Your videos is just amazing sir...I used to see Feynman's videos and I read his book...but now I found another teacher like Feynman...thanks a lot sirrr...your videos helped me a lot...n still helping sir...☺️☺️💖💖❤️❤️
It all makes sense now !! Dear Prof. Hajimiri, many thanks for sharing this knowledge, for your dedication and for your unique teaching approach that makes all so easy to understand. You are a true inspiration !! God bless you!!
It is an understatement but i wish i had such a professor in my undergraduate years. But also got to be aware that such professors only belong to the best institutions of the World. That is how the two complement each other. On another note, a bad professor can ruin your life whereas a good professor can make it heaven. That is the power of quality teaching.
don't know why there are so small number of views on your videos, i found your teaching to be efficient, fun and easy to understand! "definitely subscribing!"
Magnific, I´ve been looking for some proper explanation on impulse, impulse response and convolution of LTI systems and your class made it all clear, Thanks !!!!
Hello I found your videos very useful. Thank you so much. But one thing I want to suggest for you is that it would be much convenient if you write time in the description box. For example, sifting property (starts at --:--) convolution starts at --:--
Thank you for your good suggestion. It sounds like a good idea that I will try to incorporate when I have time :-). In the meantime, if you happen to what a video and do that in the comments I will be happy o place them in the description box for others to use. Once again thanks for your input.
Hi, Thanks for these videos. I think the doubt student had at time 21:00 was two things. a). u(t-2) - which you had explained clearly. but also, b) why the u(t-2) was giving a value of 2 at t =2? Since that function was getting added on top of the previous function it went to 2 and not 1 ,as the u(t) normally would. Since the addition of u(t-2) was doing these two things simultaneously, it was probably not apparent. I feel.
00:02 Introduction to unit step function and its shifted versions 02:08 The Dirac delta function is defined as a pulse function. 07:16 The Delta function has infinite height at 0 and 0 height elsewhere 09:33 Dirac Delta and Step Function 14:45 Building functions using basic singularity functions 17:11 Discussing structure functions and creating jumps 22:23 Linear systems can be reduced to smaller functions and expressed as a sum of their responses. 24:25 Functions can be deconstructed into elementary singularity functions. 29:56 Function approximation using lookup tables 32:12 Dirac Delta represents functions in the limit of Delta going to zero. 37:56 The sifting property allows you to take out a specific value from a function. 40:32 One-sided functions have value 0 for T < 0, related to time definition and causality. 44:26 Linear systems operate on inputs to produce outputs. 46:58 Linear systems are impervious to scaling and only respond to functions of time. 52:27 Impulse response and time-invariant systems 55:01 Assumptions of linearity and time invariance 59:07 Impulse response reveals true system characteristics 1:01:15 For an LTI system, you can determine the response to any input using the convolution of the impulse response and the input. Crafted by Merlin AI.
At 30:25 when you write f(t)=summation , I got really confused should it not be F(t) or some sort of integral of the function because it is the area under the function. Are we approximating the function drawn or are we approximating the integral of the function drawn? I would appreciate if anybody could clearify!
Yep I believe there was a mixup there the way prof. worded it. We are approximating the function f(t) (NOT the area!) by summing all these individual pulses scaled by f(tau). We are not getting area under the function, neither are we connecting the "dots" per each f(tau) - we are essentially superpositioning all these pulse function (impulses) to compose the shape of f(t)
سلام استاد بسیار از تدریس شما استفاده کردم. من دانشجوی ارشد عمران هستم و برای پایان نامه نیاز به مباحث کنترل دارم و از فیلم های شما بسیار استفاده می کنم. ممنون که اونها رو در یوتیوب قرار دادید.
1:01:55 - another way to look at it : We do not need to worry about how the output will behave to a given input to this LTI system, as long as we know the system's Impulse response. We can simply add up a ' lookup table-value' of the input multiplied by the impulse response of the system (which we know) and add them over -/+ infinity. is that understanding correct?
Well, it is more than that. It is not simply a one-to-one function converting and instantaneous input value to and instantaneous output value, rather it captures the aggregate effect of the input from negative infinity to present time (for a causal system). So it is a lot more, because is captures the effect of the 'memory' of the system of its past. Hope this helps.
At 37:20 - that integral is equal to f(tau), which is a particular value, so how that value can be similar to the function f(t). f(t) is a f(tau) function for different tau values. Someone, please explain this.
Gents I am sorry for my previous comment, as the quality of video by time it's been improve I think it's due to the connection with Internet I am very sorry
This is how a great professor looks like, thank you very much :)
These videos have been invaluable during this difficult time, thank you so much for uploading these!
Your videos is just amazing sir...I used to see Feynman's videos and I read his book...but now I found another teacher like Feynman...thanks a lot sirrr...your videos helped me a lot...n still helping sir...☺️☺️💖💖❤️❤️
It all makes sense now !! Dear Prof. Hajimiri, many thanks for sharing this knowledge, for your dedication and for your unique teaching approach that makes all so easy to understand. You are a true inspiration !! God bless you!!
Your are quite welcome and thanks for your kindness.
It is an understatement but i wish i had such a professor in my undergraduate years. But also got to be aware that such professors only belong to the best institutions of the World. That is how the two complement each other. On another note, a bad professor can ruin your life whereas a good professor can make it heaven. That is the power of quality teaching.
Time Stamps:
0:00 = Review
9:12 = Differential Operator (P), Integral Operator (1/P)
11:49 = Unit Ramp, Unit Parabola
15:30 = Constructing Functions using Singularity Functions
26:05 = Constructing Functions using Unit Pulse Functions
34:43 = Sifting Property ("Look Up Table")
40:38 = One-Sided Functions, Philosophy of Causality
43:30 = System Operator (H), Impulse Response (h)
50:48 = LTV (Linear Time Variance) vs LTI (Linear Time Invariance)
57:37 = Philosophy of Impulse Response
Thank you for your effort in indexing the videos.
