Exact(13)
The H 2, H ∞, and l 1 norm designs have the least H 2, H ∞, and l 1 norms, respectively.
Following Nilsrakoo and Saejung [6] let AN2 be the family of all absolute and normalized (i.e., || 1, 0)|| = || 0, 1)|| = 1) norms on ℝ2.
All three designed filters have less H 2, H ∞, and l 1 norms as compared with optimal feedback filters in [6] and [11].
It can be observed that all three designed filters have less H 2, H ∞ and, l 1 norms than the optimal feedback filters in [6] and [11].
Again, our proposed H 2, H ∞, and l 1 norm designs have the least H 2, H ∞, and l 1 norms, respectively.
Consider now that data-fitting term in the CS reconstruction problem uses the Huber cost function that combines the ℓ 2 and ℓ 1 norms.
Similar(47)
where ∥.∥1 is the l 1 norm.
where |·| denotes the l 1 norm.
Hence, we use the l − 1 norm.
The H ∞ and l 1 norm designs exhibit an equivalent l 1 norm, while the H 2 and H ∞ norm designs have an equivalent H 2 norm.
with minimization of the l 1 norm (BSS-l 1).
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