# Signals And Systems in B.Tech

Signals and Systems Video Course By Dennis Freeman, MIT
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Students Enrolled: 2 Total Lecturs: 24
Refer & Earn

### What will I learn from this course?

• Appriciate Signals and process.

### Requirements

• Any body who wants college level any Electronic Students.

### Who is the target audience?

• Any Body in UG as per Collage level

### Course Curriculum

Total: 24 lectures
• 48m 39s

Lec 1: Signals and Sysytems

• 48m 48s

Lec 2: Discrete-Time (DT) Systems

• 51m 17s

Lec 3: Feedback, Poles, and Fundamental Modes

• 52m 55s

Lec 4: Continuous-Time (CT) Systems

• 48m 38s

Lec 5: Z -Transform

• 45m 25s

Lec 6: Laplace Transform

• 45m 22s

Lec 7: Discrete Approximation of Continuous-Time Systems

• 53m 44s

Lec 8: Convolution

• 50m 43s

Lec 9: Frequency Response

• 36m s

Lec 10: Feedback and Control

• 53m 21s

Lec 11: Continuous-Time (CT) Frequency Response and Bode Plot

• 49m 33s

Lec 12: Continuous-Time (CT) Feedback and Control, Part 1

• 48m 49s

Lec 13: Continuous-Time (CT) Feedback and Control, Part 2

• 50m 11s

Lec 14: Fourier Representations

• 47m 28s

Lec 15: Fourier Series

• 45m 51s

Lec 16: Fourier Transform

• 51m 28s

Lec 17: Discrete-Time (DT) Frequency Representations

• 51m 43s

Lec 18: Discrete-Time (DT) Fourier Representations

• 47m 37s

Lec 19: Relations Among Fourier Representations

• 50m 15s

Lec 20: Applications of Fourier Transforms

• 52m 30s

Lec 21: Sampling

• 53m 1s

Lec 22: Sampling and Quantization

• 51m 11s

Lec 23: Modulation, Part 1

• 43m 15s

Lec 24: Modulation, Part 2

### Description

The fundamentals of signal and system analysis, focusing on representations of discrete-time and continuous-time signals (singularity functions, complex exponentials and geometrics, Fourier representations, Laplace and Z transforms, sampling) and representations of linear, time-invariant systems (difference and differential equations, block diagrams, system functions, poles and zeros, convolution, impulse and step responses, frequency responses). Applications are drawn broadly from engineering and physics, including feedback and control, communications, and signal processing.