Signals and Systems example problems?

AI Thread Summary
Resources for example problems in Signals and Systems, particularly on topics like Convolution and Fourier series, can be found through online searches, yielding class notes and exercises. Causal systems are defined as those where the output does not depend on future input values, while non-causal systems do. Real-world systems are typically causal, as they cannot anticipate future inputs. Examples of causal systems include equations like y(t) = 0.2x(t) - x(t-1), whereas non-causal systems might use y(t) = x(t+1). For further study, the textbook "Oppenheim" is recommended as a standard reference in the field.
davegillmour
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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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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!
 
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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please try to study from "Oppenheim". This is a standard book for signals and systems
 
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