Communities

Writing
Writing
Codidact Meta
Codidact Meta
The Great Outdoors
The Great Outdoors
Photography & Video
Photography & Video
Scientific Speculation
Scientific Speculation
Cooking
Cooking
Electrical Engineering
Electrical Engineering
Judaism
Judaism
Languages & Linguistics
Languages & Linguistics
Software Development
Software Development
Mathematics
Mathematics
Christianity
Christianity
Code Golf
Code Golf
Music
Music
Physics
Physics
Linux Systems
Linux Systems
Power Users
Power Users
Tabletop RPGs
Tabletop RPGs
Community Proposals
Community Proposals
tag:snake search within a tag
answers:0 unanswered questions
user:xxxx search by author id
score:0.5 posts with 0.5+ score
"snake oil" exact phrase
votes:4 posts with 4+ votes
created:<1w created < 1 week ago
post_type:xxxx type of post
Search help
Notifications
Mark all as read See all your notifications »
Q&A

Comments on Why is the Linear Time-Invariant System (LTI) dominant in Signal processing?

Post

Why is the Linear Time-Invariant System (LTI) dominant in Signal processing?

+1
−0

I just want to know why the Linear time-invariant(LTI) systems are a rich class in Signal Processing. Ofcourse there are different systems but still LTI is stressed a lot in academia. Is there any good reason for that? Also how well that system is used in professional signal processing? Please provide some practical insight.

History
Why does this post require moderator attention?
You might want to add some details to your flag.
Why should this post be closed?

1 comment thread

General comments (1 comment)
General comments
Pete W‭ wrote over 3 years ago · edited over 3 years ago

LTI works so well, it eventually takes almost no time to use. One can solve the "inside case" of many, many design problems using locally-linearized approximations, do this in like 20 minutes, and then spend days on analysis of obscure "edge cases". So it seems like all the time spent on more advanced effort goes into, perhaps, non-linear stuff, but that is really a sign of how effective LTI principles actually are.