1:30 Signal concept. 2:45 Signal examples. 4:30 Extracting information. Signaling processing examples. 3 processing issues: 1) eliminating noise on a time varying signal (unwanted distortion or information) 2) eliminating distortion (not seeing clear edges in an image is a noise that hides information) 3) processing signals in time to know something. (time series evaluation for understanding) These all are related to #3, the heart beat patterns, the egdes tell us about locational details, and the airplane traveling are number three. There is no filtering or cleaning of a signal needed first. Calculus - for understanding of frequency domain Linear algebra - dot or inner product. Probability (modeling) and statistics (averages and observations) Information is interesting. It contains a narrative that provides human understanding. I've been studying data analytics and it appears to ignore signal processing in many ways. It still blows me away that brain imaging still doesn't really study time series imaging as it applies to thought.
I had been looking for some articles on applications of signal processing and none of them were helpful. Luckily I found your video. Thank you so much.
I really liked this video; it is structured well, down to the point, explained very simply and yet precisely. Also, your voice and manner of speaking is clear and pleasant. Thank you!
Sir, you deserve public recognition for these brilliant lectures. THANK YOU so much and leave your current job and come and teach at Oxford Brookes- we NEED YOU- we will even through in a nice cup of tea and a piece of cake..
I passed an exam on this course yesterday, and that felt great. It involved a lot of Fourier Transforms, convolution integrals, Fourier Series of arbitrary periodic signals and things like that, and it was a bit confusing, but pretty fun as well.
Mr Van Veen - I have a question regarding example 2.8 in your book 'Signal and Systems' 2005, 2nd addition, where for the interval t>5, the text indicates an answer of -2. Has this been revised? How do I go about clarifying my issue?
Thanks so much fopr the class! Could anyone tell me what does "overhead" mean in signal processing? (for example, overhead in audio encoding). Thx a lot!
1:30 Signal concept.
2:45 Signal examples.
4:30 Extracting information. Signaling processing examples.
3 processing issues:
1) eliminating noise on a time varying signal (unwanted distortion or information)
2) eliminating distortion (not seeing clear edges in an image is a noise that hides information)
3) processing signals in time to know something. (time series evaluation for understanding)
These all are related to #3, the heart beat patterns, the egdes tell us about locational details, and the airplane traveling are number three. There is no filtering or cleaning of a signal needed first.
Calculus - for understanding of frequency domain
Linear algebra - dot or inner product.
Probability (modeling) and statistics (averages and observations)
Information is interesting. It contains a narrative that provides human understanding. I've been studying data analytics and it appears to ignore signal processing in many ways.
It still blows me away that brain imaging still doesn't really study time series imaging as it applies to thought.
I had been looking for some articles on applications of signal processing and none of them were helpful. Luckily I found your video. Thank you so much.
I really liked this video; it is structured well, down to the point, explained very simply and yet precisely. Also, your voice and manner of speaking is clear and pleasant. Thank you!
Sir, you deserve public recognition for these brilliant lectures. THANK YOU so much and leave your current job and come and teach at Oxford Brookes- we NEED YOU- we will even through in a nice cup of tea and a piece of cake..
Not "through in"; "throw in"! He's going to be terrified of what you "through him" next! No, he's not gonna come!
he got enough public recognition. To proof my point , simply look at the textbook most University Signal Processing course is using.
I passed an exam on this course yesterday, and that felt great.
It involved a lot of Fourier Transforms, convolution integrals, Fourier Series of arbitrary periodic signals and things like that, and it was a bit confusing, but pretty fun as well.
great introduction! more especially for beginners
good work man, I like how you capture the essence of signal processing
Thank you very much Barry. Really very helpful
Amazing introduction!! Where can I learn the concepts in more details?
Very nice! Thank you
Great content, just a little slow on the delivery. Thanks for your thoroughness!
Thanks. good points abt SP.
Super interesting, thank you.
Mr Van Veen - I have a question regarding example 2.8 in your book 'Signal and Systems' 2005, 2nd addition, where for the interval t>5, the text indicates an answer of -2. Has this been revised? How do I go about clarifying my issue?
Great introduction. Got value from this.
Thank you.
thanks for a great discussion
Thanks so much fopr the class! Could anyone tell me what does "overhead" mean in signal processing? (for example, overhead in audio encoding). Thx a lot!
i got multivariable calc and ode background is that enough for this course because next year i have to get DSP.what is the order?
Thank You
WELL DONE
Really good video!!!
Hello, can you send the explanation file in ppt format please
Thank you
Thank you sir
Is DSP considered subset of audio , telecommunications , signals or control ?
congratulations great content, but the audio was horrible
Thanks !
Thankyou 👍
amazing lect
nice
thanks for this intro :)
very clear, thank you
thanks, brief and no cringy discussion.. jesus youtube is so shit these days
awesome
thanks for sharing
I'm thinking why there are 8 dislikes...
fabbb
:p
Thank you.