Introduction to Signal Processing: An Overview (Lecture 1)

This lecture is part of a a series on signal processing. It is intended as a first course on the subject with data and code worked in both matlab and python. The lectures are from the textbook Oppenheim, Willsky and Nawab, "Systems and Signals".

[lukanguyen]

One of the best lectures on DSP I've ever seen.
Thanks a ton, professor :)

[redondoj]

Dear Professor Nathan. Thank you very much for sharing your knowledge through these videos. Excellent quality of the same in its content. Thanks again. Best and Blessed!

[wordofmouthkictchen]

This is really helpful and Nathan Kutz is well organized with his thoughts and how he presents this subject. Keep it coming sir.

[channagirijagadish]

Excellent Introductory Lecture. Much appreciated.

[gammingfatma]

Thank you, I'm really happy that you be back!

[andrewrodriguez]

Amazing, I’m an EE student and I found this lecture very interesting/helpful! I’m excited to see the rest of these lectures

[jacobmalof]

I think this is exactly what I was looking for. Thank you.

[mohamadhamoudy]

Dear Professor Nathan, thanks a lot for theses great lectrures, please could you kindly add lectures on wavelets on signal processing and compression .

[bluebird]

Thank you for the great lecture. I think the name of the book is "Signals and systems"

[ibpbylm]

For the Average Signal Power in the discrete case, I think we should be dividing by n_2 - n_1 + 1, since that is how many data points you will have in the interval from n_1 to n_2.

[princyok]

Are the PowerPoint slides for this course available anywhere? You said there will be an accompanying website. None is provided in the description.

[jacobmalof]

Can a signal be sent and received that is not em in nature? What forces exist outside of em? Gravity? Time? …
Which invisible forces can be translated into a useful spectra we can then perceive with our senses?
What are the limiting factors preventing us from translating more?

[zrmsraggot]

Hello
When talking about the Webb at 18:00 and the image we see despite the fact it's looking at Infrared spectrum, can we compare it to coordinate system and a kind of Fourier Transform ? Or not at all ... would strongly appreciate an answer, thanks