Q1 (a) (b) (c) Given arbitrary signals, x(t) and y(t) as shown in Figure Q1. 2 -2 x(t) 2 t Figure Q1 Draw graph of the following signals: (i) x (+2) (ii) x(t).y(t - 2) 2 y(t) 4 2 t Express x(t) in Figure Q1 using a single analytical expression with the aid of the unit step function, u(t). Sketch the even and odd components of x(t) in Figure Q1 using the definition of even and odd signals.
Quantization and Resolution
Quantization is a methodology of carrying out signal modulation by the process of mapping input values from an infinitely long set of continuous values to a smaller set of finite values. Quantization forms the basic algorithm for lossy compression algorithms and represents a given analog signal into digital signals. In other words, these algorithms form the base of an analog-to-digital converter. Devices that process the algorithm of quantization are known as a quantizer. These devices aid in rounding off (approximation) the errors of an input function called the quantized value.
Probability of Error
This topic is widely taught in many undergraduate and postgraduate degree courses of:
![Q1
(a)
(b)
(c)
(d)
Given arbitrary signals, x(t) and y(t) as shown in Figure Q1.
2
-2
x(t)
N
2
t
Figure Q1
Draw graph of the following signals:
(i) x (+2)
(ii) x(t).y(t-2)
2
y(t)
4
2
t
Express x(t) in Figure Q1 using a single analytical expression with the aid of the
unit step function, u(t).
Sketch the even and odd components of x(t) in Figure Q1 using the definition of
even and odd signals.
Derive the analytical expression of the signal y(t) in Figure Q1 and sketch the
signal dt
d[y(t)]](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fa964a701-ebde-441e-8ac9-bfdd0a8a15ea%2Fafc33679-4665-4457-9d8d-2c3e0751822c%2F2acf1rq_processed.jpeg&w=3840&q=75)
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