Random Processes | Digital Signal Processing # 12

📚About
This lecture is dedicated for random processes and their importance in signal processing. We naturally arrive at the need of defining random processes due to the structure of the received signal which is a superposition of three components: an information-bearing signal, an interfering (or unwanted) signal and background noise. Random processes are thought of a time-varying random variable where each time sample in this random process is itself a random variable with its own distribution function. Indeed, random process lie in the core of any radio communication system and their understanding is crucial for an signal processing study. The lecture ends by showing how to generate a very simple random process on MATLAB. This lecture is outlined as follows:

⏲Outline
00:00 Highlights
00:20 Introduction
01:01 Radio Communication System
01:53 Received Signal
02:40 Information-bearing Signal
03:51 Interfering Signal
04:29 Noise Part
05:16 Random Processes
07:16 Average Power
08:48 Sample Space
16:18 Random Process on MATLAB
20:34 Summary
21:34 Outro

📙Previous Lectures

📖 Related Content
Proakis, John G., and Dimitris G. Manolakis. "Digital signal processing." PHI Publication: New Delhi, India (2004).

Oppenheim, Alan V., John R. Buck, and Ronald W. Schafer. Discrete-time signal processing. Vol. 2. Upper Saddle River, NJ: Prentice Hall, 2001.

MATLAB

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#SignalProcessing #RandomProcess #CommunicationSystems

[hisakojaques]

14:19 clarified my doubts on sampling space for random processes :)

[sungseller]

2:07 I love the way you explain signal processing concepts as a it stick in my head

[jenelinwood]

13:01 That clarified my doubts of sample space :)

[serkankisin]

You are a very underrated GURU and Youtuber sir.

[auroreferron]

7:34 reminds me of my calculus integrations

[semihinoyundunyas]

Random process definition: *A random process is a time-varying function that assigns the outcome of a random experiment to each time instant: X(t)*

[Andytheblue]

A random or stochastic process is a random variable that evolves in time by some random mechanism.

[alisonomalley]

Thanks for another great lesson professor.

[williefigueroa]

19:08 I don't understand the meshgrid part, why one for time and other for sample?

[lagendgamer]

Please continue with your convex optimization series Ahmad !

[montanagloria]

Random variables is for family of random variables is for signal processing.

[reluzvideos]

Is it the same as stochastic processes ?

[bugra_g]

Sir, can Random Process be continuous or discrete ?

[shadhamby]

I see random processes as *uncountable number of random variables*

[yusufipek]

Thanks for another great lesson professor.