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A Linear Map is called invertible or an isomorphism if there is another linear map such that and . We call the inverse to . We say that the vector spaces and are isomorphic if there is an isomorphism , and we use the notation ### Notation We denote the inverse to a linear map to be .
The notion of invertibility and isomorphism are telling us when two vector spaces are “essentially the same”. To get a better sense of why this is true we consider the following:
If is a finite dimensional vector space with , then what this theorem is telling us is that If we are trying to solve a problem about , then we can try to translate that problem to a problem about using an isomorphism , solve the problem using the techniques we’ve learned in and then transfer the solution back to V using
Invertibility
Matrix of Linear Map
Inverse to a Linear Map is Unique
Inverse Property of Matrix of Linear Map
Criterion for Invertibility using Upper Triangular
Isomorphic Vector Spaces have the Same Dimension
Diffeomorphism
Unit
Uniquely Decodable
Distortion Rate Function
Differential Entropy
Multivariate Gaussian
Capacity of Correlated Parallel Gaussian Channels
WSS Predictor Coefficients
Companding Quantization