独立成分分析
From Ufldl
| Line 8: | Line 8: | ||
'''原文''': | '''原文''': | ||
| - | |||
If you recall, in sparse coding, we wanted to learn an over-complete basis for the data. In particular, this implies that the basis vectors that we learn in sparse coding will not be linearly independent. While this may be desirable in certain situations, sometimes we want to learn a linearly independent basis for the data. In independent component analysis (ICA), this is exactly what we want to do. Further, in ICA, we want to learn not just any linearly independent basis, but an orthonormal basis for the data. (An orthonormal basis is a basis (ϕ_1,…ϕ_n) such that if and 1 if i = j). | If you recall, in sparse coding, we wanted to learn an over-complete basis for the data. In particular, this implies that the basis vectors that we learn in sparse coding will not be linearly independent. While this may be desirable in certain situations, sometimes we want to learn a linearly independent basis for the data. In independent component analysis (ICA), this is exactly what we want to do. Further, in ICA, we want to learn not just any linearly independent basis, but an orthonormal basis for the data. (An orthonormal basis is a basis (ϕ_1,…ϕ_n) such that if and 1 if i = j). | ||
| - | |||
'''译文''': | '''译文''': | ||
