Signals and Systems : From Basics to Advance from Udemy

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Syllabus

6. Gate Signal or Rectangular Signal

Signals and system deals with operations of signals and types of signals and systems. These topics explains the clear understanding of electrical signals, representation as the signals.

1. Signals and Systems Introduction - Step Signals

2. Impulse Signal

3. Ramp Signals and Parabolic Signals

4. All Signals Summary

5. Standard Signals

7. Sampling Signal or Sync Signal

8. How to perform operations on Signals

9. Time Scaling Operation

10. Folding Operation (Time Reversal)

Adding , Subtraction and Multiplication Operations - Part 1

Adding , Subtraction and Multiplication Operations - Part 2

Operations on Signals - Differentiation

Classification of Signals (Constant and Discrete , Real and Imaginary )

Periodic and AP signals

Problems on Periodicity

Periodicity of Discrete time signals.

Even and Odd Signals

Problems on Even and Odd Signals - 1

Problems on Even and Odd Signals - 2

Energy and Power Signal.

Problems on Energy and Power Signal.

Problems on Discrete time Signal.

Deterministic and Random Signals.

Systems

1. Introduction to Systems

2. Types of Systems : Linear Systems and Nonlinear Systems

3. Types of Systems : Stable Systems and Unstable Systems

4. Types of Systems : Static Systems and Dynamic Systems

5. Types of Systems : Causal Systems and Non-causal Systems

Fourier series is used to separate DC and AC terms of periodic functions and used to convert nonsinusoidal signals to sinusoidal signals. Fourier series used for periodic functions.

Introduction to Fourier Series

Trigonometric Fourier Series (Real)

Problems on Trigonometric Fourier Series

Short Notes on Trigonometric Fourier Series

Derivation of EFS from Trigonometric Fourier Series

Problems Using EFS

Fourier Transform from Fourier Series

To find complete signals frequency response. It is the combination of Magnitude and Phase responses. These are used to find Bandwidth and resonant frequency,to design Stable system and analog circuits

Introduction to Fourier Transform.

Fourier Transform of Different Signals.

Magnitude and Phase Responses.

Fourier Transform of Rectangular.

Properties of Fourier Transform (Linearity).

Frequency and Shifting.

Time Scaling.

Time Folding and Time Differentiation.

Frequency Differentiation.

Integration Property.

Overview on Properties of Fourier Transform.

Problems on Properties of Fourier Transform - 1.

Problems on Properties of Fourier Transform - 2.

Fourier Transform of Sinusoidal Signals - 1.

Fourier Transform of Sinusoidal Signals - 2.

Fourier Transform of Triangular Signals.

Problems on Fourier Transform.

Fourier Transform of Signum Function.

Fourier Transform of Unit Step Function.

Overview of Fourier Transform.

Fourier Transform Notes

Laplace Transform

Limitations of Fourier Transform and Why Laplace Transform

Introduction of Laplace Transform.

Laplace Transform of Exponential Signals

Properties of Region of Convergence (ROC)

Laplace Transform OF Different Signals

Laplace Transform of Basic Signals

Properties of L.T - 1 : Linearity, Shifting( Time and Frequency), and Scaling

Overview of Properties of Laplace Transform

Applications of Laplace Transform - 1

Applications of Laplace Transform

Inverse Laplace Transform : Part - 1

Inverse Laplace Transform : Part - 2

Inverse Laplace Transform : Part - 3

Linear Time Invariant (LTI) Systems

Linear Time Invariant (LTI) System Responses

Differential Equations

Impulse response of the system

Sinusoidal Responses

Initial and Final Values of Function

Laplace Transform Notes

Sampling. ADC

Sampling

Sampling Theorem

Sampling1

Z-Transform

Introduction to Z-Transform and L.T and Z.T Relation.

Relation between S-Plane and Z-Plane

ROC of Z Transform.

Z-Transform of Basic Signals.

ROC of Basic Signals.

Z-Transform of Different Signals - 1.

Z-Transform of Different Signals - 2.

Inverse Z-Transform.

Problems on Inverse Z- Transform.

Problems on Z-Transform - 1.

Problems on Z-Transform - 2.

Problems on Z-Transform - 3.

Problems on Z-Transform - 4.

