The LMS algorithm and ADALINE. Part I - The LMS algorithm 

I'm studying digital signal processing right now, and i have to say your explanations made it super clear. i feel honored to be taught by the man who invented the algorithm himself! Thank you so much for making this video

Watching this lecture is such a privilege. Thanks Mr. Widrow!

This is how insightful explanations comes out when the discoverer himself teaches. I wish all discoverers make videos to explain their innovations.

This is one of the most beautiful things I have seen in RU-vid. Thank you!

It felt like I was sitting in Prof. Widrow's class and he actually answered every single possible question in this video!

I had no idea that there was such a deep explanation for this LMS algorithm. Wow, isn't it amazing to hear it from the original scientist himself!

How lucky we are, having this huge scientist bringing us an explanation of his own work! THANKS A LOT FOR SHARING

This is an absolute treasure!! Thank you thank you so much!!

We are blessed to listen directly from the guy who formulated the worldwide most used algorithm to train Neural Networks.

This is absolutely amazing! First reading about this, taking a break from reading, going on to youtube just to see what other people make on the subject, just to find the actual creator describing it! i love youtube!

Wow from the man himself, he did two amazing things in one go, design a basic neuron and a training mechanism for it. I always thought LMS was developed long time ago and the neuron came much later. Very precious video

This is Gold! I came here trying to find a deeper LMS Algorithm explanation, but before playing it I didn't realize that it was from Bernard Widrow! Awesome video and great explanation!

I absolutely love your explanation. Thanks for solving the mystery for me=)

Thanks for sharing! It was explained so clearly!

What an absolute hero. Thank you so much for the video :)

Beautiful explanation. Thank you!

Marvelous... Thanks a lot for sharing

This is just amazing! Hearing about LMS from the creator itself. Thank you so much, it was truly helpful. :)

Thank you for developing this magnificent algorithm.

Yes. How we are lucky. He is a famous scientist for everyone who learn ANN techniques. We are all happy with this lecture. Thanks for teaching us.

Thanks a lot for this video! Your explanation is very intuitive.

This is beauty

Great!! , amazing, who enunciated the principle explain the theory.

Fantastic! We are fortunate to have this from the original source.

Thanks for sharing sir..........

Thank you so much, very useful, it's an honnor that it is presented by the original autheur

大神亲自讲解，太棒了！

wow just wow, brilliant lecture

What an Informative lecture. Each and everything in detail. Like from Pakistan.

Incredible content.

very clear explanation with practical demonstration,

Thank you so much for this beautiful explanation

Excellent !

It would be great if you can share more of your discoveries with us.

thanks for sharing !!

thanks for sharing!

Amazing. Thanks

Uma lenda viva!!

He is such a fine professor that everyone who falls under his supervision is fostered to success and excellence. His ability to retain and protect talent is only challenged by those advising the likes of Gauss. No one would go homeless under his supervision, much less be marooned in an authoritarian regime.

Thank you!

Adam ben yaptım dedi. Bu kadar önemli bir konuyu babasından dinlemekte çok ayrı bir ayrıcalık.

Thank u sir👍

nyc

You have explained your LMS algorithm very well and I tried to use for beamforming. But in vain. Can you help me in this regard?

Little did he know 63 years ago, this will lead to one of the biggest inventions done by humans. AI and all neural networks follow the same concept as the backbone.

philosophical lecture

I’m on cloud nine to listen to this lecture from the original creator himself.❤️

👍

1959. wow

sir why have not you added bias weight in y

Neural nets way before they were cool

@8:19 sigmoid's output is between 0 and 1, not -1 and 1.

Why to use linear filter, when there is very simple and effective nonlinear analog www.ezcodesample.com/UAF/UAF.html which is a Urysohn operator instead of linear combination.