Time Invariance: Conceptual Introduction

[@seandever2272]

Set the video speed to 1.25

[@BirgerBurgerBargir]

+Sean Dever That's much better, thanks

[@FireFiveStar]

i use 2x and its a comfortable speed

[@Braindeadvideos]

Thank you very much! I am working on neural coding, and this concept is indespensable for neural response function, which features Dirac's delta function (or Kroenecker's). I have been having a hard time wrapping my mind around the formulas, but you did an excellent job explaining the concept.

[@iamsecrets]

Who would have thought that it was actually that simple. Nice work!

[@swethajan]

I have been coming across this 'LTI' term for quite a while and failed to understand what that was untill I bumped into this video! thanks!

[@robb1324]

Thank you for this! I watched the mathematical video first and was completely lost. After watching this, the mathematical video makes sense! Subscribed.

[@larich370]

Thank you so much, sir! Your explanation is pretty clear and helped me understand this concept completely! Thanks again!!!

[@jazminmosqueda8263]

I love your videos! I like your low-key humor! I laughed out loud a few times! Thank you for this!!!!

[@elnapa091]

Very nice conceptual explanation! Thanks a lot, Darryl

[@jonmachler8077]

The guy who made this speaks in a time invariant manner

[@DarrylMorrell]

@dhanoarajvir1 No, the video is showing that a system that multiplies its input by cos wt in the time domain is not time invariant. Because the system is not time invariant, we would have a difficult time computing the output of the system using convolution.

[@LifeReDiscovery]

Thanks, Darryl. Very intuitive. You should make more like this.

[@sajib_biswas_shuvo]

Wonderful explanation. Helped me a lot. Thanks!

[@jessicagagne6146]

this was so incredibly helpful thank you!!

[@mnada72]

Thank you very much for the super helpful explanation

[@prestoX]

Thanks a lot Sir, helped me understand the concepts for GATE exam.

[@123ise]

I love these videos they have helped me alot. Its a good quick review. Keep it up.

[@rutvikmavani1535]

very good explanation .

[@ErfanHossainShoaib]

Frankly, This is nice explanation.... A lot of thanks...... :D

[@xiaonan238]

nice explaination

[@hamidfazli6936]

Thanks. that was very helpful!

[@dobraOsoba]

wow, this is awesome and fun!

[@VinasirajanViruthshaan]

Thank you sir

[@fyqarahman2646]

I feel sleepy everytime i watch your videos...

[@AbhijithByrappa]

Loved your videos. \M/

[@lizerdboy79]

very good, thanks

[@Spark_Books]

Thanks!

[@jerryrice885]

can anyone help? so this is time invariant because you get them same result no matter the time period?

[@jerryrice885]

Thanks MJA, ive already taken Laplace transforms and process control and simulation... let just say this video didnt make it any easier to learn that witchcraft of a science... however it is cool and incredibly useful!

[@kirilpetrov2331]

Can a system be linear but time variance?

[@clintonleeedwards]

Yes. An amplifier can be linear but it's performance can change (degrade) with time.

[@clintonleeedwards]

His example of cos(wt) is an example of a linear system that is time varying.

[@hamzanasir58]

awsomee,,, thumbs up :)

[@surathgaladeniya5988]

thanks

[@horizontaalschaalbaar9470]

Type Invariance:
Not every Animal[] can be treated as if it were a Cat[], an Animal[] may contain a Dog.
A Cat[] cannot be treated as an Animal[], it should always be possible to put a Dog into an Animal[].

[@dhanoarajvir1]

here he did one thing wrong ..... he is taking Y(t)=X(t) x COS(wt) (x means multiplication )
as here he is dealing in time domain...it should be Y(t)=X(t) * COS(wt) (* means convolution)

[@uzairwarraich8961]

can you speak any slower ommg!!