@@AliHajimiriChannel It has been my pleasure sir
don't know why there are so small number of views on your videos, i found your teaching to be efficient, fun and easy to understand!
"definitely subscribing!"
Thanks for your interest. Feel free to share and let others know :-)
Magnific, I´ve been looking for some proper explanation on impulse, impulse response and convolution of LTI systems and your class made it all clear, Thanks !!!!
The clearest convolution demonstration I've ever watched. Thx professor :)
Thank you for your comment.
unbelievable! best convolution explanation I have ever seen
Love this professor! I hate slides! :) Thanks from Italy, you helped me a lot for studying "Automatic Control" exam.
Thanks for your kindness. I am glad it helped.
many love to you for the one who post this and for the sensei
This lecture really brought it together for me. Thank you, sir.
Hello I found your videos very useful. Thank you so much. But one thing I want to suggest for you is that it would be much convenient if you write time in the description box. For example, sifting property (starts at --:--) convolution starts at --:--
Thank you for your good suggestion. It sounds like a good idea that I will try to incorporate when I have time :-). In the meantime, if you happen to what a video and do that in the comments I will be happy o place them in the description box for others to use. Once again thanks for your input.
Hi, Thanks for these videos.
I think the doubt student had at time 21:00 was two things.
a). u(t-2) - which you had explained clearly. but also,
b) why the u(t-2) was giving a value of 2 at t =2? Since that function was getting added on top of the previous function it went to 2 and not 1 ,as the u(t) normally would.
Since the addition of u(t-2) was doing these two things simultaneously, it was probably not apparent. I feel.
00:02 Introduction to unit step function and its shifted versions
02:08 The Dirac delta function is defined as a pulse function.
07:16 The Delta function has infinite height at 0 and 0 height elsewhere
09:33 Dirac Delta and Step Function
14:45 Building functions using basic singularity functions
17:11 Discussing structure functions and creating jumps
22:23 Linear systems can be reduced to smaller functions and expressed as a sum of their responses.
24:25 Functions can be deconstructed into elementary singularity functions.
29:56 Function approximation using lookup tables
32:12 Dirac Delta represents functions in the limit of Delta going to zero.
37:56 The sifting property allows you to take out a specific value from a function.
40:32 One-sided functions have value 0 for T < 0, related to time definition and causality.
44:26 Linear systems operate on inputs to produce outputs.
46:58 Linear systems are impervious to scaling and only respond to functions of time.
52:27 Impulse response and time-invariant systems
55:01 Assumptions of linearity and time invariance
59:07 Impulse response reveals true system characteristics
1:01:15 For an LTI system, you can determine the response to any input using the convolution of the impulse response and the input.
Crafted by Merlin AI.
Thank you.
At 30:25 when you write f(t)=summation , I got really confused should it not be F(t) or some sort of integral of the function because it is the area under the function. Are we approximating the function drawn or are we approximating the integral of the function drawn? I would appreciate if anybody could clearify!
Yep I believe there was a mixup there the way prof. worded it. We are approximating the function f(t) (NOT the area!) by summing all these individual pulses scaled by f(tau). We are not getting area under the function, neither are we connecting the "dots" per each f(tau) - we are essentially superpositioning all these pulse function (impulses) to compose the shape of f(t)
Thank you so much for this amazing lecture.
Amazing teaching of a confusing topic! Hope to see more videos in electrical engineering!
Simply Excellent !
the best demonstration for convolution integral.
thanks alot
Thank you Sir very clar audio . May you please make a lecture on step responce on an RC circuit
for Electronic Engineers
Such a great lecture, thank you very much!
Absolutely brilliant! Thank you Professor!
Shouldn't the d(Tou) be equal to n.(dDelta) ? Your lessons are very inspiring, thank you so much and sincere greetings from Turkey.
سلام استاد
بسیار از تدریس شما استفاده کردم. من دانشجوی ارشد عمران هستم و برای پایان نامه نیاز به مباحث کنترل دارم و از فیلم های شما بسیار استفاده می کنم. ممنون که اونها رو در یوتیوب قرار دادید.
Philosophical, characterize a person with impulse response
Thank you very much! Incredible clear!
a question professor, is it not + 2u( t - 2 ) at 19:32 ? I want to achieve a height of 2 at that point ?
1:01:55
- another way to look at it :
We do not need to worry about how the output will behave to a given input to this LTI system, as long as we know the system's Impulse response. We can simply add up a ' lookup table-value' of the input multiplied by the impulse response of the system (which we know) and add them over -/+ infinity.
is that understanding correct?
Well, it is more than that. It is not simply a one-to-one function converting and instantaneous input value to and instantaneous output value, rather it captures the aggregate effect of the input from negative infinity to present time (for a causal system). So it is a lot more, because is captures the effect of the 'memory' of the system of its past. Hope this helps.
So nice
I wish I can transfer to caltech just to be taught by you
38:00 - Only one Dirac Delta will be non-zero, and that's the one that will sift the function value at time t.
At 37:20 - that integral is equal to f(tau), which is a particular value, so how that value can be similar to the function f(t).
f(t) is a f(tau) function for different tau values.
Someone, please explain this.
Gents I am sorry for my previous comment, as the quality of video by time it's been improve I think it's due to the connection with Internet I am very sorry
No problem. The videos are in 1080P60 :-)
At 14:36, the professor said "The left wing is completely suppressed" and smiled. Why else anyone hasn't noticed that
Thanks a lot , one thing the whit board continent is not really clear on video
a girl was eating food...