Method of Least Squares
... Property IV: The eigenvalues of the correlation matrix are real and non-negative. ...
... Property IV: The eigenvalues of the correlation matrix are real and non-negative. ...
4 Elementary matrices, continued
... go to the top of column 2 and, by multiplication and permuting rows if necessary, get a 1 in the (1, 2) slot. If column 2 won’t work, then go to column 3, etc. If you can’t arrange for a leading 1 somewhere in row 1, then your original matrix was the zero matrix, and it’s already reduced. 2. You now ...
... go to the top of column 2 and, by multiplication and permuting rows if necessary, get a 1 in the (1, 2) slot. If column 2 won’t work, then go to column 3, etc. If you can’t arrange for a leading 1 somewhere in row 1, then your original matrix was the zero matrix, and it’s already reduced. 2. You now ...
Lecture 3: Fourth Order BSS Method
... where y(t) = (y1 (t), ..., ym (t))> ∈ Cm , s(t) = (s1 (t), ..., sn (t))> ∈ Cn , A ∈ Cm×n (m ≥ n) and is independent of t, ε(t) is the noise independent of signal. We know {yi (t)} and that si and sj are independent for i 6= j. Our goal is to recover s(t) under the assumption that ε(t) is Gaussian wh ...
... where y(t) = (y1 (t), ..., ym (t))> ∈ Cm , s(t) = (s1 (t), ..., sn (t))> ∈ Cn , A ∈ Cm×n (m ≥ n) and is independent of t, ε(t) is the noise independent of signal. We know {yi (t)} and that si and sj are independent for i 6= j. Our goal is to recover s(t) under the assumption that ε(t) is Gaussian wh ...
