Signals and Systems example problems?

In summary, Convolution, Fourier series, and determining if a system is causal are all important topics to understand when studying signals and systems.
  • #1
davegillmour
9
0
Are there any resources on the web that provide example problems (with solutions) to Signals problems? My textbook (shown below) lacks any clear example problems (shows answers without showing you how to get them). If someone could point me toward examples of Convolution, Fourier series, or determining if a system is causal, time invariant ect would really help a lot.
Thanks


Text: https://www.amazon.com/dp/0130412074/?tag=pfamazon01-20
 
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  • #2
I googled convolution sample problems, and got lots of good hits. Here's the hit list:

http://www.google.com/search?hl=en&q=convolution+sample+problems

Some of the hits are just from class descriptions, but others have full class notes and sample problems and exercises. You can probably just google Fourier series sample problems, etc., to get the other hits you are looking for. Have fun!
 
  • #3
Causal and Non- causal system

hi there,
look i am going to explain you Causal and Non-Causal systems..
A system is causal if response or output does not begin befor the input function is applied. This means that if input is applied at t=t', then for causal system, output will depend on values of input x(t) for t lessthan or equals to t'.
Mathematically,
y(t')=f[x(t),t<=t']
In other words, we can say that a causal system is non-anticipatory. The response or output of the causal system to an input does not depends upon future values of that input, but depends only on the present and the past values of the input.
A resistor is an example of continuous time causal system because voltage across it is given by the expression
v(t) = R.i(t)
and output v(t), i.e., voltage depends only on the input i(t) i.e., current at the present time...
All the real time systems are also causal systems since these system cannot know the future value of the input signal when it construct output signal.
Thus cuasal systems are physically realizable.

Few more examples for causal and non causal systems are as follows:

Causal Systems

1. y(t) = 0.2x(t) - x(t-1)
2. y(t) = 0.8x(t-1)
3. y(n) = x(n-1)

Non-causal systems

1. y(t) = x(t+1)
2. y(n-2) = x(n)
3. y(n) = x(n)-x(n+1)..
i think its too enough for now. I will also explain you about convolution, fourier, time varient and invarient system and whatever you want to know about signals and systems..
 
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  • #4
please try to study from "Oppenheim". This is a standard book for signals and systems
 

1. What is the purpose of studying signals and systems example problems?

The purpose of studying signals and systems example problems is to gain a deeper understanding of the fundamental concepts and principles of signals and systems, such as time and frequency domains, convolution, and Fourier transforms. It also helps in developing problem-solving skills and prepares students for real-world applications in various fields such as telecommunications, control systems, and signal processing.

2. What are some common types of signals encountered in signals and systems example problems?

Some common types of signals encountered in signals and systems example problems include continuous-time signals, discrete-time signals, periodic signals, and non-periodic signals. Examples of continuous-time signals include analog audio signals and temperature readings, while digital audio signals and stock market data are examples of discrete-time signals.

3. How do we analyze signals and systems in example problems?

Signals and systems are typically analyzed using mathematical tools such as differential equations, Laplace transforms, and Fourier series and transforms. These tools help in understanding the behavior of signals and systems and their responses to different inputs. Graphical representations, such as time-domain and frequency-domain plots, are also commonly used for analysis.

4. What are some real-world applications of signals and systems example problems?

Signals and systems have numerous real-world applications, including telecommunication systems, control systems, audio and video processing, biomedical signal processing, and image processing. They are also used in fields such as robotics and aerospace engineering to analyze and design systems for various applications.

5. How can I improve my problem-solving skills in signals and systems?

To improve problem-solving skills in signals and systems, it is important to practice solving a variety of example problems and understanding the underlying concepts and principles. Working with others and discussing different approaches to solve problems can also help in improving problem-solving skills. Additionally, staying updated on new developments and applications in the field can also aid in enhancing problem-solving abilities.

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