Introduction to Wavelet Theory and its Applications
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- Опубликовано: 15 сен 2024
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Hello Viewers. In this video, the wavelet transform theory and its applications are explained.
This video includes following components,
* Fourier Transform and its limitations.
* Short Time Fourier Transform and its drawbacks.
* Wavelet theory.
* Wavelet Transform (Continuous and Discrete Wavelet Transform).
* Filter Banks theory for DWT.
* Wavelet Types.
* Wavelet Applications.
* Wavelets in MATLAB.
Wavelet transform is a very powerful tool in the field of Signal and Image processing. It is also very useful in many other areas.
Therefore, it becomes important to go through the wavelet theory to get better understanding of signal and image processing applications.
its a great effort from your side sir , thank you very much for the video
Thank you so much, Dr. Verma. That was very helpful. I will be forever grateful for this wavelets series videos. I have searched many websites and wasted many an hour because I was not getting the thorough knowledge you provided in just a single video.
Very nice introduction video to wavelet analysis and corresponding demo in MATLAB, thank you!
very good way of explaining with good visuals, thank you so much sir
Concise yet informative. The use of MATLAB examples and commands throughout the lecture greatly helped convey the concept. This video was perfectly executed.
Thank you for your time and effort! Your explanation immensely helped me in my undergrad project!
Excellent video which compares with FFT. Just what I was looking for.
Thank you for the video. It helps me so much to understand the concept.
Thank so much sir 🙏🏻 for explaining of wavelet transform in detail with easy language 🙏🏻🙏🏻
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Thank you so much for your informative video,which helps a lot on my reports for my Signals and Systems...
thanks really helped me in my college project
very informative.... need more insights of filter bank..
Thank you. Very useful infomation in a short time!
fantastic. Thanks sir 🙏
This was sooo good! thanks
Excellent explanation.
Sir nice video
Simple and clear, thank you sir.
Thanks sir you are incredible 🌹🌹🌹🌹
sir i find your videos remarkably informative. you should have much more subs
Very informative thanks.
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Hi professor, how can I extract features from a set of 19-channel electroencephalogram signals in MATLAB with .mat format?
Hello Dr verma , how are you? I wanted to ask you something. What are the necessary steps to create an image processing project using FPGA and VHDL? Can you give me any advice? I want to use the Haar wavelet but I don't know where to start.
1. First you decide the problem which you want to solve.
2. Let your problem is denoising image with wavelet filters.
3. Then write matlab code for that.
4. Convert that code to vhdl using matlab coder.
5. Load the program to FPGA.
6. The challenge will be the camera interface with FPGA.
It was well explained with good visuals. thank you Prof. Verma
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But what is the connection between the relations at 17:30 and the filter banks at 19:40?
thank you, sir!
Hello sir, This is the very informative video. Thank you for preparing this. I have a one question: What is the difference between bi-orthogonal and orthogonal wavelet transform?
Watch my video "Transform Analysis". There, I have explained orthogonal and bi orthogonal vectors.
very helpful sir.
how can I contact directly sir with you for specific questions?
email
I have a doubt sir, Why we have to take only approximation coefficients for next level decomposition?
This is awesome video, i followed you all step but my matlab did not had wavelet display. do yo have any idea?
U must have wavelet toolbox installed.
Hi,
The tabular figure must be modified in a way that all the boxes have the same area. I mean their height must be decrease from down to up, in this slide.
What is the objective of decomposing the signal into high frequency & low frequency wavelets ? How does it help ?
By this way you can do many things such as denoising, compression etc.
May I ask one question¿ why the icwt of one wavelet coefficient is just a point ¿
What do you want to do with single coefficient?
@@exploringtechnologies9 thank you. I just want to get a better understanding of the equation of inverse continuous wavelet transform(icwt).
According to the icwt equation, in my understanding if it’s correct , the icwt of one cwt coefficient should be in the form of wavelet. But the results is just a point, the values equal to zero other than the translation point of the selected coefficient.
Sir, is it fair to say the Mortlet wavelet is nothing more that a common sinusoidal basis multiplied by a certain window funktion? If that holds true, then Mortlet walelet is nothing more than STFT with very specific window function (instead of rectangular window function).
No.
There is difference between STFT and Wavelet transform. Wavelet transform doesn't suffer with ambiguity of window size selection.
@@exploringtechnologies9 Yes, I fealized this too after writing my question.
Thank you, Sir
What resources did you use for this presentetaion? and Can you recommend any book for Wavelet Theory? Thanks.
Few slides are my own original content and other slides include material from various other resources such as books of S. Mallat, I. Daubecheis, M. Misity and matlab documentation.
@@exploringtechnologies9 May I ask one question¿ why the icwt of one wavelet coefficient is just a point ¿
make discrete wavelet transform video in hdl
what is the difference between Cross Wavelet Transform and a Wavelet coherence ?
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hi sir, what does 4 means in sym4
is there any special meaning behind numbers in wavelets
Eg: sym1,sym2,....,Db1,Db2,...
Watch this video,
ruclips.net/video/1l04lrnv5ws/видео.html
Tq sir
Thank you for very informative lecture sir. Sir I had one doubt then, Is Fourier spectrum same for both its original image and it's mirror one?
Yes. Please watch my video on 2D Fourier transform.
@@exploringtechnologies9 Thank you sir. I will watch sir🙂
Sir please provide ppt of this one
Sir Please explain orthoganal and Bioorthoganal wavelet
For any transform, the basis functions must be orthogonal. So wavelets as basis functions are orthogonal. Soon i will make a video on understanding concepts of orthogonality, biorthogonality, basis functions.