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Signals and Systems : From Basics to Advance with these activities:

Review Calculus Fundamentals

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Strengthen your understanding of calculus concepts, which are essential for grasping Fourier and Laplace transforms.

Browse courses on Calculus

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Review differentiation and integration techniques.
Practice solving problems involving limits and continuity.
Familiarize yourself with common functions and their properties.

Signals and Systems

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Supplement your learning with a comprehensive textbook that provides in-depth explanations and examples.

View Signals and Systems (Second Edition) on Amazon

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Read the chapters corresponding to the course syllabus.
Work through the example problems in the book.
Attempt the end-of-chapter exercises for practice.

Solve Fourier Transform Problems

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Reinforce your understanding of Fourier transforms by solving a variety of problems.

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Find practice problems online or in textbooks.
Work through the problems step-by-step.
Check your answers and review the solutions.

Four other activities

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Create a Signals and Systems Cheat Sheet

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Summarize key concepts and formulas into a concise cheat sheet for quick reference.

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Identify the most important formulas and concepts.
Organize the information in a clear and concise manner.
Include examples and diagrams to illustrate the concepts.

Design a Simple Filter

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Apply your knowledge of signals and systems to design a basic filter that meets specific requirements.

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Define the filter specifications (e.g., cutoff frequency, passband ripple).
Choose a suitable filter type (e.g., Butterworth, Chebyshev).
Calculate the filter coefficients.
Simulate the filter's performance using software like MATLAB or Python.

Understanding Digital Signal Processing

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Explore the practical applications of signals and systems in digital signal processing.

View Digital Signal Processing: A Practical Guide... on Amazon

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Read the relevant chapters on digital filtering and signal analysis.
Experiment with the examples provided in the book.
Consider how the concepts relate to the course material.

Help Others in Online Forums

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Solidify your understanding by explaining concepts and answering questions from other students in online forums.

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Monitor online forums related to signals and systems.
Identify questions that you can answer confidently.
Provide clear and concise explanations.

Career center

Learners who complete Signals and Systems : From Basics to Advance will develop knowledge and skills that may be useful to these careers:

Signal Processing Engineer

A signal processing engineer analyzes, designs, and develops signal processing systems. This course, which covers signals and systems representations and classifications along with time and frequency domain analysis, directly benefits a signal processing engineer. The course's coverage of Fourier series, Fourier transforms, Laplace transforms, and Z transforms is particularly useful as these are essential tools in the field. The course's discussion of the limitations of Fourier transforms gives a signal processing engineer insight into when to employ Laplace transforms and how to analyze systems in the s-domain. A signal processing engineer should find this course quite helpful.

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Control Systems Engineer

Control systems engineers design, develop, and test control systems. This course provides a strong foundation for a control systems engineer by exploring the fundamental properties of linear systems and developing input output relationships for linear shift invariant systems. Understanding the convolution operator for continuous and discrete time systems, as discussed in this course, is crucial for designing and analyzing control systems. The coverage of Laplace transforms further aids a control systems engineer in analyzing system behavior in the s-domain. A control systems engineer will likely find this course quite valuable.

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Telecommunications Engineer

Telecommunications engineers design and oversee the installation of telecommunications equipment and facilities, such as complex electronic switching systems, and other plain old telephone service facilities, optical fiber cabling, data networks, and wireless infrastructure. The time and frequency domain analysis of continuous time signals, covered in this course, is particularly relevant. The course's exploration of Fourier series and transforms, as well as Laplace and Z transforms, provides a telecommunications engineer with essential tools for analyzing signals and systems. Learning about sampling and analog to digital conversion would be valuable to a telecommunications engineer.

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RF Engineer

An RF engineer designs, develops, and tests radio frequency (RF) components and systems. The exploration of Fourier transforms helps an RF engineer find a signal's frequency response. The course material on magnitude and phase responses gives an RF engineer insight into bandwidth and resonant frequency for designing stable systems and analog circuits. Furthermore, the treatment of Laplace transforms allows the RF engineer to analyze systems in the s-domain. An RF engineer who wants to broaden their skillset would benefit from this course.

