each pulse in the sampled data
series has a changing top according to signal variation in this method. Noise
interferes with the top of pulses during transmission. The structure of the top
of the pulse at the receiver is very difficult to determine.

**7. Discuss sample and hold operation?**

The top of the pulse changes according to the signal
fluctuation in natural sampling. As a result, the amplitude detection of the
pulse is not precise, and mistakes in the signal are introduced. The solution
to this problem is to use flat-top pulses. Flat top pulses are generated using
a sample and hold circuit.

The sample and hold operation is defined as the
convolution of a sampled pulse train with a rectangular pulse of unity
amplitude. The flat-top sampled sequence is the outcome of the convolution
procedure.

**8. Explain about aliasing effect?**

Aliasing is the phenomenon in which a high-frequency
component in a signal's frequency spectrum assumes the identity of a lower
frequency component in the sampled signal's spectrum. Due to the effect of under-sampling (fs<
2fm), aliasing occurs.

**9. How we can prevent aliasing?**

Antialiasing filters may be used in two different
methods to eliminate aliasing.

(i) A low pass filter is used to preprocess the
analog signal. The filter's bandwidth is less than or equal to half of the
sampling frequency (fm<fs/2).

(ii) After sampling, a lowpass filter is used to
postfilter the analog signal. The aliased words can be removed after sampling
when the signal structure is well known.

**10. Explain quantization noise?**

Analog baseband signal sample values are rounded to
the quantizer's nearest allowable representation levels. Quantization noise is
a term used to describe the distortion caused by this approximation of the
quantized samples. The quantity of noise generated by the quantization process
is inversely related to the number of levels utilized.

**11. What is quantization? Mention its types.**

The quantization technique reduces continuous
amplitude values to a limited (discrete) range of acceptable values. In terms
of time and amplitude, this is referred to as "discretization." In
general, the quantization process may be categorized as follows.

I. Uniform quantization

1. Midtread type

2. Midrise type

II. Non-Uniform quantization

**12. What is Uniform Quantization?**

The quantizer is referred to as a Uniform or Linear
quantizer when the quantization levels are uniformly distributed over the
entire amplitude range of the input signal. Throughout the input range, the
step size between quantization levels remains the same.

**13.
Discuss non-uniform quantization?**

The
quantizer is considered non-uniform or non-linear if the quantization levels
are not uniformly distributed throughout the amplitude range of the input
signal. The stepsize between quantization levels fluctuates here according to a
system of rules.

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