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Audio Engineer

Audio engineers record, mix, and master sound. This course may be useful to an audio engineer, particularly the sections on Fourier transforms, which help the audio engineer find a signal's frequency response. Understanding magnitude and phase responses, as well as bandwidth and resonant frequency, are also helpful to an audio engineer. The signal operations discussed like adding and subtraction, and differentiation are all applicable to the field. An audio engineer can use this background to analyze different audio systems.

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Image Processing Engineer

Image processing engineers develop algorithms and systems for processing and analyzing images. This course may be useful for an image processing engineer, particularly the sections on Fourier transforms and Z transforms. These transforms are used to analyze images in the frequency domain. The exploration of different types of signals, including rectangular signals, might be beneficial for understanding image data representations. An image processing engineer could benefit from the course to analyze images.

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Data Scientist

Data scientists analyze large datasets to extract meaningful insights and develop predictive models. This course may be useful to a data scientist, particularly the sections related to signal processing techniques. While data science often involves different types of data, the underlying principles of signal analysis can be applied to time series data or other sequential data. A data scientist may find the sections on Fourier transforms and Z transforms helpful for analyzing data in different domains. A data scientist can use signal processing techniques to complement their existing knowledge.

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Machine Learning Engineer

Machine learning engineers develop and implement machine learning algorithms and models. The course may be useful to a machine learning engineer, especially considering the overlap between signal processing and machine learning. Understanding signal representations, Fourier transforms, Laplace transforms, and Z transforms can be beneficial for machine learning applications involving time series data or signal-based features. The course could provide a machine learning engineer with additional tools and techniques for feature extraction and data analysis.

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Robotics Engineer

Robotics engineers design, build, and program robots for various applications. This course may be helpful, particularly the sections on signals and systems analysis. Robotics often involves processing sensor data, controlling actuators, and analyzing system responses. The course's coverage of Fourier transforms, Laplace transforms, and Z transforms can be valuable for analyzing sensor signals and designing control systems for robots. Robotics engineers may be able to use this knowledge to improve robot performance.

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Embedded Systems Engineer

Embedded systems engineers design, develop, and test software and hardware for embedded systems. The topics covered, such as signal operations, different transforms, and system responses can broaden an embedded systems engineer's understanding of signal processing. This understanding is essential for processing sensor data or implementing control algorithms in embedded systems. An embedded systems engineer can use insights from this course to improve the performance and reliability of embedded systems.

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Biomedical Engineer

Biomedical engineers apply engineering principles to solve medical and healthcare-related problems. A biomedical engineer working with medical devices or signal processing applications may find the course's coverage of signal representations, Fourier transforms, Laplace transforms, and Z transforms useful. These concepts can be applied to analyze biomedical signals such as electrocardiograms (ECG) or electroencephalograms (EEG). A biomedical engineer can use the knowledge gained to improve diagnostic or therapeutic devices.

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Acoustic Consultant

Acoustic consultants advise on sound and vibration issues in buildings and environments. This course may be relevant, especially the sections on Fourier analysis, which are essential for analyzing sound signals and understanding frequency characteristics. The course's coverage of different transforms may help you model acoustic systems and predict sound propagation. Acoustic consultants can apply these concepts to design effective noise control measures and optimize acoustic environments.

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Data Analyst

Data analysts examine data using statistical techniques and software to identify trends and insights that lead to improvements in a company's operations. A data analyst can apply the concepts of signal processing to time series data. The course's coverage of Fourier transforms, Laplace transforms, and Z transforms can be valuable for analyzing patterns and anomalies in time-dependent data. Data analysts can enhance their analytical skills and improve the accuracy of their insights.

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Network Engineer

Network engineers design, implement, and manage computer networks. This course may provide value by offering insights into signal transmission and processing within networks. The concepts covered in the course, such as signal representations, Fourier transforms, and Z transforms may be applicable to analyzing network traffic and optimizing network performance. Understanding these concepts can help network engineers design more efficient and reliable networks. It will allow them to fine tune their network performance.

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Technical Writer

Technical writers create technical documentation such as user manuals and help guides. While this career is not directly related to the course, an understanding of technical fields such as signal processing may be useful. The course's coverage of signals and systems provides a technical writer with a foundation for communicating technical information clearly and accurately. Technical writers can use this knowledge to create high-quality documentation for signal processing-related products.

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Signals and Systems

From Basics to Advance

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